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Sample records for brain integrating models

  1. Allostasis and the Human Brain: Integrating Models of Stress from the Social and Life Sciences

    Science.gov (United States)

    Ganzel, Barbara L.; Morris, Pamela A.; Wethington, Elaine

    2010-01-01

    We draw on the theory of allostasis to develop an integrative model of the current stress process that highlights the brain as a dynamically adapting interface between the changing environment and the biological self. We review evidence that the core emotional regions of the brain constitute the primary mediator of the well-established association…

  2. Predictors of social integration for individuals with brain injury: An application of the ICF model.

    Science.gov (United States)

    Ditchman, Nicole; Sheehan, Lindsay; Rafajko, Sean; Haak, Christopher; Kazukauskas, Kelly

    2016-01-01

    People with brain injury often experience significant challenges to social and community engagement following injury. The purpose of this study was to investigate factors impacting social integration for adults with brain injury using the International Classification and Functioning, Disability and Health (ICF) as a conceptual model. Adults with brain injury (n = 103) recruited through two US state brain injury associations participated in a survey study. Hierarchical regression analysis was used to examine the predictive impact of components of the ICF model on social integration outcomes. Specifically, demographic (age, gender, SES), disability (severity of functional limitations), personal (disability acceptance, social self-efficacy) and environmental (neighbourhood climate, stigma, social support network) factors were entered as four conceptual groups of predictors to examine the incremental contribution of the variance in social integration explained by each set. As hypothesized, the inclusion of each block of predictors significantly improved the model. The overall regression model explained 41% of the variance in social integration. Specifically, SES (β = 0.25), severity of functional limitations (β = 0.29) and social support network (β = 0.29) emerged as the strongest independent predictors. Findings from this study highlight the importance of adopting a biopsychosocial approach to understanding social integration for people with brain injury.

  3. Integration of Brain and Skull in Prenatal Mouse Models of Apert and Crouzon Syndromes.

    Science.gov (United States)

    Motch Perrine, Susan M; Stecko, Tim; Neuberger, Thomas; Jabs, Ethylin W; Ryan, Timothy M; Richtsmeier, Joan T

    2017-01-01

    The brain and skull represent a complex arrangement of integrated anatomical structures composed of various cell and tissue types that maintain structural and functional association throughout development. Morphological integration, a concept developed in vertebrate morphology and evolutionary biology, describes the coordinated variation of functionally and developmentally related traits of organisms. Syndromic craniosynostosis is characterized by distinctive changes in skull morphology and perceptible, though less well studied, changes in brain structure and morphology. Using mouse models for craniosynostosis conditions, our group has precisely defined how unique craniosynostosis causing mutations in fibroblast growth factor receptors affect brain and skull morphology and dysgenesis involving coordinated tissue-specific effects of these mutations. Here we examine integration of brain and skull in two mouse models for craniosynostosis: one carrying the FGFR2c C342Y mutation associated with Pfeiffer and Crouzon syndromes and a mouse model carrying the FGFR2 S252W mutation, one of two mutations responsible for two-thirds of Apert syndrome cases. Using linear distances estimated from three-dimensional coordinates of landmarks acquired from dual modality imaging of skull (high resolution micro-computed tomography and magnetic resonance microscopy) of mice at embryonic day 17.5, we confirm variation in brain and skull morphology in Fgfr2cC342Y/+ mice, Fgfr2+/S252W mice, and their unaffected littermates. Mutation-specific variation in neural and cranial tissue notwithstanding, patterns of integration of brain and skull differed only subtly between mice carrying either the FGFR2c C342Y or the FGFR2 S252W mutation and their unaffected littermates. However, statistically significant and substantial differences in morphological integration of brain and skull were revealed between the two mutant mouse models, each maintained on a different strain. Relative to the effects of

  4. Integration of Brain and Skull in Prenatal Mouse Models of Apert and Crouzon Syndromes

    Directory of Open Access Journals (Sweden)

    Susan M. Motch Perrine

    2017-07-01

    Full Text Available The brain and skull represent a complex arrangement of integrated anatomical structures composed of various cell and tissue types that maintain structural and functional association throughout development. Morphological integration, a concept developed in vertebrate morphology and evolutionary biology, describes the coordinated variation of functionally and developmentally related traits of organisms. Syndromic craniosynostosis is characterized by distinctive changes in skull morphology and perceptible, though less well studied, changes in brain structure and morphology. Using mouse models for craniosynostosis conditions, our group has precisely defined how unique craniosynostosis causing mutations in fibroblast growth factor receptors affect brain and skull morphology and dysgenesis involving coordinated tissue-specific effects of these mutations. Here we examine integration of brain and skull in two mouse models for craniosynostosis: one carrying the FGFR2c C342Y mutation associated with Pfeiffer and Crouzon syndromes and a mouse model carrying the FGFR2 S252W mutation, one of two mutations responsible for two-thirds of Apert syndrome cases. Using linear distances estimated from three-dimensional coordinates of landmarks acquired from dual modality imaging of skull (high resolution micro-computed tomography and magnetic resonance microscopy of mice at embryonic day 17.5, we confirm variation in brain and skull morphology in Fgfr2cC342Y/+ mice, Fgfr2+/S252W mice, and their unaffected littermates. Mutation-specific variation in neural and cranial tissue notwithstanding, patterns of integration of brain and skull differed only subtly between mice carrying either the FGFR2c C342Y or the FGFR2 S252W mutation and their unaffected littermates. However, statistically significant and substantial differences in morphological integration of brain and skull were revealed between the two mutant mouse models, each maintained on a different strain. Relative

  5. An Anatomically Constrained Model for Path Integration in the Bee Brain.

    Science.gov (United States)

    Stone, Thomas; Webb, Barbara; Adden, Andrea; Weddig, Nicolai Ben; Honkanen, Anna; Templin, Rachel; Wcislo, William; Scimeca, Luca; Warrant, Eric; Heinze, Stanley

    2017-10-23

    Path integration is a widespread navigational strategy in which directional changes and distance covered are continuously integrated on an outward journey, enabling a straight-line return to home. Bees use vision for this task-a celestial-cue-based visual compass and an optic-flow-based visual odometer-but the underlying neural integration mechanisms are unknown. Using intracellular electrophysiology, we show that polarized-light-based compass neurons and optic-flow-based speed-encoding neurons converge in the central complex of the bee brain, and through block-face electron microscopy, we identify potential integrator cells. Based on plausible output targets for these cells, we propose a complete circuit for path integration and steering in the central complex, with anatomically identified neurons suggested for each processing step. The resulting model circuit is thus fully constrained biologically and provides a functional interpretation for many previously unexplained architectural features of the central complex. Moreover, we show that the receptive fields of the newly discovered speed neurons can support path integration for the holonomic motion (i.e., a ground velocity that is not precisely aligned with body orientation) typical of bee flight, a feature not captured in any previously proposed model of path integration. In a broader context, the model circuit presented provides a general mechanism for producing steering signals by comparing current and desired headings-suggesting a more basic function for central complex connectivity, from which path integration may have evolved. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

    Science.gov (United States)

    Zhao, Xiaomei; Wu, Yihong; Song, Guidong; Li, Zhenye; Zhang, Yazhuo; Fan, Yong

    2018-01-01

    Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Gene set based integrated data analysis reveals phenotypic differences in a brain cancer model.

    Directory of Open Access Journals (Sweden)

    Kjell Petersen

    Full Text Available A key challenge in the data analysis of biological high-throughput experiments is to handle the often low number of samples in the experiments compared to the number of biomolecules that are simultaneously measured. Combining experimental data using independent technologies to illuminate the same biological trends, as well as complementing each other in a larger perspective, is one natural way to overcome this challenge. In this work we investigated if integrating proteomics and transcriptomics data from a brain cancer animal model using gene set based analysis methodology, could enhance the biological interpretation of the data relative to more traditional analysis of the two datasets individually. The brain cancer model used is based on serial passaging of transplanted human brain tumor material (glioblastoma--GBM through several generations in rats. These serial transplantations lead over time to genotypic and phenotypic changes in the tumors and represent a medically relevant model with a rare access to samples and where consequent analyses of individual datasets have revealed relatively few significant findings on their own. We found that the integrated analysis both performed better in terms of significance measure of its findings compared to individual analyses, as well as providing independent verification of the individual results. Thus a better context for overall biological interpretation of the data can be achieved.

  8. Modeling community integration in workers with delayed recovery from mild traumatic brain injury

    DEFF Research Database (Denmark)

    Mollayeva, T.; Shapiro, C. M.; Mollayeva, S.

    2015-01-01

    Background: Delayed recovery in persons after mild traumatic brain injury (mTBI) is poorly understood. Community integration (CI) is endorsed by persons with neurological disorders as an important outcome. We aimed to describe CI and its associated factors in insured Ontario workers with delayed...... recovery following mTBI. Methods: A cross-sectional study of insured workers in the chronic phase following mTBI was performed at a rehabilitation hospital in Ontario, Canada. Sociodemographic, occupational, injury-related, clinical, and claim-related data were collected from self-reports, medical.......2 +/- 9.9 years old, 61.2 % male) at 197 days post-injury (interquartile range, 139-416 days) were included. The CIQ total and subscale scores were similar to those reported in more severe TBI samples. The CIQ scores were moderately to strongly correlated with various sociodemographic, claim...

  9. Modeling community integration in workers with delayed recovery from mild traumatic brain injury

    DEFF Research Database (Denmark)

    Mollayeva, T.; Shapiro, C. M.; Mollayeva, S.

    2015-01-01

    Background: Delayed recovery in persons after mild traumatic brain injury (mTBI) is poorly understood. Community integration (CI) is endorsed by persons with neurological disorders as an important outcome. We aimed to describe CI and its associated factors in insured Ontario workers with delayed...... recovery following mTBI. Methods: A cross-sectional study of insured workers in the chronic phase following mTBI was performed at a rehabilitation hospital in Ontario, Canada. Sociodemographic, occupational, injury-related, clinical, and claim-related data were collected from self-reports, medical...... married or in a relationship, time since injury, and a diagnosis of possible/probable malingering were independently associated with limited CI. Conclusions: Workers with delayed recovery from mTBI experience difficulty with CI. Insomnia is a particularly relevant covariate, explaining the greater part...

  10. The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

    Science.gov (United States)

    Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

    2016-02-01

    Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

  11. Traumatic brain injury and employment outcomes: integration of the working alliance model.

    Science.gov (United States)

    Kissinger, Daniel B

    2008-01-01

    Individuals who have suffered polytrauma injuries must often contend with a complex constellation of physical, psychological, and psychosocial factors. These variables must be understood and addressed by rehabilitation specialists in order to optimize employment outcomes and overall quality of life for persons who have incurred these injuries. This article provides an abridged review of the current empirical data concerning the relationship between polytrauma and employment outcomes, with a focus on traumatic brain injury (TBI). In addition, Bordin's [4] working alliance model is recommended as a framework for strengthening the relationship between rehabilitation professionals and persons with TBI, thereby optimizing their employment outcomes.

  12. Markers for blood-brain barrier integrity

    DEFF Research Database (Denmark)

    Saunders, Norman R; Dziegielewska, Katarzyna M; Møllgård, Kjeld

    2015-01-01

    known when first introduced, but seem to have been forgotten since. Understanding these limitations is important because Evans blue is still the most commonly used marker of brain barrier integrity and those using it seem oblivious to problems arising from its in vivo application. The introduction......In recent years there has been a resurgence of interest in brain barriers and various roles their intrinsic mechanisms may play in neurological disorders. Such studies require suitable models and markers to demonstrate integrity and functional changes at the interfaces between blood, brain......, and cerebrospinal fluid. Studies of brain barrier mechanisms and measurements of plasma volume using dyes have a long-standing history, dating back to the late nineteenth-century. Their use in blood-brain barrier studies continues in spite of their known serious limitations in in vivo applications. These were well...

  13. HITS-CLIP and integrative modeling define the Rbfox splicing-regulatory network linked to brain development and autism.

    Science.gov (United States)

    Weyn-Vanhentenryck, Sebastien M; Mele, Aldo; Yan, Qinghong; Sun, Shuying; Farny, Natalie; Zhang, Zuo; Xue, Chenghai; Herre, Margaret; Silver, Pamela A; Zhang, Michael Q; Krainer, Adrian R; Darnell, Robert B; Zhang, Chaolin

    2014-03-27

    The RNA binding proteins Rbfox1/2/3 regulate alternative splicing in the nervous system, and disruption of Rbfox1 has been implicated in autism. However, comprehensive identification of functional Rbfox targets has been challenging. Here, we perform HITS-CLIP for all three Rbfox family members in order to globally map, at a single-nucleotide resolution, their in vivo RNA interaction sites in the mouse brain. We find that the two guanines in the Rbfox binding motif UGCAUG are critical for protein-RNA interactions and crosslinking. Using integrative modeling, these interaction sites, combined with additional datasets, define 1,059 direct Rbfox target alternative splicing events. Over half of the quantifiable targets show dynamic changes during brain development. Of particular interest are 111 events from 48 candidate autism-susceptibility genes, including syndromic autism genes Shank3, Cacna1c, and Tsc2. Alteration of Rbfox targets in some autistic brains is correlated with downregulation of all three Rbfox proteins, supporting the potential clinical relevance of the splicing-regulatory network. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  14. HITS-CLIP and Integrative Modeling Define the Rbfox Splicing-Regulatory Network Linked to Brain Development and Autism

    Directory of Open Access Journals (Sweden)

    Sebastien M. Weyn-Vanhentenryck

    2014-03-01

    Full Text Available The RNA binding proteins Rbfox1/2/3 regulate alternative splicing in the nervous system, and disruption of Rbfox1 has been implicated in autism. However, comprehensive identification of functional Rbfox targets has been challenging. Here, we perform HITS-CLIP for all three Rbfox family members in order to globally map, at a single-nucleotide resolution, their in vivo RNA interaction sites in the mouse brain. We find that the two guanines in the Rbfox binding motif UGCAUG are critical for protein-RNA interactions and crosslinking. Using integrative modeling, these interaction sites, combined with additional datasets, define 1,059 direct Rbfox target alternative splicing events. Over half of the quantifiable targets show dynamic changes during brain development. Of particular interest are 111 events from 48 candidate autism-susceptibility genes, including syndromic autism genes Shank3, Cacna1c, and Tsc2. Alteration of Rbfox targets in some autistic brains is correlated with downregulation of all three Rbfox proteins, supporting the potential clinical relevance of the splicing-regulatory network.

  15. Integrated Arts-Based Teaching (IAT) Model for Brain-Based Learning

    Science.gov (United States)

    Inocian, Reynaldo B.

    2015-01-01

    This study analyzes teaching strategies among the eight books in Principles and Methods of Teaching recommended for use in the College of Teacher Education in the Philippines. It seeks to answer the following objectives: (1) identify the most commonly used teaching strategies congruent with the integrated arts-based teaching (IAT) and (2) design…

  16. Creating the brain and interacting with the brain: an integrated approach to understanding the brain.

    Science.gov (United States)

    Morimoto, Jun; Kawato, Mitsuo

    2015-03-06

    In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the 'understanding the brain by creating the brain' approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain-machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  17. Korea Brain Initiative: Integration and Control of Brain Functions.

    Science.gov (United States)

    Jeong, Sung-Jin; Lee, Haejin; Hur, Eun-Mi; Choe, Youngshik; Koo, Ja Wook; Rah, Jong-Cheol; Lee, Kea Joo; Lim, Hyun-Ho; Sun, Woong; Moon, Cheil; Kim, Kyungjin

    2016-11-02

    This article introduces the history and the long-term goals of the Korea Brain Initiative, which is centered on deciphering the brain functions and mechanisms that mediate the integration and control of brain functions that underlie decision-making. The goal of this initiative is the mapping of a functional connectome with searchable, multi-dimensional, and information-integrated features. The project also includes the development of novel technologies and neuro-tools for integrated brain mapping. Beyond the scientific goals this grand endeavor will ultimately have socioeconomic ramifications that not only facilitate global collaboration in the neuroscience community, but also develop various brain science-related industrial and medical innovations. Copyright © 2016. Published by Elsevier Inc.

  18. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  19. Formal learning theory dissociates brain regions with different temporal integration.

    Science.gov (United States)

    Gläscher, Jan; Büchel, Christian

    2005-07-21

    Learning can be characterized as the extraction of reliable predictions about stimulus occurrences from past experience. In two experiments, we investigated the interval of temporal integration of previous learning trials in different brain regions using implicit and explicit Pavlovian fear conditioning with a dynamically changing reinforcement regime in an experimental setting. With formal learning theory (the Rescorla-Wagner model), temporal integration is characterized by the learning rate. Using fMRI and this theoretical framework, we are able to distinguish between learning-related brain regions that show long temporal integration (e.g., amygdala) and higher perceptual regions that integrate only over a short period of time (e.g., fusiform face area, parahippocampal place area). This approach allows for the investigation of learning-related changes in brain activation, as it can dissociate brain areas that differ with respect to their integration of past learning experiences by either computing long-term outcome predictions or instantaneous reinforcement expectancies.

  20. Creating the brain and interacting with the brain: an integrated approach to understanding the brain

    Science.gov (United States)

    Morimoto, Jun; Kawato, Mitsuo

    2015-01-01

    In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. PMID:25589568

  1. Biophysical modeling of brain tumor progression: From unconditionally stable explicit time integration to an inverse problem with parabolic PDE constraints for model calibration.

    Science.gov (United States)

    Mang, Andreas; Toma, Alina; Schuetz, Tina A; Becker, Stefan; Eckey, Thomas; Mohr, Christian; Petersen, Dirk; Buzug, Thorsten M

    2012-07-01

    A novel unconditionally stable, explicit numerical method is introduced to the field of modeling brain cancer progression on a tissue level together with an inverse problem (IP) based on optimal control theory that allows for automated model calibration with respect to observations in clinical imaging data. Biophysical models of cancer progression on a tissue level are in general based on the assumption that the spatiotemporal spread of cancerous cells is determined by cell division and net migration. These processes are typically described in terms of a parabolic partial differential equation (PDE). In the present work a parallelized implementation of an unconditionally stable, explicit Euler (EE(⋆) ) time integration method for the solution of this PDE is detailed. The key idea of the discussed EE(⋆) method is to relax the strong stability requirement on the spectral radius of the coefficient matrix by introducing a subdivision regime for a given outer time step. The performance is related to common implicit numerical methods. To quantify the numerical error, a simplified model that has a closed form solution is considered. To allow for a systematic, phenomenological validation a novel approach for automated model calibration on the basis of observations in medical imaging data is developed. The resulting IP is based on optimal control theory and manifests as a large scale, PDE constrained optimization problem. The numerical error of the EE(⋆) method is at the order of standard implicit numerical methods. The computing times are well below those obtained for implicit methods and by that demonstrate efficiency. Qualitative and quantitative analysis in 12 patients demonstrates that the obtained results are in strong agreement with observations in medical imaging data. Rating simulation success in terms of the mean overlap between model predictions and manual expert segmentations yields a success rate of 75% (9 out of 12 patients). The discussed EE(⋆) method

  2. Integrating Retinoic Acid Signaling with Brain Function

    Science.gov (United States)

    Luo, Tuanlian; Wagner, Elisabeth; Drager, Ursula C.

    2009-01-01

    The vitamin A derivative retinoic acid (RA) regulates the transcription of about a 6th of the human genome. Compelling evidence indicates a role of RA in cognitive activities, but its integration with the molecular mechanisms of higher brain functions is not known. Here we describe the properties of RA signaling in the mouse, which point to…

  3. Brain networks for integrative rhythm formation.

    Directory of Open Access Journals (Sweden)

    Michael H Thaut

    2008-05-01

    Full Text Available Performance of externally paced rhythmic movements requires brain and behavioral integration of sensory stimuli with motor commands. The underlying brain mechanisms to elaborate beat-synchronized rhythm and polyrhythms that musicians readily perform may differ. Given known roles in perceiving time and repetitive movements, we hypothesized that basal ganglia and cerebellar structures would have greater activation for polyrhythms than for on-the-beat rhythms.Using functional MRI methods, we investigated brain networks for performing rhythmic movements paced by auditory cues. Musically trained participants performed rhythmic movements at 2 and 3 Hz either at a 1:1 on-the-beat or with a 3:2 or a 2:3 stimulus-movement structure. Due to their prior musical experience, participants performed the 3:2 or 2:3 rhythmic movements automatically. Both the isorhythmic 1:1 and the polyrhythmic 3:2 or 2:3 movements yielded the expected activation in contralateral primary motor cortex and related motor areas and ipsilateral cerebellum. Direct comparison of functional MRI signals obtained during 3:2 or 2:3 and on-the-beat rhythms indicated activation differences bilaterally in the supplementary motor area, ipsilaterally in the supramarginal gyrus and caudate-putamen and contralaterally in the cerebellum.The activated brain areas suggest the existence of an interconnected brain network specific for complex sensory-motor rhythmic integration that might have specificity for elaboration of musical abilities.

  4. Obesity, fitness, and brain integrity in adolescence.

    Science.gov (United States)

    Ross, Naima; Yau, Po Lai; Convit, Antonio

    2015-10-01

    We set out to ascertain the relationship between insulin resistance, fitness, and brain structure and function in adolescents. We studied 79 obese and 51 non-obese participants who were recruited from the community, all without type 2 diabetes mellitus. All participants received medical, endocrine, neuropsychological, and MRI evaluations as well as a 6-minute walk test that was used to estimate fitness (maximal oxygen consumption). Obese adolescents had significantly thinner orbitofrontal cortices and performed significantly worse on Visual Working Memory tasks and the Digit Vigilance task. Insulin sensitivity and maximal oxygen consumption (VO2 max) were both highly correlated with central obesity and orbitofrontal cortical thickness, although insulin sensitivity was the stronger predictor for orbitofrontal cortical thickness. We also found that VO2 max was the only significant physiological variable related to visual working memory. This is the first study to report positive associations between insulin resistance, VO2 max, and frontal lobe brain integrity in adolescents. Given the importance of brain health for learning and school performance, we conclude that schools should also emphasize physical fitness in order to maintain structural and functional brain integrity and facilitate academic achievement. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. The modular and integrative functional architecture of the human brain.

    Science.gov (United States)

    Bertolero, Maxwell A; Yeo, B T Thomas; D'Esposito, Mark

    2015-12-08

    Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules' processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author-topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network's modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules' functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain's modular yet integrated implementation of cognitive functions.

  6. Modeling Structural Brain Connectivity

    DEFF Research Database (Denmark)

    Ambrosen, Karen Marie Sandø

    The human brain consists of a gigantic complex network of interconnected neurons. Together all these connections determine who we are, how we react and how we interpret the world. Knowledge about how the brain is connected can further our understanding of the brain’s structural organization, help...... improve diagnosis, and potentially allow better treatment of a wide range of neurological disorders. Tractography based on diffusion magnetic resonance imaging is a unique tool to estimate this “structural connectivity” of the brain non-invasively and in vivo. During the last decade, brain connectivity...... has increasingly been analyzed using graph theoretic measures adopted from network science and this characterization of the brain’s structural connectivity has been shown to be useful for the classification of populations, such as healthy and diseased subjects. The structural connectivity of the brain...

  7. HITS-CLIP and integrative modeling define the Rbfox splicing-regulatory network linked to brain development and autism

    OpenAIRE

    Weyn-Vanhentenryck, Sebastien M.; Mele, Aldo; Yan, Qinghong; Sun, Shuying; Farny, Natalie; Zhang, Zuo; Xue, Chenghai; Herre, Margaret; Silver, Pamela A.; Zhang, Michael Q.; Krainer, Adrian R.; Darnell, Robert B.; Zhang, Chaolin

    2014-01-01

    The RNA binding proteins Rbfox1/2/3 regulate alternative splicing in the nervous system, and disruption of Rbfox1 has been implicated in autism. However, comprehensive identification of functional Rbfox targets has been challenging. Here, we perform HITS-CLIP for all three Rbfox family members in order to globally map, at a single-nucleotide resolution, their in vivo RNA interaction sites in the mouse brain. We find that the two guanines in the Rbfox binding motif UGCAUG are critical for prot...

  8. Functional Anatomy of the Thalamus as a Model of Integrated Structural and Functional Connectivity of the Human Brain In Vivo.

    Science.gov (United States)

    Mastropasqua, Chiara; Bozzali, Marco; Spanò, Barbara; Koch, Giacomo; Cercignani, Mara

    2015-07-01

    While methods of measuring non-invasively both, functional and structural brain connectivity are available, the degree of overlap between them is still unknown. In this paper this issue is addressed by investigating the connectivity pattern of a brain structure with many, well characterized structural connections, namely the thalamus. Diffusion-weighted and resting state (RS) functional MRI (fMRI) data were collected in a group of 38 healthy participants. Probabilistic tractography was performed to parcellate the thalamus into regions structurally connected to different cortical areas. The resulting regions were used as seeds for seed-based analysis of RS fMRI data. The tractographic parcellation was thus cross-validated against functional connectivity data by evaluating the overlap between the functional and structural thalamo-cortical connections originating from the parcellated regions. Our data show only a partial overall correspondence between structural and functional connections, in the same group of healthy individuals, thus suggesting that the two approaches provide complementary and not overlapping information. Future studies are warranted to extend the results we obtained in the thalamus to other structures, and to confirm that the mechanisms behind functional connectivity are more complex than just expressing structural connectivity.

  9. Which brain networks related to art perception are we talking about?. Comment on "Move me, astonish me…" delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates; by Matthew Pelowski et al.

    Science.gov (United States)

    Ayala, Francisco J.; Cela-Conde, Camilo J.

    2017-07-01

    The proposal by the Vienna Integrated Model of Art Perception (Pelowski et al., [4]; VIMAP, hereafter) is a valuable and much needed attempt to summarize and understand the cognitive processes underlying art perception. Very important in their model is, as expected, to ascertain the psychological and brain processes correlated with the perception of beauty in art works. In this commentary we'll focus exclusively on the consideration of VIMAP's section 5, ;Model stages and corresponding areas of the brain.; We'll examine the evidence advanced by VIMAP in the section about brain networks related to the perception of art.

  10. Social neuroscience, empathy, brain integration, and neurodevelopmental disorders.

    Science.gov (United States)

    Harris, James C

    2003-08-01

    Paul MacLean has investigated integrated brain functioning through selected brain lesions in animals that disturb circuits necessary for complex behaviors, such as social displays. MacLean is unique in his comparative neurobehavioral approach that emphasizes the evolutionary origins of parenting and social behaviors and the implications of brain changes in the evolution from reptiles (social displays) to mammals (nursing, audiovocal communication, play) to man (self-awareness, intentionality, social context) that link affect and cognition. Subjectively, how "looking with feeling toward others," the basic element in empathy, evolved has been a central concern of his. Neuroimaging studies of social cognition, mother-infant communication, moral behavior, forgiveness, and trust are consistent with particular brain systems being activated in cooperative social behaviors. The identification of mirror neurons is pertinent to MacLean's model of isopraxis and studies of thalamocortical resonances may be pertinent to his neurobehavioral models. Studies of behavioral phenotypes in human neurodevelopmental disorders are consistent with MacLean's model of brain circuits being linked to complex behaviors during development. In autistic disorder, the behavioral phenotype involves disrupted social communication, deviant imaginative play, and motor stereotypies. In Lesch-Nyhan syndrome (LNS), self-injury occurs in individuals with normal sensory systems intact who require and request physical restraint to prevent self-injury; they ask for assistance from others to prevent them from harming themselves. Autism involves the lack of subjective awareness of others intentions and LNS involves a failure in self-regulation and self-control of self-injurious behavior. MacLean's models laid the groundwork for studies focused on understanding brain functioning in these conditions.

  11. Data integration technologies to support integrated modelling

    NARCIS (Netherlands)

    Knapen, M.J.R.; Roosenschoon, O.R.; Lokers, R.M.; Janssen, S.J.C.; Randen, van Y.; Verweij, P.J.F.M.

    2013-01-01

    Over the recent years the scientific activities of our organisation in large research projects show a shifting priority from model integration to the integration of data itself. Our work in several large projects on integrated modelling for impact assessment studies has clearly shown the importance

  12. INTEGRATED CORPORATE STRATEGY MODEL

    Directory of Open Access Journals (Sweden)

    CATALINA SORIANA SITNIKOV

    2014-02-01

    Full Text Available Corporations are at present operating in demanding and highly unsure periods, facing a mixture of increased macroeconomic need, competitive and capital market dangers, and in many cases, the prospect for significant technical and regulative gap. Throughout these demanding and highly unsure times, the corporations must pay particular attention to corporate strategy. In present times, corporate strategy must be perceived and used as a function of various fields, covers, and characters as well as a highly interactive system. For the corporation's strategy to become a competitive advantage is necessary to understand and also to integrate it in a holistic model to ensure sustainable progress of corporation activities under the optimum conditions of profitability. The model proposed in this paper is aimed at integrating the two strategic models, Hoshin Kanri and Integrated Strategy Model, as well as their consolidation with the principles of sound corporate governance set out by the OECD.

  13. Multi-sensory integration in a small brain

    Science.gov (United States)

    Gepner, Ruben; Wolk, Jason; Gershow, Marc

    Understanding how fluctuating multi-sensory stimuli are integrated and transformed in neural circuits has proved a difficult task. To address this question, we study the sensori-motor transformations happening in the brain of the Drosophila larva, a tractable model system with about 10,000 neurons. Using genetic tools that allow us to manipulate the activity of individual brain cells through their transparent body, we observe the stochastic decisions made by freely-behaving animals as their visual and olfactory environments fluctuate independently. We then use simple linear-nonlinear models to correlate outputs with relevant features in the inputs, and adaptive filtering processes to track changes in these relevant parameters used by the larva's brain to make decisions. We show how these techniques allow us to probe how statistics of stimuli from different sensory modalities combine to affect behavior, and can potentially guide our understanding of how neural circuits are anatomically and functionally integrated. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

  14. Brain temperature changes during selective cooling with endovascular intracarotid cold saline infusion: simulation using human data fitted with an integrated mathematical model.

    Science.gov (United States)

    Neimark, Matthew Aaron Harold; Konstas, Angelos Aristeidis; Lee, Leslie; Laine, Andrew Francis; Pile-Spellman, John; Choi, Jae

    2013-03-01

    The feasibility of rapid cerebral hypothermia induction in humans with intracarotid cold saline infusion (ICSI) was investigated using a hybrid approach of jugular venous bulb temperature (JVBT) sampling and mathematical modeling of transient and steady state brain temperature distribution. This study utilized both forward mathematical modeling, in which brain temperatures were predicted based on input saline temperatures, and inverse modeling, where brain temperatures were inferred based on JVBT. Changes in ipsilateral anterior circulation territory temperature (IACT) were estimated in eight patients as a result of 10 min of a cold saline infusion of 33 ml/min. During ICSI, the measured JVBT dropped by 0.76±0.18°C while the modeled JVBT decreased by 0.86±0.18°C. The modeled IACT decreased by 2.1±0.23°C. In the inverse model, IACT decreased by 1.9±0.23°C. The results of this study suggest that mild cerebral hypothermia can be induced rapidly and safely with ICSI in the neuroangiographical setting. The JVBT corrected mathematical model can be used as a non-invasive estimate of transient and steady state cerebral temperature changes.

  15. Computational modeling of neurostimulation in brain diseases.

    Science.gov (United States)

    Wang, Yujiang; Hutchings, Frances; Kaiser, Marcus

    2015-01-01

    Neurostimulation as a therapeutic tool has been developed and used for a range of different diseases such as Parkinson's disease, epilepsy, and migraine. However, it is not known why the efficacy of the stimulation varies dramatically across patients or why some patients suffer from severe side effects. This is largely due to the lack of mechanistic understanding of neurostimulation. Hence, theoretical computational approaches to address this issue are in demand. This chapter provides a review of mechanistic computational modeling of brain stimulation. In particular, we will focus on brain diseases, where mechanistic models (e.g., neural population models or detailed neuronal models) have been used to bridge the gap between cellular-level processes of affected neural circuits and the symptomatic expression of disease dynamics. We show how such models have been, and can be, used to investigate the effects of neurostimulation in the diseased brain. We argue that these models are crucial for the mechanistic understanding of the effect of stimulation, allowing for a rational design of stimulation protocols. Based on mechanistic models, we argue that the development of closed-loop stimulation is essential in order to avoid inference with healthy ongoing brain activity. Furthermore, patient-specific data, such as neuroanatomic information and connectivity profiles obtainable from neuroimaging, can be readily incorporated to address the clinical issue of variability in efficacy between subjects. We conclude that mechanistic computational models can and should play a key role in the rational design of effective, fully integrated, patient-specific therapeutic brain stimulation. © 2015 Elsevier B.V. All rights reserved.

  16. A Culture-Behavior-Brain Loop Model of Human Development.

    Science.gov (United States)

    Han, Shihui; Ma, Yina

    2015-11-01

    Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases

    Directory of Open Access Journals (Sweden)

    Ilya eZaslavsky

    2014-09-01

    Full Text Available Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today’s data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI. A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS, a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML: XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POIs, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas

  18. Q-ball imaging models: comparison between high and low angular resolution diffusion-weighted MRI protocols for investigation of brain white matter integrity

    Energy Technology Data Exchange (ETDEWEB)

    Caiazzo, Giuseppina; Trojsi, Francesca; Cirillo, Mario; Tedeschi, Gioacchino [MRI Research Center SUN-FISM-Neurological Institute for Diagnosis and Care ' ' Hermitage Capodimonte' ' , Naples (Italy); Second University of Naples, Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, Naples (Italy); Esposito, Fabrizio [University of Salerno, Department of Medicine and Surgery, Baronissi (Salerno) (Italy); Maastricht University, Department of Cognitive Neuroscience, Maastricht (Netherlands)

    2016-02-15

    Q-ball imaging (QBI) is one of the typical data models for quantifying white matter (WM) anisotropy in diffusion-weighted MRI (DwMRI) studies. Brain and spinal investigation by high angular resolution DwMRI (high angular resolution imaging (HARDI)) protocols exhibits higher angular resolution in diffusion imaging compared to low angular resolution models, although with longer acquisition times. We aimed to assess the difference between QBI-derived anisotropy values from high and low angular resolution DwMRI protocols and their potential advantages or shortcomings in neuroradiology. Brain DwMRI data sets were acquired in seven healthy volunteers using both HARDI (b = 3000 s/mm{sup 2}, 54 gradient directions) and low angular resolution (b = 1000 s/mm{sup 2}, 32 gradient directions) acquisition schemes. For both sequences, tract of interest tractography and generalized fractional anisotropy (GFA) measures were extracted by using QBI model and were compared between the two data sets. QBI tractography and voxel-wise analyses showed that some WM tracts, such as corpus callosum, inferior longitudinal, and uncinate fasciculi, were reconstructed as one-dominant-direction fiber bundles with both acquisition schemes. In these WM tracts, mean percent different difference in GFA between the two data sets was less than 5 %. Contrariwise, multidirectional fiber bundles, such as corticospinal tract and superior longitudinal fasciculus, were more accurately depicted by HARDI acquisition scheme. Our results suggest that the design of optimal DwMRI acquisition protocols for clinical investigation of WM anisotropy by QBI models should consider the specific brain target regions to be explored, inducing researchers to a trade-off choice between angular resolution and acquisition time. (orig.)

  19. Work-up times in an integrated brain cancer pathway

    DEFF Research Database (Denmark)

    Lund Laursen, Emilie; Rasmussen, Birthe Krogh

    2012-01-01

    The integrated brain cancer pathway (IBCP) aims to ensure fast-track diagnostics and treatment for brain cancers in Denmark. This paper focuses on the referral pattern and the time frame of key pathway elements during the first two years following implementation of the IBCP in a regional neurology...

  20. Integrated Assessment Model Evaluation

    Science.gov (United States)

    Smith, S. J.; Clarke, L.; Edmonds, J. A.; Weyant, J. P.

    2012-12-01

    Integrated assessment models of climate change (IAMs) are widely used to provide insights into the dynamics of the coupled human and socio-economic system, including emission mitigation analysis and the generation of future emission scenarios. Similar to the climate modeling community, the integrated assessment community has a two decade history of model inter-comparison, which has served as one of the primary venues for model evaluation and confirmation. While analysis of historical trends in the socio-economic system has long played a key role in diagnostics of future scenarios from IAMs, formal hindcast experiments are just now being contemplated as evaluation exercises. Some initial thoughts on setting up such IAM evaluation experiments are discussed. Socio-economic systems do not follow strict physical laws, which means that evaluation needs to take place in a context, unlike that of physical system models, in which there are few fixed, unchanging relationships. Of course strict validation of even earth system models is not possible (Oreskes etal 2004), a fact borne out by the inability of models to constrain the climate sensitivity. Energy-system models have also been grappling with some of the same questions over the last quarter century. For example, one of "the many questions in the energy field that are waiting for answers in the next 20 years" identified by Hans Landsberg in 1985 was "Will the price of oil resume its upward movement?" Of course we are still asking this question today. While, arguably, even fewer constraints apply to socio-economic systems, numerous historical trends and patterns have been identified, although often only in broad terms, that are used to guide the development of model components, parameter ranges, and scenario assumptions. IAM evaluation exercises are expected to provide useful information for interpreting model results and improving model behavior. A key step is the recognition of model boundaries, that is, what is inside

  1. Dynamic Functional Segregation and Integration in Human Brain Network During Complex Tasks.

    Science.gov (United States)

    Shen Ren; Junhua Li; Taya, Fumihiko; deSouza, Joshua; Thakor, Nitish V; Bezerianos, Anastasios

    2017-06-01

    The analysis of the topology and organization of brain networks is known to greatly benefit from network measures in graph theory. However, to evaluate dynamic changes of brain functional connectivity, more sophisticated quantitative metrics characterizing temporal evolution of brain topological features are required. To simplify conversion of time-varying brain connectivity to a static graph representation is straightforward but the procedure loses temporal information that could be critical in understanding the brain functions. To extend the understandings of functional segregation and integration to a dynamic fashion, we recommend dynamic graph metrics to characterise temporal changes of topological features of brain networks. This study investigated functional segregation and integration of brain networks over time by dynamic graph metrics derived from EEG signals during an experimental protocol: performance of complex flight simulation tasks with multiple levels of difficulty. We modelled time-varying brain functional connectivity as multi-layer networks, in which each layer models brain connectivity at time window t + Δt. Dynamic graph metrics were calculated to quantify temporal and topological properties of the network. Results show that brain networks under the performance of complex tasks reveal a dynamic small-world architecture with a number of frequently connected nodes or hubs, which supports the balance of information segregation and integration in brain over time. The results also show that greater cognitive workloads caused by more difficult tasks induced a more globally efficient but less clustered dynamic small-world functional network. Our study illustrates that task-related changes of functional brain network segregation and integration can be characterized by dynamic graph metrics.

  2. Integrated Assessment Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Edmonds, James A.; Calvin, Katherine V.; Clarke, Leon E.; Janetos, Anthony C.; Kim, Son H.; Wise, Marshall A.; McJeon, Haewon C.

    2012-10-31

    This paper discusses the role of Integrated Assessment models (IAMs) in climate change research. IAMs are an interdisciplinary research platform, which constitutes a consistent scientific framework in which the large-scale interactions between human and natural Earth systems can be examined. In so doing, IAMs provide insights that would otherwise be unavailable from traditional single-discipline research. By providing a broader view of the issue, IAMs constitute an important tool for decision support. IAMs are also a home of human Earth system research and provide natural Earth system scientists information about the nature of human intervention in global biogeophysical and geochemical processes.

  3. Hierarchical models in the brain.

    Directory of Open Access Journals (Sweden)

    Karl Friston

    2008-11-01

    Full Text Available This paper describes a general model that subsumes many parametric models for continuous data. The model comprises hidden layers of state-space or dynamic causal models, arranged so that the output of one provides input to another. The ensuing hierarchy furnishes a model for many types of data, of arbitrary complexity. Special cases range from the general linear model for static data to generalised convolution models, with system noise, for nonlinear time-series analysis. Crucially, all of these models can be inverted using exactly the same scheme, namely, dynamic expectation maximization. This means that a single model and optimisation scheme can be used to invert a wide range of models. We present the model and a brief review of its inversion to disclose the relationships among, apparently, diverse generative models of empirical data. We then show that this inversion can be formulated as a simple neural network and may provide a useful metaphor for inference and learning in the brain.

  4. Schizophrenia: an integrated sociodevelopmental-cognitive model

    OpenAIRE

    Howes, Oliver D; Murray, Robin M

    2013-01-01

    Schizophrenia remains a major burden1. The dopamine (DA) and neurodevelopmental hypotheses attempt to explain the pathogenic mechanisms and origins of the disorder respectively2-4. Recently an alternative, the cognitive model, has gained popularity5. However the first two theories have not been satisfactorily integrated, and the most influential iteration of the cognitive model makes no mention of DA, neurodevelopment, or indeed the brain5. Here we show that developmental alterations secondar...

  5. Integrated Environmental Assessment Modelling

    Energy Technology Data Exchange (ETDEWEB)

    Guardanz, R.; Gimeno, B. S.; Bermejo, V.; Elvira, S.; Martin, F.; Palacios, M.; Rodriguez, E.; Donaire, I. [Ciemat, Madrid (Spain)

    2000-07-01

    This report describes the results of the Spanish participation in the project Coupling CORINAIR data to cost-effect emission reduction strategies based on critical threshold. (EU/LIFE97/ENV/FIN/336). The subproject has focused on three tasks. Develop tools to improve knowledge on the spatial and temporal details of emissions of air pollutants in Spain. Exploit existing experimental information on plant response to air pollutants in temperate ecosystem and Integrate these findings in a modelling framework that can asses with more accuracy the impact of air pollutants to temperate ecosystems. The results obtained during the execution of this project have significantly improved the models of the impact of alternative emission control strategies on ecosystems and crops in the Iberian Peninsula. (Author) 375 refs.

  6. Integrated Medical Model Overview

    Science.gov (United States)

    Myers, J.; Boley, L.; Foy, M.; Goodenow, D.; Griffin, D.; Keenan, A.; Kerstman, E.; Melton, S.; McGuire, K.; Saile, L.; hide

    2015-01-01

    The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project.

  7. Implications of the Vienna Integrated Model of Art Perception for art-based interventions in clinical populations: Comment on "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

    Science.gov (United States)

    Taruffi, Liila; Koelsch, Stefan

    2017-07-01

    Pelowski et al. present a holistic framework within which the multiple processes underlying art viewing can be systematically organized [1]. The proposed model integrates a broad range of dynamic mechanisms, which can effectively account for empirical as well as humanistic perspectives on art perception. Particularly challenging is the final section of the article, where the authors draw a correspondence between behavioral and cognitive components and brain structures (as well as networks). Here, we comment on the implications of the Vienna Integrated Model of Art Perception for art therapy in clinical populations, particularly focusing on (1) expanding Pelowski et al.'s considerations of the Default Mode Network (DMN) into discussion of its relevance to mental diseases, and (2) elaborating on empathic resonance in aesthetic contexts and the capacity of art to build up empathic skills.

  8. New Ideas for Brain Modelling

    Directory of Open Access Journals (Sweden)

    Kieran Greer

    2016-01-01

    Full Text Available This paper describes some biologically-inspired processes that could be used to build the sort of networks that we associate with the human brain. New to this paper, a ‘refined’ neuron will be proposed. This is a group of neurons that by joining together can produce a more analogue system, but with the same level of control and reliability that a binary neuron would have. With this new structure, it will be possible to think of an essentially binary system in terms of a more variable set of values. The paper also shows how recent research can be combined with established theories, to produce a more complete picture.The propositions are largely in line with conventional thinking, but possibly with one or two more radical suggestions. An earlier cognitive model can be filled in with more specific details, based on the new research results, where the components appear to fit together almost seamlessly. The intention of the research has been to describe plausible ‘mechanical’ processes that can produce the appropriate brain structures and mechanisms, but that could be used without the magical ‘intelligence’ part that is still not fully understood.There are also some important updates from an earlier version of this paper.Keywords: neuron, neural network, cognitive model, self-organise, analogue, resonance.

  9. Integrative structure modeling with the Integrative Modeling Platform.

    Science.gov (United States)

    Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

    2017-09-28

    Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use. © 2017 The Protein Society.

  10. Mixed oligomers and monomeric amyloid-β disrupts endothelial cells integrity and reduces monomeric amyloid-β transport across hCMEC/D3 cell line as an in vitro blood-brain barrier model.

    Science.gov (United States)

    Qosa, Hisham; LeVine, Harry; Keller, Jeffrey N; Kaddoumi, Amal

    2014-09-01

    Senile amyloid plaques are one of the diagnostic hallmarks of Alzheimer's disease (AD). However, the severity of clinical symptoms of AD is weakly correlated with the plaque load. AD symptoms severity is reported to be more strongly correlated with the level of soluble amyloid-β (Aβ) assemblies. Formation of soluble Aβ assemblies is stimulated by monomeric Aβ accumulation in the brain, which has been related to its faulty cerebral clearance. Studies tend to focus on the neurotoxicity of specific Aβ species. There are relatively few studies investigating toxic effects of Aβ on the endothelial cells of the blood-brain barrier (BBB). We hypothesized that a soluble Aβ pool more closely resembling the in vivo situation composed of a mixture of Aβ40 monomer and Aβ42 oligomer would exert higher toxicity against hCMEC/D3 cells as an in vitro BBB model than either component alone. We observed that, in addition to a disruptive effect on the endothelial cells integrity due to enhancement of the paracellular permeability of the hCMEC/D3 monolayer, the Aβ mixture significantly decreased monomeric Aβ transport across the cell culture model. Consistent with its effect on Aβ transport, Aβ mixture treatment for 24h resulted in LRP1 down-regulation and RAGE up-regulation in hCMEC/D3 cells. The individual Aβ species separately failed to alter Aβ clearance or the cell-based BBB model integrity. Our study offers, for the first time, evidence that a mixture of soluble Aβ species, at nanomolar concentrations, disrupts endothelial cells integrity and its own transport across an in vitro model of the BBB. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Tick-borne encephalitis virus infects human brain microvascular endothelial cells without compromising blood-brain barrier integrity.

    Science.gov (United States)

    Palus, Martin; Vancova, Marie; Sirmarova, Jana; Elsterova, Jana; Perner, Jan; Ruzek, Daniel

    2017-07-01

    Alteration of the blood-brain barrier (BBB) is a hallmark of tick-borne encephalitis (TBE), a life-threating human viral neuroinfection. However, the mechanism of BBB breakdown during TBE, as well as TBE virus (TBEV) entry into the brain is unclear. Here, primary human microvascular endothelial cells (HBMECs) were infected with TBEV to study interactions with the BBB. Although the number of infected cells was relatively low in culture (10 6 pfu/ml). Infection did not induce any significant changes in the expression of key tight junction proteins or upregulate the expression of cell adhesion molecules, and did not alter the highly organized intercellular junctions between HBMECs. In an in vitro BBB model, the virus crossed the BBB via a transcellular pathway without compromising the integrity of the cell monolayer. The results indicate that HBMECs may support TBEV entry into the brain without altering BBB integrity. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Joint Modelling of Structural and Functional Brain Networks

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten

    Functional and structural magnetic resonance imaging have become the most important noninvasive windows to the human brain. A major challenge in the analysis of brain networks is to establish the similarities and dissimilarities between functional and structural connectivity. We formulate a non......-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...... significant structures that are consistently shared across subjects and data splits. This provides an unsupervised approach for modeling of structure-function relations in the brain and provides a general framework for multimodal integration....

  13. Integrability of the Rabi model.

    Science.gov (United States)

    Braak, D

    2011-09-02

    The Rabi model is a paradigm for interacting quantum systems. It couples a bosonic mode to the smallest possible quantum model, a two-level system. I present the analytical solution which allows us to consider the question of integrability for quantum systems that do not possess a classical limit. A criterion for quantum integrability is proposed which shows that the Rabi model is integrable due to the presence of a discrete symmetry. Moreover, I introduce a generalization with no symmetries; the generalized Rabi model is the first example of a nonintegrable but exactly solvable system.

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

    Science.gov (United States)

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

    2016-01-01

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

  15. Integrated Genomic and Epigenomic Analysis of Breast Cancer Brain Metastasis

    Science.gov (United States)

    Salhia, Bodour; Kiefer, Jeff; Ross, Julianna T. D.; Metapally, Raghu; Martinez, Rae Anne; Johnson, Kyle N.; DiPerna, Danielle M.; Paquette, Kimberly M.; Jung, Sungwon; Nasser, Sara; Wallstrom, Garrick; Tembe, Waibhav; Baker, Angela; Carpten, John; Resau, Jim; Ryken, Timothy; Sibenaller, Zita; Petricoin, Emanuel F.; Liotta, Lance A.; Ramanathan, Ramesh K.; Berens, Michael E.; Tran, Nhan L.

    2014-01-01

    The brain is a common site of metastatic disease in patients with breast cancer, which has few therapeutic options and dismal outcomes. The purpose of our study was to identify common and rare events that underlie breast cancer brain metastasis. We performed deep genomic profiling, which integrated gene copy number, gene expression and DNA methylation datasets on a collection of breast brain metastases. We identified frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q and frequent broad-level deletions involving 8p, 17p, 21p and Xq. Frequently amplified and overexpressed genes included ATAD2, BRAF, DERL1, DNMTRB and NEK2A. The ATM, CRYAB and HSPB2 genes were commonly deleted and underexpressed. Knowledge mining revealed enrichment in cell cycle and G2/M transition pathways, which contained AURKA, AURKB and FOXM1. Using the PAM50 breast cancer intrinsic classifier, Luminal B, Her2+/ER negative, and basal-like tumors were identified as the most commonly represented breast cancer subtypes in our brain metastasis cohort. While overall methylation levels were increased in breast cancer brain metastasis, basal-like brain metastases were associated with significantly lower levels of methylation. Integrating DNA methylation data with gene expression revealed defects in cell migration and adhesion due to hypermethylation and downregulation of PENK, EDN3, and ITGAM. Hypomethylation and upregulation of KRT8 likely affects adhesion and permeability. Genomic and epigenomic profiling of breast brain metastasis has provided insight into the somatic events underlying this disease, which have potential in forming the basis of future therapeutic strategies. PMID:24489661

  16. Integration of the antennal lobe glomeruli and three projection neurons in the standard brain atlas of the moth Heliothis virescens

    Directory of Open Access Journals (Sweden)

    Bjarte B Løfaldli

    2010-02-01

    Full Text Available Digital three dimensional standard brain atlases are valuable tools for integrating neuroimaging data of different preparations. In insects, standard brain atlases of five species are available, including the atlas of the female Heliothis virescens moth brain. Like for the other species, the antennal lobes of the moth brain atlas were integrated as one material identity without internal structures. Different from the others, the H. virescens standard brain atlas exclusively included the glomerular layer of the antennal lobe. This was an advantage in the present study for performing a direct registration of the glomerular layer of individual preparations into the standard brain. We here present the H. virescens female standard brain atlas with a new model of the antennal lobe glomeruli integrated into the atlas, i.e. with each of the 66 glomeruli identified and labelled with a specific number. The new model differs from the previous H. virescens antennal lobe model both in respect to the number of glomeruli and the numbering system; the latter according to the system used for the antennal lobe atlases of two other heliothine species. For identifying female specific glomeruli comparison with the male antennal lobe was necessary. This required a new male antennal lobe atlas, included in this paper. As demonstrated by the integration of three antennal lobe projection neurons of different preparations, the new standard brain atlas with the integrated glomruli is a helpful tool for determining the glomeruli innervated as well as the relative position of the axonal projections in the protocerebrum.

  17. IMMIGRANTS’ INTEGRATION MODELS

    Directory of Open Access Journals (Sweden)

    CARMEN UZLĂU

    2012-05-01

    Full Text Available In the context of the European population aging trend, and while the birth rate is still at a low level, the immigrants may contribute to the support of the EU economy and to finance the national social protection systems. But this would be possible only if they have been fully integrated in the host countries, the integration policies being a task of the national governments. The European Union may still offer support and stimulation through financing, policies coordination and good practices exchange facilitation. The new measures should encourage local level actions, including cooperation between local authorities, employers, migrants’ organizations, service providers and local population. Within the EU, there live 20.1 million immigrants (approximately 4% of the entire population coming from outside European area. An important element of the common EU policy on immigration is the one regarding the development of a policy on immigrants’ integration, which should provide a fair treatment within the member states, and guarantee rights and obligations comparable with the ones of the Union citizens.

  18. Modeling premature brain injury and recovery

    Science.gov (United States)

    Scafidi, Joey; Fagel, Devon M.; Ment, Laura R.; Vaccarino, Flora M.

    2009-01-01

    Premature birth is a growing and significant public health problem because of the large number of infants that survive with neurodevelopmental sequelae from brain injury. Recent advances in neuroimaging have shown that although some neuroanatomical structures are altered, others improve over time. This review outlines recent insights into brain structure and function in these preterm infants at school age and relevant animal models. These animal models have provided scientists with an opportunity to explore in depth the molecular and cellular mechanisms of injury as well as the potential of the brain for recovery. The endogenous potential that the brain has for neurogenesis and gliogenesis, and how environment contributes to recovery, are also outlined. These preclinical models will provide important insights into the genetic and epigenetic mechanisms responsible for variable degrees of injury and recovery, permitting the exploration of targeted therapies to facilitate recovery in the developing preterm brain. PMID:19482072

  19. An adaptive complex network model for brain functional networks.

    Directory of Open Access Journals (Sweden)

    Ignacio J Gomez Portillo

    Full Text Available Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution.

  20. Integrating Retirement Models

    OpenAIRE

    Gustman, Alan L.; Thomas Steinmeier

    2009-01-01

    This paper advances the specification and estimation of models of retirement and saving in two earner families. The complications introduced by the interaction of retirement decisions by husbands and wives have led researchers to adopt a number of simplifications to increase the feasibility of estimating family retirement models. Our model relaxes these restrictions. It includes the extended choice set created when each spouse makes an independent retirement decision. It also includes the ful...

  1. Transdiagnostic Associations Between Functional Brain Network Integrity and Cognition.

    Science.gov (United States)

    Sheffield, Julia M; Kandala, Sridhar; Tamminga, Carol A; Pearlson, Godfrey D; Keshavan, Matcheri S; Sweeney, John A; Clementz, Brett A; Lerman-Sinkoff, Dov B; Hill, S Kristian; Barch, Deanna M

    2017-06-01

    Cognitive impairment occurs across the psychosis spectrum and is associated with functional outcome. However, it is unknown whether these shared manifestations of cognitive dysfunction across diagnostic categories also reflect shared neurobiological mechanisms or whether the source of impairment differs. To examine whether the general cognitive deficit observed across psychotic disorders is similarly associated with functional integrity of 2 brain networks widely implicated in supporting many cognitive domains. A total of 201 healthy control participants and 375 patients with psychotic disorders from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were studied from September 29, 2007, to May 31, 2011. The B-SNIP recruited healthy controls and stable outpatients from 6 sites: Baltimore, Maryland; Boston, Massachusetts; Chicago, Illinois; Dallas, Texas; Detroit, Michigan; and Hartford, Connecticut. All participants underwent cognitive testing and resting-state functional magnetic resonance imaging. Data analysis was performed from April 28, 2015, to February 21, 2017. The Brief Assessment of Cognition in Schizophrenia was used to measure cognitive ability. A principal axis factor analysis on the Brief Assessment of Cognition in Schizophrenia battery yielded a single factor (54% variance explained) that served as the measure of general cognitive ability. Functional network integrity measures included global and local efficiency of the whole brain, cingulo-opercular network (CON), frontoparietal network, and auditory network and exploratory analyses of all networks from the Power atlas. Group differences in network measures, associations between cognition and network measures, and mediation models were tested. The final sample for the current study included 201 healthy controls, 143 patients with schizophrenia, 103 patients with schizoaffective disorder, and 129 patients with psychotic bipolar disorder (mean [SD] age, 35.1 [12.0] years

  2. Integrated Workforce Modeling System

    Science.gov (United States)

    Moynihan, Gary P.

    2000-01-01

    There are several computer-based systems, currently in various phases of development at KSC, which encompass some component, aspect, or function of workforce modeling. These systems may offer redundant capabilities and/or incompatible interfaces. A systems approach to workforce modeling is necessary in order to identify and better address user requirements. This research has consisted of two primary tasks. Task 1 provided an assessment of existing and proposed KSC workforce modeling systems for their functionality and applicability to the workforce planning function. Task 2 resulted in the development of a proof-of-concept design for a systems approach to workforce modeling. The model incorporates critical aspects of workforce planning, including hires, attrition, and employee development.

  3. Move me, astonish me… delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates.

    Science.gov (United States)

    Pelowski, Matthew; Markey, Patrick S; Forster, Michael; Gerger, Gernot; Leder, Helmut

    2017-07-01

    This paper has a rather audacious purpose: to present a comprehensive theory explaining, and further providing hypotheses for the empirical study of, the multiple ways by which people respond to art. Despite common agreement that interaction with art can be based on a compelling, and occasionally profound, psychological experience, the nature of these interactions is still under debate. We propose a model, The Vienna Integrated Model of Art Perception (VIMAP), with the goal of resolving the multifarious processes that can occur when we perceive and interact with visual art. Specifically, we focus on the need to integrate bottom-up, artwork-derived processes, which have formed the bulk of previous theoretical and empirical assessments, with top-down mechanisms which can describe how individuals adapt or change within their processing experience, and thus how individuals may come to particularly moving, disturbing, transformative, as well as mundane, results. This is achieved by combining several recent lines of theoretical research into a new integrated approach built around three processing checks, which we argue can be used to systematically delineate the possible outcomes in art experience. We also connect our model's processing stages to specific hypotheses for emotional, evaluative, and physiological factors, and address main topics in psychological aesthetics including provocative reactions-chills, awe, thrills, sublime-and difference between "aesthetic" and "everyday" emotional response. Finally, we take the needed step of connecting stages to functional regions in the brain, as well as broader core networks that may coincide with the proposed cognitive checks, and which taken together can serve as a basis for future empirical and theoretical art research. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Move me, astonish me… delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates

    Science.gov (United States)

    Pelowski, Matthew; Markey, Patrick S.; Forster, Michael; Gerger, Gernot; Leder, Helmut

    2017-07-01

    This paper has a rather audacious purpose: to present a comprehensive theory explaining, and further providing hypotheses for the empirical study of, the multiple ways by which people respond to art. Despite common agreement that interaction with art can be based on a compelling, and occasionally profound, psychological experience, the nature of these interactions is still under debate. We propose a model, The Vienna Integrated Model of Art Perception (VIMAP), with the goal of resolving the multifarious processes that can occur when we perceive and interact with visual art. Specifically, we focus on the need to integrate bottom-up, artwork-derived processes, which have formed the bulk of previous theoretical and empirical assessments, with top-down mechanisms which can describe how individuals adapt or change within their processing experience, and thus how individuals may come to particularly moving, disturbing, transformative, as well as mundane, results. This is achieved by combining several recent lines of theoretical research into a new integrated approach built around three processing checks, which we argue can be used to systematically delineate the possible outcomes in art experience. We also connect our model's processing stages to specific hypotheses for emotional, evaluative, and physiological factors, and address main topics in psychological aesthetics including provocative reactions-chills, awe, thrills, sublime-and difference between ;aesthetic; and ;everyday; emotional response. Finally, we take the needed step of connecting stages to functional regions in the brain, as well as broader core networks that may coincide with the proposed cognitive checks, and which taken together can serve as a basis for future empirical and theoretical art research.

  5. The integration of functional brain activity from adolescence to adulthood.

    Science.gov (United States)

    Kundu, Prantik; Benson, Brenda E; Rosen, Dana; Frangou, Sophia; Leibenluft, Ellen; Luh, Wen-Ming; Bandettini, Peter A; Pine, Daniel S; Ernst, Monique

    2018-02-27

    Age-related changes in human functional neuroanatomy are poorly understood. This is partly due to the limits to interpretation of standard fMRI. These limits relate to age-related variation in noise levels across subjects, and the frequent need for standard adult parcellations in developmental studies. Here we used an emerging MRI approach called multi-echo (ME)-fMRI to characterize functional brain changes with age. ME-fMRI acquires blood oxygenation level dependent (BOLD) signals while also quantifying T2* signal decay. This newly enables reliable analysis of BOLD components at the subject level. We hypothesized that BOLD components of the resting state are not stable with age, and would decrease in number from adolescence to adulthood. This runs counter to the current assumptions in neurodevelopmental analyses of brain connectivity that the number of components is a random effect. From resting state ME-fMRI of 51 healthy subjects of both sexes, between ages of 8.3 and 46.2 y, we found a highly significant (R=-0.55, p[dlt]0.001) exponential decrease in the number of BOLD components with age. The number of BOLD components were halved from adolescence to the fifth decade of life, stabilizing in middle adulthood. The regions driving this change were dorsolateral prefrontal cortices, parietal cortex, and cerebellum. The functional network of these regions centered on the cerebellum. We conclude that age-related decrease in BOLD component number concurs with the hypothesis of neurodevelopmental integration of functional brain activity. We show evidence that the cerebellum may play a key role in this process. SIGNIFICANCE STATEMENT Human brain development is ongoing to at least age 30. Functional MRI (fMRI) is key for studying the change in brain function with development. However, developmental fMRI studies have relied on reference maps of brain organization derived from adult data. This may limit sensitivity to major differences in younger brains. We created an f

  6. Computational Intelligence in a Human Brain Model

    Directory of Open Access Journals (Sweden)

    Viorel Gaftea

    2016-06-01

    Full Text Available This paper focuses on the current trends in brain research domain and the current stage of development of research for software and hardware solutions, communication capabilities between: human beings and machines, new technologies, nano-science and Internet of Things (IoT devices. The proposed model for Human Brain assumes main similitude between human intelligence and the chess game thinking process. Tactical & strategic reasoning and the need to follow the rules of the chess game, all are very similar with the activities of the human brain. The main objective for a living being and the chess game player are the same: securing a position, surviving and eliminating the adversaries. The brain resolves these goals, and more, the being movement, actions and speech are sustained by the vital five senses and equilibrium. The chess game strategy helps us understand the human brain better and easier replicate in the proposed ‘Software and Hardware’ SAH Model.

  7. The Center for Integrated Molecular Brain Imaging (Cimbi) database

    DEFF Research Database (Denmark)

    Knudsen, Gitte M.; Jensen, Peter S.; Erritzoe, David

    2016-01-01

    We here describe a multimodality neuroimaging containing data from healthy volunteers and patients, acquired within the Lundbeck Foundation Center for Integrated Molecular Brain Imaging (Cimbi) in Copenhagen, Denmark. The data is of particular relevance for neurobiological research questions rela...... currently contains blood and in some instances saliva samples from about 500 healthy volunteers and 300 patients with e.g., major depression, dementia, substance abuse, obesity, and impulsive aggression. Data continue to be added to the Cimbi database and biobank....

  8. Integrated Debugging of Modelica Models

    Directory of Open Access Journals (Sweden)

    Adrian Pop

    2014-04-01

    Full Text Available The high abstraction level of equation-based object-oriented (EOO languages such as Modelica has the drawback that programming and modeling errors are often hard to find. In this paper we present integrated static and dynamic debugging methods for Modelica models and a debugger prototype that addresses several of those problems. The goal is an integrated debugging framework that combines classical debugging techniques with special techniques for equation-based languages partly based on graph visualization and interaction. To our knowledge, this is the first Modelica debugger that supports both equation-based transformational and algorithmic code debugging in an integrated fashion.

  9. Integrated Inflammatory Stress (ITIS) Model

    DEFF Research Database (Denmark)

    Bangsgaard, Elisabeth O.; Hjorth, Poul G.; Olufsen, Mette S.

    2017-01-01

    maintains a long-term level of the stress hormone cortisol which is also anti-inflammatory. A new integrated model of the interaction between these two subsystems of the inflammatory system is proposed and coined the integrated inflammatory stress (ITIS) model. The coupling mechanisms describing....... A constant activation results in elevated levels of the variables in the model while a prolonged change of the oscillations in ACTH and cortisol concentrations is the most pronounced result of different LPS doses predicted by the model....

  10. Brain tumor symptoms as antecedents to uncertainty: an integrative review.

    Science.gov (United States)

    Cahill, Jennifer; LoBiondo-Wood, Geri; Bergstrom, Nancy; Armstrong, Terri

    2012-06-01

    Uncertainty is a common experience within human cancer. For brain tumor patients, irregular symptom pattern and presentation may promote uncertainties about treatment response, prognosis, and life quality. We sought to identify the somatic symptom experience associated with primary and secondary brain tumors and the potential impact on illness-related uncertainty. An integrative literature search of Medline and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) was performed. Symptom data were excerpted into tables and reviewed critically against the broader uncertainty-focused oncology literature. Twenty-one studies investigated a diverse range of brain tumor symptoms that persist through the now-expanding, post-treatment survival. While symptoms such as fatigue were common, antecedents and patterns were poorly characterized and inconsistent between and within categories of tumor. Symptom investigation is an emerging and rapidly developing area of neuro-oncology. The extent to which symptoms are familiar, predictable, and understandable can mitigate uncertainty. The unstable nature of symptoms across the trajectory of a brain tumor may be a significant corollary to illness-related uncertainty. Because the majority of brain tumor patients cannot be cured of their cancer, understanding the symptom expanse and potential to promote uncertainty could inform alternative nursing strategies to reduce anxiety and distress, and to preserve life quality where cure is often unattainable. © 2012 Sigma Theta Tau International.

  11. Bayesian Modelling of Functional Whole Brain Connectivity

    DEFF Research Database (Denmark)

    Røge, Rasmus

    the prevalent strategy of standardizing of fMRI time series and model data using directional statistics or we model the variability in the signal across the brain and across multiple subjects. In either case, we use Bayesian nonparametric modeling to automatically learn from the fMRI data the number......This thesis deals with parcellation of whole-brain functional magnetic resonance imaging (fMRI) using Bayesian inference with mixture models tailored to the fMRI data. In the three included papers and manuscripts, we analyze two different approaches to modeling fMRI signal; either we accept...... of funcional units, i.e. parcels. We benchmark the proposed mixture models against state of the art methods of brain parcellation, both probabilistic and non-probabilistic. The time series of each voxel are most often standardized using z-scoring which projects the time series data onto a hypersphere...

  12. Integrated materials–structural models

    DEFF Research Database (Denmark)

    Stang, Henrik; Geiker, Mette Rica

    2008-01-01

    Reliable service life models for load carrying structures are significant elements in the evaluation of the performance and sustainability of existing and new structures. Furthermore, reliable service life models are prerequisites for the evaluation of the sustainability of maintenance strategies...... of structural modelling and materials concepts will both operational in both identifying important research issues and in answering the ‘real’ needs of society. Integrated materials-structural models will allow synergy to develop between materials and structural research. On one side the structural modelling...... should define a framework in which materials research results eventually should fit in and on the other side the materials research should define needs and capabilities in structural modelling. Integrated materials-structural models of a general nature are almost non-existent in the field of cement based...

  13. Models for medical practice integration.

    Science.gov (United States)

    Harris, R M

    1994-08-01

    Decreased physician income, increased administrative burdens, and interference with the compassionate delivery of high-quality medical care are threatening the independent practice of medicine in solo and small group practices. Many established physicians, and the hospitals with which they relate, are searching for organizational models that, by integrating some or all aspects of their practices, will preserve incomes and reduce regulatory and administrative burdens. This article will describe several "practice integration models," pointing out advantages and disadvantages to physicians in established practices. (Many of the same arguments could be made for physicians new to practice, with different emphasis). The continuum of integration models is shown in figure 1, page 19. The group practice without walls and its two submodels, the independent group practice without walls (IGWW) and the affiliated medical practice corporation (AMPC) are more recent and more effective models and will be covered in depth in the article.

  14. Human emotion in the brain and the body: Why language matters. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

    Science.gov (United States)

    Herbert, Cornelia

    2015-06-01

    What is an Emotion? This question has fascinated scientific research since William James. Despite the fact that a consensus has been reached about the biological origin of emotions, uniquely human aspects of emotions are still poorly understood. One of these blind spots concerns the relationship between emotion and human language. Historically, many theories imply a duality between emotions on the one hand and cognitive functions such as language on the other hand. Especially for symbolic forms of written language and word processing, it has been assumed that semantic information would bear no relation to bodily, affective, or sensorimotor processing (for an overview see Ref. [1]). The Quartet Theory proposed by Koelsch and colleagues [2] could provide a solution to this problem. It offers a novel, integrative neurofunctional model of human emotions which considers language and emotion as closely related. Crucially, language - be it spoken or written - is assumed to "regulate, modulate, and partly initiate" activity in core affective brain systems in accord with physical needs and individual concerns [cf. page 34, line 995]. In this regard, the Quartet Theory combines assumptions from earlier bioinformational theories of emotions [3], contemporary theories of embodied cognition [4], and appraisal theories such as the Component Process Model [5] into one framework, thereby providing a holistic model for the neuroscientific investigation of human emotion processing at the interface of emotion and cognition, mind and body.

  15. Melanoma Brain Metastasis: Mechanisms, Models, and Medicine

    Science.gov (United States)

    Kircher, David A.; Silvis, Mark R.; Cho, Joseph H.; Holmen, Sheri L.

    2016-01-01

    The development of brain metastases in patients with advanced stage melanoma is common, but the molecular mechanisms responsible for their development are poorly understood. Melanoma brain metastases cause significant morbidity and mortality and confer a poor prognosis; traditional therapies including whole brain radiation, stereotactic radiotherapy, or chemotherapy yield only modest increases in overall survival (OS) for these patients. While recently approved therapies have significantly improved OS in melanoma patients, only a small number of studies have investigated their efficacy in patients with brain metastases. Preliminary data suggest that some responses have been observed in intracranial lesions, which has sparked new clinical trials designed to evaluate the efficacy in melanoma patients with brain metastases. Simultaneously, recent advances in our understanding of the mechanisms of melanoma cell dissemination to the brain have revealed novel and potentially therapeutic targets. In this review, we provide an overview of newly discovered mechanisms of melanoma spread to the brain, discuss preclinical models that are being used to further our understanding of this deadly disease and provide an update of the current clinical trials for melanoma patients with brain metastases. PMID:27598148

  16. Enabling model customization and integration

    Science.gov (United States)

    Park, Minho; Fishwick, Paul A.

    2003-09-01

    Until fairly recently, the idea of dynamic model content and presentation were treated synonymously. For example, if one was to take a data flow network, which captures the dynamics of a target system in terms of the flow of data through nodal operators, then one would often standardize on rectangles and arrows for the model display. The increasing web emphasis on XML, however, suggests that the network model can have its content specified in an XML language, and then the model can be represented in a number of ways depending on the chosen style. We have developed a formal method, based on styles, that permits a model to be specified in XML and presented in 1D (text), 2D, and 3D. This method allows for customization and personalization to exert their benefits beyond e-commerce, to the area of model structures used in computer simulation. This customization leads naturally to solving the bigger problem of model integration - the act of taking models of a scene and integrating them with that scene so that there is only one unified modeling interface. This work focuses mostly on customization, but we address the integration issue in the future work section.

  17. D-galactose-induced brain ageing model

    DEFF Research Database (Denmark)

    Sadigh-Eteghad, Saeed; Majdi, Alireza; McCann, Sarah K.

    2017-01-01

    Animal models are commonly used in brain ageing research. Amongst these, models where rodents are exposed to d-galactose are held to recapitulate a number of features of ageing including neurobehavioral and neurochemical changes. However, results from animal studies are often inconsistent...

  18. Modeling high dimensional multichannel brain signals

    KAUST Repository

    Hu, Lechuan

    2017-03-27

    In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

  19. Integrated modeling: a look back

    Science.gov (United States)

    Briggs, Clark

    2015-09-01

    This paper discusses applications and implementation approaches used for integrated modeling of structural systems with optics over the past 30 years. While much of the development work focused on control system design, significant contributions were made in system modeling and computer-aided design (CAD) environments. Early work appended handmade line-of-sight models to traditional finite element models, such as the optical spacecraft concept from the ACOSS program. The IDEAS2 computational environment built in support of Space Station collected a wider variety of existing tools around a parametric database. Later, IMOS supported interferometer and large telescope mission studies at JPL with MATLAB modeling of structural dynamics, thermal analysis, and geometric optics. IMOS's predecessor was a simple FORTRAN command line interpreter for LQG controller design with additional functions that built state-space finite element models. Specialized language systems such as CAESY were formulated and prototyped to provide more complex object-oriented functions suited to control-structure interaction. A more recent example of optical modeling directly in mechanical CAD is used to illustrate possible future directions. While the value of directly posing the optical metric in system dynamics terms is well understood today, the potential payoff is illustrated briefly via project-based examples. It is quite likely that integrated structure thermal optical performance (STOP) modeling could be accomplished in a commercial off-the-shelf (COTS) tool set. The work flow could be adopted, for example, by a team developing a small high-performance optical or radio frequency (RF) instrument.

  20. Integrated Inflammatory Stress (ITIS) Model.

    Science.gov (United States)

    Bangsgaard, Elisabeth O; Hjorth, Poul G; Olufsen, Mette S; Mehlsen, Jesper; Ottesen, Johnny T

    2017-07-01

    During the last decade, there has been an increasing interest in the coupling between the acute inflammatory response and the Hypothalamic-Pituitary-Adrenal (HPA) axis. The inflammatory response is activated acutely by pathogen- or damage-related molecular patterns, whereas the HPA axis maintains a long-term level of the stress hormone cortisol which is also anti-inflammatory. A new integrated model of the interaction between these two subsystems of the inflammatory system is proposed and coined the integrated inflammatory stress (ITIS) model. The coupling mechanisms describing the interactions between the subsystems in the ITIS model are formulated based on biological reasoning and its ability to describe clinical data. The ITIS model is calibrated and validated by simulating various scenarios related to endotoxin (LPS) exposure. The model is capable of reproducing human data of tumor necrosis factor alpha, adrenocorticotropic hormone (ACTH) and cortisol and suggests that repeated LPS injections lead to a deficient response. The ITIS model predicts that the most extensive response to an LPS injection in ACTH and cortisol concentrations is observed in the early hours of the day. A constant activation results in elevated levels of the variables in the model while a prolonged change of the oscillations in ACTH and cortisol concentrations is the most pronounced result of different LPS doses predicted by the model.

  1. Schizophrenia: an integrated sociodevelopmental-cognitive model.

    Science.gov (United States)

    Howes, Oliver D; Murray, Robin M

    2014-05-10

    Schizophrenia remains a major burden on patients and society. The dopamine hypothesis attempts to explain the pathogenic mechanisms of the disorder, and the neurodevelopmental hypothesis the origins. In the past 10 years an alternative, the cognitive model, has gained popularity. However, the first two theories have not been satisfactorily integrated, and the most influential iteration of the cognitive model makes no mention of dopamine, neurodevelopment, or indeed the brain. In this Review we show that developmental alterations secondary to variant genes, early hazards to the brain, and childhood adversity sensitise the dopamine system, and result in excessive presynaptic dopamine synthesis and release. Social adversity biases the cognitive schema that the individual uses to interpret experiences towards paranoid interpretations. Subsequent stress results in dysregulated dopamine release, causing the misattribution of salience to stimuli, which are then misinterpreted by the biased cognitive processes. The resulting paranoia and hallucinations in turn cause further stress, and eventually repeated dopamine dysregulation hardwires the psychotic beliefs. Finally, we consider the implications of this model for understanding and treatment of schizophrenia. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Nano-Modeling and Computation in Bio and Brain Dynamics

    Directory of Open Access Journals (Sweden)

    Paolo Di Sia

    2016-04-01

    Full Text Available The study of brain dynamics currently utilizes the new features of nanobiotechnology and bioengineering. New geometric and analytical approaches appear very promising in all scientific areas, particularly in the study of brain processes. Efforts to engage in deep comprehension lead to a change in the inner brain parameters, in order to mimic the external transformation by the proper use of sensors and effectors. This paper highlights some crossing research areas of natural computing, nanotechnology, and brain modeling and considers two interesting theoretical approaches related to brain dynamics: (a the memory in neural network, not as a passive element for storing information, but integrated in the neural parameters as synaptic conductances; and (b a new transport model based on analytical expressions of the most important transport parameters, which works from sub-pico-level to macro-level, able both to understand existing data and to give new predictions. Complex biological systems are highly dependent on the context, which suggests a “more nature-oriented” computational philosophy.

  3. An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

    Science.gov (United States)

    Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

    2017-11-22

    Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

  4. Verbal Neuropsychological Functions in Aphasia: An Integrative Model

    Science.gov (United States)

    Vigliecca, Nora Silvana; Báez, Sandra

    2015-01-01

    A theoretical framework which considers the verbal functions of the brain under a multivariate and comprehensive cognitive model was statistically analyzed. A confirmatory factor analysis was performed to verify whether some recognized aphasia constructs can be hierarchically integrated as latent factors from a homogenously verbal test. The Brief…

  5. Haplotypes of catechol-O-methyltransferase modulate intelligence-related brain white matter integrity.

    Science.gov (United States)

    Liu, Bing; Li, Jun; Yu, Chunshui; Li, Yonghui; Liu, Yong; Song, Ming; Fan, Ming; Li, Kuncheng; Jiang, Tianzi

    2010-03-01

    Twin studies have indicated a common genetic origin for intelligence and for variations in brain morphology. Our previous diffusion tensor imaging studies found an association between intelligence and white matter integrity of specific brain regions or tracts. However, specific genetic determinants of the white matter integrity of these brain regions and tracts are still unclear. In this study, we assess whether and how catechol-O-methyltransferase (COMT) gene polymorphisms affect brain white matter integrity. We genotyped twelve single nucleotide polymorphisms (SNPs) within the COMT gene and performed haplotype analyses on data from 79 healthy subjects. Our subjects had the same three major COMT haplotypes (termed the HPS, APS and LPS haplotypes) as previous studies have reported as regulating significantly different levels of enzymatic activity and dopamine. We used the mean fractional anisotropy (FA) values from four regions and five tracts of interest to assess the effect of COMT polymorphisms, including the well-studied val158met SNP and the three main haplotypes that we had identified, on intelligence-related white matter integrity. We identified an association between the mean FA values of two regions in the bilateral prefrontal lobes and the COMT haplotypes, rather than between them and val158met. The haplotype-FA value associations modulated nonlinearly and fit an inverted U-model. Our findings suggest that COMT haplotypes can nonlinearly modulate the intelligence-related white matter integrity of the prefrontal lobes by more significantly influencing prefrontal dopamine variations than does val158met. Copyright (c) 2009 Elsevier Inc. All rights reserved.

  6. Mobile impurities in integrable models

    Directory of Open Access Journals (Sweden)

    Andrew S. Campbell, Dimitri M. Gangardt

    2017-08-01

    Full Text Available We use a mobile impurity or depleton model to study elementary excitations in one-dimensional integrable systems. For Lieb-Liniger and bosonic Yang-Gaudin models we express two phenomenological parameters characterising renormalised inter- actions of mobile impurities with superfluid background: the number of depleted particles, $N$ and the superfluid phase drop $\\pi J$ in terms of the corresponding Bethe Ansatz solution and demonstrate, in the leading order, the absence of two-phonon scattering resulting in vanishing rates of inelastic processes such as viscosity experienced by the mobile impurities

  7. The integrated environmental control model

    Energy Technology Data Exchange (ETDEWEB)

    Rubin, E.S.; Berkenpas, M.B.; Kalagnanam, J.R. [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    1995-11-01

    The capability to estimate the performance and cost of emission control systems is critical to a variety of planning and analysis requirements faced by utilities, regulators, researchers and analysts in the public and private sectors. The computer model described in this paper has been developed for DOe to provide an up-to-date capability for analyzing a variety of pre-combustion, combustion, and post-combustion options in an integrated framework. A unique capability allows performance and costs to be modeled probabilistically, which allows explicit characterization of uncertainties and risks.

  8. Modeling High-Dimensional Multichannel Brain Signals

    KAUST Repository

    Hu, Lechuan

    2017-12-12

    Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from analyzing these data mainly come from two aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with potentially high lag order so that complex lead-lag temporal dynamics between the channels can be captured. Estimates of the VAR model will be obtained by our proposed hybrid LASSLE (LASSO + LSE) method which combines regularization (to control for sparsity) and least squares estimation (to improve bias and mean-squared error). Then we employ some measures of connectivity but put an emphasis on partial directed coherence (PDC) which can capture the directional connectivity between channels. PDC is a frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative to all possible receivers in the network. The proposed modeling approach provided key insights into potential functional relationships among simultaneously recorded sites during performance of a complex memory task. Specifically, this novel method was successful in quantifying patterns of effective connectivity across electrode locations, and in capturing how these patterns varied across trial epochs and trial types.

  9. Brain-inspired Stochastic Models and Implementations

    KAUST Repository

    Al-Shedivat, Maruan

    2015-05-12

    One of the approaches to building artificial intelligence (AI) is to decipher the princi- ples of the brain function and to employ similar mechanisms for solving cognitive tasks, such as visual perception or natural language understanding, using machines. The recent breakthrough, named deep learning, demonstrated that large multi-layer networks of arti- ficial neural-like computing units attain remarkable performance on some of these tasks. Nevertheless, such artificial networks remain to be very loosely inspired by the brain, which rich structures and mechanisms may further suggest new algorithms or even new paradigms of computation. In this thesis, we explore brain-inspired probabilistic mechanisms, such as neural and synaptic stochasticity, in the context of generative models. The two questions we ask here are: (i) what kind of models can describe a neural learning system built of stochastic components? and (ii) how can we implement such systems e ̆ciently? To give specific answers, we consider two well known models and the corresponding neural architectures: the Naive Bayes model implemented with a winner-take-all spiking neural network and the Boltzmann machine implemented in a spiking or non-spiking fashion. We propose and analyze an e ̆cient neuromorphic implementation of the stochastic neu- ral firing mechanism and study the e ̄ects of synaptic unreliability on learning generative energy-based models implemented with neural networks.

  10. Integrity modelling of tropospheric delay models

    Science.gov (United States)

    Rózsa, Szabolcs; Bastiaan Ober, Pieter; Mile, Máté; Ambrus, Bence; Juni, Ildikó

    2017-04-01

    The effect of the neutral atmosphere on signal propagation is routinely estimated by various tropospheric delay models in satellite navigation. Although numerous studies can be found in the literature investigating the accuracy of these models, for safety-of-life applications it is crucial to study and model the worst case performance of these models using very low recurrence frequencies. The main objective of the INTegrity of TROpospheric models (INTRO) project funded by the ESA PECS programme is to establish a model (or models) of the residual error of existing tropospheric delay models for safety-of-life applications. Such models are required to overbound rare tropospheric delays and should thus include the tails of the error distributions. Their use should lead to safe error bounds on the user position and should allow computation of protection levels for the horizontal and vertical position errors. The current tropospheric model from the RTCA SBAS Minimal Operational Standards has an associated residual error that equals 0.12 meters in the vertical direction. This value is derived by simply extrapolating the observed distribution of the residuals into the tail (where no data is present) and then taking the point where the cumulative distribution has an exceedance level would be 10-7.While the resulting standard deviation is much higher than the estimated standard variance that best fits the data (0.05 meters), it surely is conservative for most applications. In the context of the INTRO project some widely used and newly developed tropospheric delay models (e.g. RTCA MOPS, ESA GALTROPO and GPT2W) were tested using 16 years of daily ERA-INTERIM Reanalysis numerical weather model data and the raytracing technique. The results showed that the performance of some of the widely applied models have a clear seasonal dependency and it is also affected by a geographical position. In order to provide a more realistic, but still conservative estimation of the residual

  11. Integrated Resource Planning Model (IRPM)

    Energy Technology Data Exchange (ETDEWEB)

    Graham, T. B.

    2010-04-01

    The Integrated Resource Planning Model (IRPM) is a decision-support software product for resource-and-capacity planning. Users can evaluate changing constraints on schedule performance, projected cost, and resource use. IRPM is a unique software tool that can analyze complex business situations from a basic supply chain to an integrated production facility to a distributed manufacturing complex. IRPM can be efficiently configured through a user-friendly graphical interface to rapidly provide charts, graphs, tables, and/or written results to summarize postulated business scenarios. There is not a similar integrated resource planning software package presently available. Many different businesses (from government to large corporations as well as medium-to-small manufacturing concerns) could save thousands of dollars and hundreds of labor hours in resource and schedule planning costs. Those businesses also could avoid millions of dollars of revenue lost from fear of overcommitting or from penalties and lost future business for failing to meet promised delivery by using IRPM to perform what-if business-case evaluations. Tough production planning questions that previously were left unanswered can now be answered with a high degree of certainty. Businesses can anticipate production problems and have solutions in hand to deal with those problems. IRPM allows companies to make better plans, decisions, and investments.

  12. Mouse Genetic Models of Human Brain Disorders

    Directory of Open Access Journals (Sweden)

    Celeste eLeung

    2016-03-01

    Full Text Available Over the past three decades, genetic manipulations in mice have been used in neuroscience as a major approach to investigate the in vivo function of genes and their alterations. In particular, gene targeting techniques using embryonic stem cells have revolutionized the field of mammalian genetics and have been at the forefront in the generation of numerous mouse models of human brain disorders. In this review, we will first examine childhood developmental disorders such as autism, intellectual disability, Fragile X syndrome, and Williams-Beuren syndrome. We will then explore psychiatric disorders such as schizophrenia and lastly, neurodegenerative disorders including Alzheimer’s disease and Parkinson’s disease. We will outline the creation of these mouse models that range from single gene deletions, subtle point mutations to multi-gene manipulations, and discuss the key behavioural phenotypes of these mice. Ultimately, the analysis of the models outlined in this review will enhance our understanding of the in vivo role and underlying mechanisms of disease-related genes in both normal brain function and brain disorders, and provide potential therapeutic targets and strategies to prevent and treat these diseases.

  13. The Community Integration Questionnaire: factor structure across racial/ethnic groups in persons with traumatic brain injury.

    Science.gov (United States)

    Lequerica, Anthony H; Chiaravalloti, Nancy D; Sander, Angelle M; Pappadis, Monique R; Arango-Lasprilla, Juan Carlos; Hart, Tessa; Baños, James H; Marquez De La Plata, Carlos D; Hammond, Flora M; Sherman, Tanya E

    2013-01-01

    To examine the factor structure and construct validity of the Community Integration Questionnaire, a widely used measure of community participation among individuals with traumatic brain injury (TBI), among 3 racial/ethnic groups. Prospective longitudinal cohort study. Enrollment in acute inpatient TBI rehabilitation with follow-up at 1 year after injury. A total of 1756 persons with TBI enrolled in the Traumatic Brain Injury Model Systems (TBIMS) national Database. Community Integration Questionnaire at 1 year after injury. The goodness of fit for the factor structure of the Community Integration Questionnaire, separating items into Home Competency, Social Integration, and Productive Activity, was satisfactory for whites but not for blacks or Hispanics. Clinicians and researchers should take race/ethnicity into account when utilizing measures of community integration.

  14. The BRAIN Initiative Provides a Unifying Context for Integrating Core STEM Competencies into a Neurobiology Course

    OpenAIRE

    Schaefer, Jennifer E.

    2016-01-01

    The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative introduced by the Obama Administration in 2013 presents a context for integrating many STEM competencies into undergraduate neuroscience coursework. The BRAIN Initiative core principles overlap with core STEM competencies identified by the AAAS Vision and Change report and other entities. This neurobiology course utilizes the BRAIN Initiative to serve as the unifying theme that facilitates a primary emphasis ...

  15. Impaired Visual Integration in Children with Traumatic Brain Injury: An Observational Study.

    Directory of Open Access Journals (Sweden)

    Marsh Königs

    Full Text Available Axonal injury after traumatic brain injury (TBI may cause impaired sensory integration. We aim to determine the effects of childhood TBI on visual integration in relation to general neurocognitive functioning.We compared children aged 6-13 diagnosed with TBI (n = 103; M = 1.7 years post-injury to children with traumatic control (TC injury (n = 44. Three TBI severity groups were distinguished: mild TBI without risk factors for complicated TBI (mildRF- TBI, n = 22, mild TBI with ≥1 risk factor (mildRF+ TBI, n = 46 or moderate/severe TBI (n = 35. An experimental paradigm measured speed and accuracy of goal-directed behavior depending on: (1 visual identification; (2 visual localization; or (3 both, measuring visual integration. Group-differences on reaction time (RT or accuracy were tracked down to task strategy, visual processing efficiency and extra-decisional processes (e.g. response execution using diffusion model analysis. General neurocognitive functioning was measured by a Wechsler Intelligence Scale short form.The TBI group had poorer accuracy of visual identification and visual integration than the TC group (Ps ≤ .03; ds ≤ -0.40. Analyses differentiating TBI severity revealed that visual identification accuracy was impaired in the moderate/severe TBI group (P = .05, d = -0.50 and that visual integration accuracy was impaired in the mildRF+ TBI group and moderate/severe TBI group (Ps < .02, ds ≤ -0.56. Diffusion model analyses tracked impaired visual integration accuracy down to lower visual integration efficiency in the mildRF+ TBI group and moderate/severe TBI group (Ps < .001, ds ≤ -0.73. Importantly, intelligence impairments observed in the TBI group (P = .009, d = -0.48 were statistically explained by visual integration efficiency (P = .002.Children with mildRF+ TBI or moderate/severe TBI have impaired visual integration efficiency, which may contribute to poorer general neurocognitive functioning.

  16. Brain-on-a-chip integrated neuronal networks

    NARCIS (Netherlands)

    Xie, Sijia

    2016-01-01

    The brain-on-a-chip technology aims to provide an efficient and economic in vitro platform for brain disease study. In the well-known literature on brain-on-a-chip systems, nonstructured surfaces were conventionally used for the cell attachment in a culture chamber, therefore the neuronal networks

  17. Integrable models of quantum optics

    Directory of Open Access Journals (Sweden)

    Yudson Vladimir

    2017-01-01

    Full Text Available We give an overview of exactly solvable many-body models of quantum optics. Among them is a system of two-level atoms which interact with photons propagating in a one-dimensional (1D chiral waveguide; exact eigenstates of this system can be explicitly constructed. This approach is used also for a system of closely located atoms in the usual (non-chiral waveguide or in 3D space. Moreover, it is shown that for an arbitrary atomic system with a cascade spontaneous radiative decay, the fluorescence spectrum can be described by an exact analytic expression which accounts for interference of emitted photons. Open questions related with broken integrability are discussed.

  18. Mannitol Improves Brain Tissue Oxygenation in a Model of Diffuse Traumatic Brain Injury.

    Science.gov (United States)

    Schilte, Clotilde; Bouzat, Pierre; Millet, Anne; Boucheix, Perrine; Pernet-Gallay, Karin; Lemasson, Benjamin; Barbier, Emmanuel L; Payen, Jean-François

    2015-10-01

    Based on evidence supporting a potential relation between posttraumatic brain hypoxia and microcirculatory derangements with cell edema, we investigated the effects of the antiedematous agent mannitol on brain tissue oxygenation in a model of diffuse traumatic brain injury. Experimental study. Neurosciences and physiology laboratories. Adult male Wistar rats. Thirty minutes after diffuse traumatic brain injury (impact-acceleration model), rats were IV administered with either a saline solution (traumatic brain injury-saline group) or 20% mannitol (1 g/kg) (traumatic brain injury-mannitol group). Sham-saline and sham-mannitol groups received no insult. Two series of experiments were conducted 2 hours after traumatic brain injury (or equivalent) to investigate 1) the effect of mannitol on brain edema and oxygenation, using a multiparametric magnetic resonance-based approach (n = 10 rats per group) to measure the apparent diffusion coefficient, tissue oxygen saturation, mean transit time, and blood volume fraction in the cortex and caudoputamen; 2) the effect of mannitol on brain tissue PO2 and on venous oxygen saturation of the superior sagittal sinus (n = 5 rats per group); and 3) the cortical ultrastructural changes after treatment (n = 1 per group, taken from the first experiment). Compared with the sham-saline group, the traumatic brain injury-saline group had significantly lower tissue oxygen saturation, brain tissue PO2, and venous oxygen saturation of the superior sagittal sinus values concomitant with diffuse brain edema. These effects were associated with microcirculatory collapse due to astrocyte swelling. Treatment with mannitol after traumatic brain injury reversed all these effects. In the absence of traumatic brain injury, mannitol had no effect on brain oxygenation. Mean transit time and blood volume fraction were comparable between the four groups of rats. The development of posttraumatic brain edema can limit the oxygen utilization by brain tissue

  19. An architecture for integration of multidisciplinary models

    DEFF Research Database (Denmark)

    Belete, Getachew F.; Voinov, Alexey; Holst, Niels

    2014-01-01

    , Enterprise Application Integration, and Integration Design Patterns. We developed an architecture of a multidisciplinary model integration framework that brings these three aspects of integration together. Service-oriented-based platform independent architecture that enables to establish loosely coupled......Integrating multidisciplinary models requires linking models: that may operate at different temporal and spatial scales; developed using different methodologies, tools and techniques; different levels of complexity; calibrated for different ranges of inputs and outputs, etc. On the other hand......, integration of models requires us to address technical, semantic, and dataset aspects of interoperability. So we need a genuine techniques that enable us to integrate various domain specific models for interdisciplinary study. In this research work, we investigated best practices of System Integration...

  20. Automatic integration of confidence in the brain valuation signal.

    Science.gov (United States)

    Lebreton, Maël; Abitbol, Raphaëlle; Daunizeau, Jean; Pessiglione, Mathias

    2015-08-01

    A key process in decision-making is estimating the value of possible outcomes. Growing evidence suggests that different types of values are automatically encoded in the ventromedial prefrontal cortex (VMPFC). Here we extend this idea by suggesting that any overt judgment is accompanied by a second-order valuation (a confidence estimate), which is also automatically incorporated in VMPFC activity. In accordance with the predictions of our normative model of rating tasks, two behavioral experiments showed that confidence levels were quadratically related to first-order judgments (age, value or probability ratings). The analysis of three functional magnetic resonance imaging data sets using similar rating tasks confirmed that the quadratic extension of first-order ratings (our proxy for confidence) was encoded in VMPFC activity, even if no confidence judgment was required of the participants. Such an automatic aggregation of value and confidence in a same brain region might provide insight into many distortions of judgment and choice.

  1. The digital bee brain: integrating and managing neurons in a common 3D reference system

    Directory of Open Access Journals (Sweden)

    Jürgen Rybak

    2010-07-01

    Full Text Available The honeybee standard brain (HSB serves as an interactive tool for relating morphologies of bee brain neurons and provides a reference system for functional and bibliographical properties (http://www.neurobiologie.fu-berlin.de/beebrain/. The ultimate goal is to document not only the morphological network properties of neurons collected from separate brains, but also to establish a graphical user interface for a neuron-related data base. Here, we review the current methods and protocols used to incorporate neuronal reconstructions into the HSB. Our registration protocol consists of two separate steps applied to imaging data from two-channel confocal microscopy scans: (1 The reconstruction of the neuron, facilitated by an automatic extraction of the neuron’s skeleton based on threshold segmentation, and (2 the semi-automatic 3D segmentation of the neuropils and their registration with the HSB. The integration of neurons in the HSB is performed by applying the transformation computed in step (2 to the reconstructed neurons of step (1. The most critical issue of this protocol in terms of user interaction time – the segmentation process – is drastically improved by the use of a model-based segmentation process. Furthermore, the underlying statistical shape models (SSM allow the visualization and analysis of characteristic variations in large sets of bee brain data. The anatomy of neural networks composed of multiple neurons that are registered into the HSB are visualized by depicting the 3D reconstructions together with semantic information with the objective to integrate data from multiple sources (electrophysiology, imaging, immunocytochemistry, molecular biology. Ultimately, this will allow the user to specify cell types and retrieve their morphologies along with physiological characterizations.

  2. Endothelial progenitor cells physiology and metabolic plasticity in brain angiogenesis and blood-brain barrier modeling

    Directory of Open Access Journals (Sweden)

    Natalia Malinovskaya

    2016-12-01

    Full Text Available Currently, there is a considerable interest to the assessment of blood-brain barrier (BBB development as a part of cerebral angiogenesis developmental program. Embryonic and adult angiogenesis in the brain is governed by the coordinated activity of endothelial progenitor cells, brain microvascular endothelial cells, and non-endothelial cells contributing to the establishment of the BBB (pericytes, astrocytes, neurons. Metabolic and functional plasticity of endothelial progenitor cells controls their timely recruitment, precise homing to the brain microvessels, and efficient support of brain angiogenesis. Deciphering endothelial progenitor cells physiology would provide novel engineering approaches to establish adequate microfluidically-supported BBB models and brain microphysiological systems for translational studies.

  3. Sustained NMDA receptor hypofunction induces compromised neural systems integration and schizophrenia-like alterations in functional brain networks.

    Science.gov (United States)

    Dawson, Neil; Xiao, Xiaolin; McDonald, Martin; Higham, Desmond J; Morris, Brian J; Pratt, Judith A

    2014-02-01

    Compromised functional integration between cerebral subsystems and dysfunctional brain network organization may underlie the neurocognitive deficits seen in psychiatric disorders. Applying topological measures from network science to brain imaging data allows the quantification of complex brain network connectivity. While this approach has recently been used to further elucidate the nature of brain dysfunction in schizophrenia, the value of applying this approach in preclinical models of psychiatric disease has not been recognized. For the first time, we apply both established and recently derived algorithms from network science (graph theory) to functional brain imaging data from rats treated subchronically with the N-methyl-D-aspartic acid (NMDA) receptor antagonist phencyclidine (PCP). We show that subchronic PCP treatment induces alterations in the global properties of functional brain networks akin to those reported in schizophrenia. Furthermore, we show that subchronic PCP treatment induces compromised functional integration between distributed neural systems, including between the prefrontal cortex and hippocampus, that have established roles in cognition through, in part, the promotion of thalamic dysconnectivity. We also show that subchronic PCP treatment promotes the functional disintegration of discrete cerebral subsystems and also alters the connectivity of neurotransmitter systems strongly implicated in schizophrenia. Therefore, we propose that sustained NMDA receptor hypofunction contributes to the pathophysiology of dysfunctional brain network organization in schizophrenia.

  4. MicroRNA-210 Suppresses Junction Proteins and Disrupts Blood-Brain Barrier Integrity in Neonatal Rat Hypoxic-Ischemic Brain Injury.

    Science.gov (United States)

    Ma, Qingyi; Dasgupta, Chiranjib; Li, Yong; Huang, Lei; Zhang, Lubo

    2017-06-24

    Cerebral edema, primarily caused by disruption of the blood-brain barrier (BBB), is one of the serious complications associated with brain injury in neonatal hypoxic-ischemic encephalopathy (HIE). Our recent study demonstrated that the hypoxic-ischemic (HI) treatment significantly increased microRNA-210 (miR-210) in the neonatal rat brain and inhibition of miR-210 provided neuroprotection in neonatal HI brain injury. The present study aims to determine the role of miR-210 in the regulation of BBB integrity in the developing brain. miR-210 mimic was administered via intracerebroventricular injection (i.c.v.) into the brain of rat pups. Forty-eight hours after the injection, a modified Rice-Vannucci model was conducted to produce HI brain injury. Post-assays included cerebral edema analysis, western blotting, and immunofluorescence staining for serum immunoglobulin G (IgG) leakage. The results showed that miR-210 mimic exacerbated cerebral edema and IgG leakage into the brain parenchyma. In contrast, inhibition of miR-210 with its complementary locked nucleic acid oligonucleotides (miR-210-LNA) significantly reduced cerebral edema and IgG leakage. These findings suggest that miR-210 negatively regulates BBB integrity i n the neonatal brain. Mechanistically, the seed sequences of miR-210 were identified complementary to the 3' untranslated region (3' UTR) of the mRNA transcripts of tight junction protein occludin and adherens junction protein β-catenin, indicating downstream targets of miR-210. This was further validated by in vivo data showing that miR-210 mimic significantly reduced the expression of these junction proteins in rat pup brains. Of importance, miR-210-LNA preserved the expression of junction proteins occludin and β-catenin from neonatal HI insult. Altogether, the present study reveals a novel mechanism of miR-210 in impairing BBB integrity that contributes to cerebral edema formation after neonatal HI insult, and provides new insights in miR-210-LNA

  5. Highlighting the Structure-Function Relationship of the Brain with the Ising Model and Graph Theory

    Directory of Open Access Journals (Sweden)

    T. K. Das

    2014-01-01

    Full Text Available With the advent of neuroimaging techniques, it becomes feasible to explore the structure-function relationships in the brain. When the brain is not involved in any cognitive task or stimulated by any external output, it preserves important activities which follow well-defined spatial distribution patterns. Understanding the self-organization of the brain from its anatomical structure, it has been recently suggested to model the observed functional pattern from the structure of white matter fiber bundles. Different models which study synchronization (e.g., the Kuramoto model or global dynamics (e.g., the Ising model have shown success in capturing fundamental properties of the brain. In particular, these models can explain the competition between modularity and specialization and the need for integration in the brain. Graphing the functional and structural brain organization supports the model and can also highlight the strategy used to process and organize large amount of information traveling between the different modules. How the flow of information can be prevented or partially destroyed in pathological states, like in severe brain injured patients with disorders of consciousness or by pharmacological induction like in anaesthesia, will also help us to better understand how global or integrated behavior can emerge from local and modular interactions.

  6. Highlighting the Structure-Function Relationship of the Brain with the Ising Model and Graph Theory

    Science.gov (United States)

    Das, T. K.; Abeyasinghe, P. M.; Crone, J. S.; Sosnowski, A.; Laureys, S.; Owen, A. M.; Soddu, A.

    2014-01-01

    With the advent of neuroimaging techniques, it becomes feasible to explore the structure-function relationships in the brain. When the brain is not involved in any cognitive task or stimulated by any external output, it preserves important activities which follow well-defined spatial distribution patterns. Understanding the self-organization of the brain from its anatomical structure, it has been recently suggested to model the observed functional pattern from the structure of white matter fiber bundles. Different models which study synchronization (e.g., the Kuramoto model) or global dynamics (e.g., the Ising model) have shown success in capturing fundamental properties of the brain. In particular, these models can explain the competition between modularity and specialization and the need for integration in the brain. Graphing the functional and structural brain organization supports the model and can also highlight the strategy used to process and organize large amount of information traveling between the different modules. How the flow of information can be prevented or partially destroyed in pathological states, like in severe brain injured patients with disorders of consciousness or by pharmacological induction like in anaesthesia, will also help us to better understand how global or integrated behavior can emerge from local and modular interactions. PMID:25276772

  7. An integrated modelling framework for neural circuits with multiple neuromodulators.

    Science.gov (United States)

    Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

    2017-01-01

    Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

  8. INTEGRATED HYDROGEN STORAGE SYSTEM MODEL

    Energy Technology Data Exchange (ETDEWEB)

    Hardy, B

    2007-11-16

    Hydrogen storage is recognized as a key technical hurdle that must be overcome for the realization of hydrogen powered vehicles. Metal hydrides and their doped variants have shown great promise as a storage material and significant advances have been made with this technology. In any practical storage system the rate of H2 uptake will be governed by all processes that affect the rate of mass transport through the bed and into the particles. These coupled processes include heat and mass transfer as well as chemical kinetics and equilibrium. However, with few exceptions, studies of metal hydrides have focused primarily on fundamental properties associated with hydrogen storage capacity and kinetics. A full understanding of the complex interplay of physical processes that occur during the charging and discharging of a practical storage system requires models that integrate the salient phenomena. For example, in the case of sodium alanate, the size of NaAlH4 crystals is on the order of 300nm and the size of polycrystalline particles may be approximately 10 times larger ({approx}3,000nm). For the bed volume to be as small as possible, it is necessary to densely pack the hydride particles. Even so, in packed beds composed of NaAlH{sub 4} particles alone, it has been observed that the void fraction is still approximately 50-60%. Because of the large void fraction and particle to particle thermal contact resistance, the thermal conductivity of the hydride is very low, on the order of 0.2 W/m-{sup o}C, Gross, Majzoub, Thomas and Sandrock [2002]. The chemical reaction for hydrogen loading is exothermic. Based on the data in Gross [2003], on the order of 10{sup 8}J of heat of is released for the uptake of 5 kg of H{sub 2}2 and complete conversion of NaH to NaAlH{sub 4}. Since the hydride reaction transitions from hydrogen loading to discharge at elevated temperatures, it is essential to control the temperature of the bed. However, the low thermal conductivity of the hydride

  9. Integrated modeling, data transfers, and physical models

    Science.gov (United States)

    Brookshire, D. S.; Chermak, J. M.

    2003-04-01

    Difficulties in developing precise economic policy models for water reallocation and re-regulation in various regional and transboundary settings has been exacerbated not only by climate issues but also by institutional changes reflected in the promulgation of environmental laws, changing regional populations, and an increased focus on water quality standards. As complexity of the water issues have increased, model development at a micro-policy level is necessary to capture difficult institutional nuances and represent the differing national, regional and stakeholders' viewpoints. More often than not, adequate "local" or specific micro-data are not available in all settings for modeling and policy decisions. Economic policy analysis increasingly deals with this problem through data transfers (transferring results from one study area to another) and significant progress has been made in understanding the issue of the dimensionality of data transfers. This paper explores the conceptual and empirical dimensions of data transfers in the context of integrated modeling when the transfers are not only from the behavioral, but also from the hard sciences. We begin by exploring the domain of transfer issues associated with policy analyses that directly consider uncertainty in both the behavioral and physical science settings. We then, through a stylized, hybrid, economic-engineering model of water supply and demand in the Middle Rio Grand Valley of New Mexico (USA) analyze the impacts of; (1) the relative uncertainty of data transfers methods, (2) the uncertainty of climate data and, (3) the uncertainly of population growth. These efforts are motivated by the need to address the relative importance of more accurate data both from the physical sciences as well as from demography and economics for policy analyses. We evaluate the impacts by empirically addressing (within the Middle Rio Grand model): (1) How much does the surrounding uncertainty of the benefit transfer

  10. Increase in seizure susceptibility in sepsis like condition explained by spiking cytokines and altered adhesion molecules level with impaired blood brain barrier integrity in experimental model of rats treated with lipopolysaccharides.

    Science.gov (United States)

    Sewal, Rakesh K; Modi, Manish; Saikia, Uma Nahar; Chakrabarti, Amitava; Medhi, Bikash

    2017-09-01

    Epilepsy is a neurological disorder characterized by recurrent unprovoked seizures. Sepsis is a condition which initiates a cascade of a surge of inflammatory mediators. Interplay between seizures and inflammation other than of brain origin is yet to be explored. The present study was designed to evaluate the seizure susceptibility in experimental models of lipopolysaccharide (LPS) induced sepsis. Experimental sepsis was induced using lipopolysaccharides in Wistar rats. Valproic acid, dexametasone were given to two different groups of animals along with LPS. Two groups of animals were subjected to administration of vehicle and LPS respectively with no other treatment. 24h later, animals were subjected to seizures by using either maximal electro shock or pentylenetetrazole. Seizures related parameters, oxidative stress and TNF-α, IL-6, IL-1β, ICAM-1, ICAM-2, VCAM-1, MMP-9 level in serum and brain samples were evaluated. Histopathological and blood brain barrier permeability studies were conducted. Seizures were decreased in valproic acid treated animals. Reduced oxidative stress was seen in dexamethasone plus valproic acid treated groups as compared to LPS alone treated group. TNF-α, IL-6, IL-1β, ICAM-1, VCAM-1, MMP-9 levels were found increased in LPS treated animals whereas a reverse observation was noted for ICAM-2 level in brain and serum. Histopathological findings confirmed the successful establishment of sepsis like state in animals. Blood brain barrier permeability was found increased in LPS treated groups of animals. Seizure susceptibility may escalate during the sepsis like inflammatory conditions and curbing the inflammatory state might reverse the phenomenon. Copyright © 2017. Published by Elsevier B.V.

  11. Impaired Visual Integration in Children with Traumatic Brain Injury: An Observational Study.

    Science.gov (United States)

    Königs, Marsh; Weeda, Wouter D; van Heurn, L W Ernest; Vermeulen, R Jeroen; Goslings, J Carel; Luitse, Jan S K; Poll-Thé, Bwee Tien; Beelen, Anita; van der Wees, Marleen; Kemps, Rachèl J J K; Catsman-Berrevoets, Coriene E; Oosterlaan, Jaap

    2015-01-01

    Axonal injury after traumatic brain injury (TBI) may cause impaired sensory integration. We aim to determine the effects of childhood TBI on visual integration in relation to general neurocognitive functioning. We compared children aged 6-13 diagnosed with TBI (n = 103; M = 1.7 years post-injury) to children with traumatic control (TC) injury (n = 44). Three TBI severity groups were distinguished: mild TBI without risk factors for complicated TBI (mildRF- TBI, n = 22), mild TBI with ≥1 risk factor (mildRF+ TBI, n = 46) or moderate/severe TBI (n = 35). An experimental paradigm measured speed and accuracy of goal-directed behavior depending on: (1) visual identification; (2) visual localization; or (3) both, measuring visual integration. Group-differences on reaction time (RT) or accuracy were tracked down to task strategy, visual processing efficiency and extra-decisional processes (e.g. response execution) using diffusion model analysis. General neurocognitive functioning was measured by a Wechsler Intelligence Scale short form. The TBI group had poorer accuracy of visual identification and visual integration than the TC group (Ps ≤ .03; ds ≤ -0.40). Analyses differentiating TBI severity revealed that visual identification accuracy was impaired in the moderate/severe TBI group (P = .05, d = -0.50) and that visual integration accuracy was impaired in the mildRF+ TBI group and moderate/severe TBI group (Ps impaired visual integration accuracy down to lower visual integration efficiency in the mildRF+ TBI group and moderate/severe TBI group (Ps impairments observed in the TBI group (P = .009, d = -0.48) were statistically explained by visual integration efficiency (P = .002). Children with mildRF+ TBI or moderate/severe TBI have impaired visual integration efficiency, which may contribute to poorer general neurocognitive functioning.

  12. Brain Dynamics An Introduction to Models and Simualtions

    CERN Document Server

    Haken, Hermann

    2008-01-01

    Brain Dynamics serves to introduce graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences. Some of the advanced chapters will also be of interest to the specialists. The book approaches the subject through pulse-coupled neural networks, with at their core the lighthouse and integrate-and-fire models, which allow for the highly flexible modelling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. Topics also include pulse-averaged equations and their application to movement coordination. The book closes with a short analysis of models versus the real neurophysiological system. The second edition has been thoroughly updated and augmented by two extensive chapters that discuss the interplay between pattern recognition and synchronization. Further, to enhance the usefulness as textbook and for self-study, the detailed solutions for all 34 exercises throughout the text have been added.

  13. How the brain integrates costs and benefits during decision making.

    Science.gov (United States)

    Basten, Ulrike; Biele, Guido; Heekeren, Hauke R; Fiebach, Christian J

    2010-12-14

    When we make decisions, the benefits of an option often need to be weighed against accompanying costs. Little is known, however, about the neural systems underlying such cost-benefit computations. Using functional magnetic resonance imaging and choice modeling, we show that decision making based on cost-benefit comparison can be explained as a stochastic accumulation of cost-benefit difference. Model-driven functional MRI shows that ventromedial and left dorsolateral prefrontal cortex compare costs and benefits by computing the difference between neural signatures of anticipated benefits and costs from the ventral striatum and amygdala, respectively. Moreover, changes in blood oxygen level dependent (BOLD) signal in the bilateral middle intraparietal sulcus reflect the accumulation of the difference signal from ventromedial prefrontal cortex. In sum, we show that a neurophysiological mechanism previously established for perceptual decision making, that is, the difference-based accumulation of evidence, is fundamental also in value-based decisions. The brain, thus, weighs costs against benefits by combining neural benefit and cost signals into a single, difference-based neural representation of net value, which is accumulated over time until the individual decides to accept or reject an option.

  14. Clostridium butyricum exerts a neuroprotective effect in a mouse model of traumatic brain injury via the gut-brain axis.

    Science.gov (United States)

    Li, H; Sun, J; Du, J; Wang, F; Fang, R; Yu, C; Xiong, J; Chen, W; Lu, Z; Liu, J

    2017-11-27

    Traumatic brain injury (TBI) is a common occurrence following gastrointestinal dysfunction. Recently, more and more attentions are being focused on gut microbiota in brain and behavior. Glucagon-like peptide-1 (GLP-1) is considered as a mediator that links the gut-brain axis. The aim of this study was to explore the neuroprotective effects of Clostridium butyricum (Cb) on brain damage in a mouse model of TBI. Male C57BL/6 mice were subjected to a model of TBI-induced by weight-drop impact head injury and were treated intragastrically with Cb. The cognitive deficits, brain water content, neuronal death, and blood-brain barrier (BBB) permeability were evaluated. The expression of tight junction (TJ) proteins, Bcl-2, Bax, GLP-1 receptor (GLP-1R), and phosphorylation of Akt (p-Akt) in the brain were also measured. Moreover, the intestinal barrier permeability, the expression of TJ protein and GLP-1, and IL-6 level in the intestine were detected. Cb treatment significantly improved neurological dysfunction, brain edema, neurodegeneration, and BBB impairment. Meanwhile, Cb treatment also significantly increased the expression of TJ proteins (occludin and zonula occluden-1), p-Akt and Bcl-2, but decreased expression of Bax. Moreover, Cb treatment exhibited more prominent effects on decreasing the levels of plasma d-lactate and colonic IL-6, upregulating expression of Occludin, and protecting intestinal barrier integrity. Furthermore, Cb-treated mice showed increased the secretion of intestinal GLP-1 and upregulated expression of cerebral GLP-1R. Our findings demonstrated the neuroprotective effect of Cb in TBI mice and the involved mechanisms were partially attributed to the elevating GLP-1 secretion through the gut-brain axis. © 2017 John Wiley & Sons Ltd.

  15. Relationship of preinjury caregiver and family functioning to community integration in adults with traumatic brain injury.

    Science.gov (United States)

    Sady, Maegan D; Sander, Angelle M; Clark, Allison N; Sherer, Mark; Nakase-Richardson, Risa; Malec, James F

    2010-10-01

    To investigate the relationship of preinjury caregiver and family functioning to community integration outcomes in persons with traumatic brain injury (TBI). Inception cohort. Three TBI Model Systems inpatient rehabilitation facilities. Persons with TBI (N=141) and their caregivers admitted to inpatient rehabilitation and followed up at 1 to 2 years after injury. Not applicable. Community Integration Questionnaire and the Social and Occupation scales of the Craig Handicap Assessment and Reporting Technique. There were significant interactions of several preinjury caregiver and family variables with injury severity. For persons with complicated mild/moderate injury, better family functioning was associated with greater home integration, and less caregiver distress was associated with better social integration. For persons with severe injuries, greater caregiver perceived social support was associated with better outcomes in productivity and social integration. Preinjury caregiver and family characteristics interact with injury severity to affect outcomes in persons with injury. Research on outcomes should include measures of caregiver and family functioning. Early interventions targeted toward decreasing caregiver distress, increasing support, and improving family functioning may have a positive impact on later outcomes. Copyright © 2010 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  16. Multiscale modeling and simulation of brain blood flow

    Energy Technology Data Exchange (ETDEWEB)

    Perdikaris, Paris, E-mail: parisp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com [IBM T.J Watson Research Center, 1 Rogers St, Cambridge, Massachusetts 02142 (United States); Karniadakis, George Em, E-mail: george-karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912 (United States)

    2016-02-15

    The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

  17. The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

    Science.gov (United States)

    Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

    2018-02-09

    Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

  18. Modeling integrated biomass gasification business concepts

    Science.gov (United States)

    Peter J. Ince; Ted Bilek; Mark A. Dietenberger

    2011-01-01

    Biomass gasification is an approach to producing energy and/or biofuels that could be integrated into existing forest product production facilities, particularly at pulp mills. Existing process heat and power loads tend to favor integration at existing pulp mills. This paper describes a generic modeling system for evaluating integrated biomass gasification business...

  19. Rodent brain extraction using B-spline based deformable model.

    Science.gov (United States)

    Weimin Huang; Chen Ling; Su Huang; Zhongkang Lu; Zhiping Lin

    2017-07-01

    Accurate rodent brain extraction is one of the basic steps for many translational study using Magnetic Resonance Imaging (MRI). In this paper, we present a new approach to model the rodent brain variation using non-rigid B-spline image registration for the brain extraction in MRI images. We model the shape and appearance with the B-spline parameters together with a mean brain image. Followed by a method using multi-expert, we refine the brain extraction region. Compared with the image-based template model using cross-correlation, the performance for rodent brain extraction has shown much improvement on one data set while maintaining the similar yet more consistent performance for another. Both template based methods however outperform the voxel based method (3D PCNN) and a modified BET version for rodent brain extraction.

  20. The BRAIN Initiative Provides a Unifying Context for Integrating Core STEM Competencies into a Neurobiology Course.

    Science.gov (United States)

    Schaefer, Jennifer E

    2016-01-01

    The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative introduced by the Obama Administration in 2013 presents a context for integrating many STEM competencies into undergraduate neuroscience coursework. The BRAIN Initiative core principles overlap with core STEM competencies identified by the AAAS Vision and Change report and other entities. This neurobiology course utilizes the BRAIN Initiative to serve as the unifying theme that facilitates a primary emphasis on student competencies such as scientific process, scientific communication, and societal relevance while teaching foundational neurobiological content such as brain anatomy, cellular neurophysiology, and activity modulation. Student feedback indicates that the BRAIN Initiative is an engaging and instructional context for this course. Course module organization, suitable BRAIN Initiative commentary literature, sample primary literature, and important assignments are presented.

  1. Modeling brain resonance phenomena using a neural mass model.

    Directory of Open Access Journals (Sweden)

    Andreas Spiegler

    2011-12-01

    Full Text Available Stimulation with rhythmic light flicker (photic driving plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect.

  2. An integrated urban systems model with GIS

    OpenAIRE

    Kim, Tschangho John; You, Jinsoo; Lee, Seung-kwan

    1998-01-01

    The purpose of the research is to develop an integrated urban systems model, which will assist in formulating a better land use-transportation policy by simulating the relationships between land use patterns and travel behavior, integrated with geographic information systems (GISs). In order to make an integrated land use-transportation model possible with the assistance of GISs technologies, the following four sub-systems have been developed: (1) an effective traffic analysis zone generation...

  3. Similarity on neural stem cells and brain tumor stem cells in transgenic brain tumor mouse models

    OpenAIRE

    Qiao, Guanqun; Li, Qingquan; Peng, Gang; Ma, Jun; Fan, Hongwei; Li, Yingbin

    2013-01-01

    Although it is believed that glioma is derived from brain tumor stem cells, the source and molecular signal pathways of these cells are still unclear. In this study, we used stable doxycycline-inducible transgenic mouse brain tumor models (c-myc+/SV40Tag+/Tet-on+) to explore the malignant trans-formation potential of neural stem cells by observing the differences of neural stem cells and brain tumor stem cells in the tumor models. Results showed that chromosome instability occurred in brain t...

  4. Regional Economic Integration: The European Model

    Directory of Open Access Journals (Sweden)

    Pierre Jacquet

    2001-12-01

    Full Text Available Regional initiatives have flourished since the end of the Cold War. Given the degree of integration it has achieved, the European Union is often cited as a model of regional integration. This article argues that European integration has been the product of very specific historical conditions, implying that the politics and dynamics of regional integration in Europe may not be appropriate for and replicable in other regions. It also discusses European monetary union (EMU and argues that integration within EMU is still incomplete in particular because economic policies are not sufficiently coordinated. Finally, it discusses the contribution of regional integration to global governance and suggests that the "European model" can be a source of inspiration for the rest of the world not as much as a process to emulate as for the lessons that can be learned from the dynamics and experience of European integration about some important issues in managing economic interdependence.

  5. Experimental deep brain stimulation in animal models.

    Science.gov (United States)

    Tan, Sonny Kh; Vlamings, Rinske; Lim, Leewei; Sesia, Thibault; Janssen, Marcus Lf; Steinbusch, Harry Wm; Visser-Vandewalle, Veerle; Temel, Yasin

    2010-10-01

    DEEP BRAIN STIMULATION (DBS) as a therapy in neurological and psychiatric disorders is widely applied in the field of functional and stereotactic neurosurgery. In this respect, experimental DBS in animal models is performed to evaluate new indications and new technology. In this article, we review our experience with the concept of experimental DBS, including its development and validation. An electrode construction was developed using clinical principles to perform DBS unilaterally or bilaterally in freely moving rats. The stimulation parameters were adjusted for the rat using current density calculations. We performed validation studies in 2 animal models: a rat model of Parkinson's disease (bilateral 6-hydroxydopamine infusion in the striatum) and a rat model of Huntington's disease (transgenic rats). The effects of DBS were evaluated in different behavioral tasks measuring motor and cognitive functions. The electrode construction developed allows experimental DBS to be performed in freely moving rats. With the current setup, electrodes are placed in the target in 70% to 95% of the cases. Using a rat model, we showed that bilateral DBS of the subthalamic nucleus improves parkinsonian motor disability, but can induce behavioral side effects, similar to the clinical situation. In addition, we showed that DBS of the globus pallidus can improve motor and cognitive symptoms in a rat model of Huntington's disease. Nevertheless, during the process of the development and validation of experimental DBS, we encountered specific problems. These are discussed in detail. Experimental DBS in freely moving animals is an adequate tool to explore new indications for DBS and to refine DBS technology.

  6. Integrated modelling in materials and process technology

    DEFF Research Database (Denmark)

    Hattel, Jesper Henri

    2008-01-01

    processes from the viewpoint of combined materials and process modelling are presented: solidification of thin walled ductile cast iron, integrated modelling of spray forming and multiphysics modelling of friction stir welding. The fourth example describes integrated modelling applied to a failure analysis...... of premature rupture of a stellite weld on a P91 valve used in a power plant. For all four examples, the focus is put on modelling results rather than describing the models in detail. Proper comparison with experimental work is given in all examples for model validation as well as relevant references...

  7. Modeling the brain-pituitary-gonad axis in salmon

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jonghan; Hayton, William L.; Schultz, Irv R.

    2006-08-24

    To better understand the complexity of the brain-pituitary-gonad axis (BPG) in fish, we developed a biologically based pharmacodynamic model capable of accurately predicting the normal functioning of the BPG axis in salmon. This first-generation model consisted of a set of 13 equations whose formulation was guided by published values for plasma concentrations of pituitary- (FSH, LH) and ovary- (estradiol, 17a,20b-dihydroxy-4-pregnene-3-one) derived hormones measured in Coho salmon over an annual spawning period. In addition, the model incorporated pertinent features of previously published mammalian models and indirect response pharmacodynamic models. Model-based equations include a description of gonadotropin releasing hormone (GnRH) synthesis and release from the hypothalamus, which is controlled by environmental variables such as photoperiod and water temperature. GnRH stimulated the biosynthesis of mRNA for FSH and LH, which were also influenced by estradiol concentration in plasma. The level of estradiol in the plasma was regulated by the oocytes, which moved along a maturation progression. Estradiol was synthesized at a basal rate and as oocytes matured, stimulation of its biosynthesis occurred. The BPG model can be integrated with toxico-genomic, -proteomic data, allowing linkage between molecular based biomarkers and reproduction in fish.

  8. Poorer physical fitness is associated with reduced structural brain integrity in heart failure.

    Science.gov (United States)

    Alosco, Michael L; Brickman, Adam M; Spitznagel, Mary Beth; Griffith, Erica Y; Narkhede, Atul; Raz, Naftali; Cohen, Ronald; Sweet, Lawrence H; Colbert, Lisa H; Josephson, Richard; Hughes, Joel; Rosneck, Jim; Gunstad, John

    2013-05-15

    Physical fitness is an important correlate of structural and functional integrity of the brain in healthy adults. In heart failure (HF) patients, poor physical fitness may contribute to cognitive dysfunction and we examined the unique contribution of physical fitness to brain structural integrity among patients with HF. Sixty-nine HF patients performed the Modified Mini Mental State examination (3MS) and underwent brain magnetic resonance imaging. All participants completed the 2-minute step test (2MST), a brief measure of physical fitness. We examined the associations between cognitive performance, physical fitness, and three indices of global brain integrity: total cortical gray matter volume, total white matter volume, and whole brain cortical thickness. Regression analyses adjusting for demographic characteristics, medical variables (e.g., left ventricular ejection fraction), and intracranial volume revealed reduced performance on the 2MST were associated with decreased gray matter volume and thinner cortex (passociated with poorer 3MS scores (pphysical fitness is common in HF and associated with reduced structural brain integrity. Prospective studies are needed to elucidate underlying mechanisms for the influence of physical fitness on brain health in HF. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

    Science.gov (United States)

    Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

    2015-03-01

    Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing

  10. Resveratrol defends blood-brain barrier integrity in experimental autoimmune encephalomyelitis mice.

    Science.gov (United States)

    Wang, Dong; Li, Shi-Ping; Fu, Jin-Sheng; Zhang, Sheng; Bai, Lin; Guo, Li

    2016-11-01

    The mouse autoimmune encephalomyelitis (EAE), an experimental model of multiple sclerosis (MS), is primarily characterized as dysfunction of the blood-brain barrier (BBB). Resveratrol exhibits anti-inflammatory, antioxidative, and neuroprotective activities. We investigated the beneficial effects of resveratrol in protecting the integrity of the BBB in EAE mice and observed improved clinical outcome in the EAE mice after resveratrol treatment. Evans blue (EB) extravasation was used to detect the disruption of BBB. Western blot were used to detected the tight junction proteins and adhesion molecules zonula occludens-1 (ZO-1), occludin, ICAM-1, and VCAM-1. Inflammatory factors inducible nitric oxide synthase (iNOS), IL-1β, and arginase 1 were evaluated by quantitative RT-PCR (qPCR) and IL-10 by ELISA. NADPH oxidase (NOX) levels were evaluated by qPCR, and its activity was analyzed by lucigenin-derived chemiluminescence. Resveratrol at doses of 25 and 50 mg/kg produced a dose-dependent decrease in EAE paralysis and EB leakage, ameliorated EAE-induced loss of tight junction proteins ZO-1, occludin, and claudin-5, as well as repressed the EAE-induced increase in adhesion proteins ICAM-1 and VCAM-1. In addition, resveratrol suppressed the EAE-induced overexpression of proinflammatory transcripts iNOS and IL-1β and upregulated the expression of anti-inflammatory transcripts arginase 1 and IL-10 cytokine in the brain. Furthermore, resveratrol downregulated the overexpressed NOX2 and NOX4 in the brain and suppressed NADPH activity. Resveratrol ameliorates the clinical severity of MS through maintaining the BBB integrity in EAE mice. Copyright © 2016 the American Physiological Society.

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

    Directory of Open Access Journals (Sweden)

    Peter Carbone

    2011-10-01

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

  12. [NOVEL STRATEGY IN THE RADIOTHERAPY OF METASTATIC BRAIN TUMORS: SIMULTANEOUS WHOLE BRAIN RADIOTHERAPY AND INTEGRATED STEREOTACTIC RADIOSURGERY].

    Science.gov (United States)

    Kalincsák, Judit; László, Zoltán; Sebestyén, Zsolt; Kovács, Péter; Horváth, Zsolt; Dóczi, Tamás; Mangel László

    2015-11-30

    Treatment of central nervous system (CNS) tumors has always played an important role in development of radiotherapy techniques. Precise patient immobilisation, non-coplanar field arrangement, conformal treatment, arc therapy, radiosurgery, application of image fusion to radiation planning or re-irradiation were first introduced into clinical routine in the treatment of brain tumors. A modern multifunctional radiation instrument, Novalis TX has been installed at the University of Pécs two years ago. New methods, such as real time 3D image guided therapy, dynamic arc therapy and ultra-conformity offer further progress in treatment of CNS tumors. Whole brain irradiation and simultaneous fractionated stereotactic radiosurgery or integrated boost seem to be an optimal method in the treatment of not only soliter or oligo, but even a higher number (4-9) and not typically radiosensitive brain metastases. The new treatment strategy is illustrated by presentation of four case histories. Treatment protocol was completed in all cases. Treatment period of 1.5 to 3 weeks, and treatment time of only a few minutes were not stressful for the patients. A quite remarkable clinical improvement as to general condition of the patients was experienced in three cases. Follow-up images confirmed either remission or a stable disease. Simultaneous whole brain radiotherapy and integrated stereotactic radiosurgery is a reproducible, safe method that offers an effective irradiation with delivery of definitive dosage even in cases with radio-insensitive brain metastasis.

  13. Mobile Technology Integrated Pedagogical Model

    Science.gov (United States)

    Khan, Arshia

    2014-01-01

    Integrated curricula and experiential learning are the main ingredients to the recipe to improve student learning in higher education. In the academic computer science world it is mostly assumed that this experiential learning takes place at a business as an internship experience. The intent of this paper is to schism the traditional understanding…

  14. Associations between insulin action and integrity of brain microstructure differ with familial longevity and with age

    Directory of Open Access Journals (Sweden)

    Abimbola A. Akintola

    2015-05-01

    Full Text Available Impaired glucose metabolism and type 2 diabetes have been associated with cognitive decline, dementia, and with structural and functional brain features. However, it is unclear whether these associations differ in individuals that differ in familial longevity or age. Here, we investigated the association between parameters of glucose metabolism and microstructural brain integrity in offspring of long-lived families (offspring and controls; and age categories thereof. From the Leiden Longevity Study, 132 participants underwent oral glucose tolerance test to assess glycemia (fasted glucose and glucose area-under-the-curve (AUC, insulin resistance (fasted insulin, AUCinsulin, and homeostatic model assessment of insulin resistance (HOMA-IR, and pancreatic Beta cell secretory capacity (insulinogenic index. 3Tesla MRI and Magnetization Transfer (MT imaging MT-ratio peak-height was used to quantify differences in microstructural brain parenchymal tissue homogeneity that remain invisible on conventional MRI. Analyses were performed in offspring and age-matched controls, with and without stratification for age.In the full offspring group only, reduced peak-height in grey and white matter was inversely associated with AUCinsulin, fasted insulin, HOMA-IR and insulinogenic-index (all p65 years: in younger controls, significantly stronger inverse associations were observed between peak-height and fasted glucose, AUCglucose, fasted insulin, AUCinsulin and HOMA-IR in grey matter; and for AUCglucose, fasted insulin and HOMA-IR in white matter (all P-interaction<0.05. Although the strength of the associations tended to attenuate with age in the offspring group, the difference between age groups was not statistically significant. Thus, associations between impaired insulin action and reduced microstructural brain parenchymal tissue homogeneity were stronger in offspring compared to controls, and seemed to diminish with age.

  15. The selectivity and promiscuity of brain-neuroregenerative inhibitors between ROCK1 and ROCK2 isoforms: An integration of SB-QSSR modelling, QM/MM analysis and in vitro kinase assay.

    Science.gov (United States)

    Zhu, L; Yang, Y; Lu, X

    2016-01-01

    The Rho-associated kinases (ROCKs) have long been recognized as an attractive therapeutic target for various neurological diseases; selective inhibition of ROCK1 and ROCK2 isoforms would result in distinct biological effects on neurogenesis, neuroplasticity and neuroregeneration after brain surgery and traumatic brain injury. However, the discovery and design of isoform-selective inhibitors remain a great challenge due to the high conservation and similarity between the kinase domains of ROCK1 and ROCK2. Here, a structure-based quantitative structure-selectivity relationship (SB-QSSR) approach was used to correlate experimentally measured selectivity with the difference in inhibitor binding to the two kinase isoforms. The resulting regression models were examined rigorously through both internal cross-validation and external blind validation; a nonlinear predictor was found to have high fitting stability and strong generalization ability, which was then employed to perform virtual screening against a structurally diverse, drug-like compound library. Consequently, five and seven hits were identified as promising candidates of 1-o-2 and 2-o-1 selective inhibitors, respectively, from which seven purchasable compounds were tested in vitro using a standard kinase assay protocol to determine their inhibitory activity against and selectivity between ROCK1 and ROCK2. The structural basis, energetic property and biological implication underlying inhibitor selectivity and promiscuity were also investigated systematically using a hybrid quantum mechanics/molecular mechanics (QM/MM) scheme.

  16. Open source integrated modeling environment Delta Shell

    Science.gov (United States)

    Donchyts, G.; Baart, F.; Jagers, B.; van Putten, H.

    2012-04-01

    In the last decade, integrated modelling has become a very popular topic in environmental modelling since it helps solving problems, which is difficult to model using a single model. However, managing complexity of integrated models and minimizing time required for their setup remains a challenging task. The integrated modelling environment Delta Shell simplifies this task. The software components of Delta Shell are easy to reuse separately from each other as well as a part of integrated environment that can run in a command-line or a graphical user interface mode. The most components of the Delta Shell are developed using C# programming language and include libraries used to define, save and visualize various scientific data structures as well as coupled model configurations. Here we present two examples showing how Delta Shell simplifies process of setting up integrated models from the end user and developer perspectives. The first example shows coupling of a rainfall-runoff, a river flow and a run-time control models. The second example shows how coastal morphological database integrates with the coastal morphological model (XBeach) and a custom nourishment designer. Delta Shell is also available as open-source software released under LGPL license and accessible via http://oss.deltares.nl.

  17. Performance modeling of a wearable brain PET (BET) camera

    Science.gov (United States)

    Schmidtlein, C. R.; Turner, J. N.; Thompson, M. O.; Mandal, K. C.; Häggström, I.; Zhang, J.; Humm, J. L.; Feiglin, D. H.; Krol, A.

    2016-03-01

    Purpose: To explore, by means of analytical and Monte Carlo modeling, performance of a novel lightweight and low-cost wearable helmet-shaped Brain PET (BET) camera based on thin-film digital Geiger Avalanche Photo Diode (dGAPD) with LSO and LaBr3 scintillators for imaging in vivo human brain processes for freely moving and acting subjects responding to various stimuli in any environment. Methods: We performed analytical and Monte Carlo modeling PET performance of a spherical cap BET device and cylindrical brain PET (CYL) device, both with 25 cm diameter and the same total mass of LSO scintillator. Total mass of LSO in both the BET and CYL systems is about 32 kg for a 25 mm thick scintillator, and 13 kg for 10 mm thick scintillator (assuming an LSO density of 7.3 g/ml). We also investigated a similar system using an LaBr3 scintillator corresponding to 22 kg and 9 kg for the 25 mm and 10 mm thick systems (assuming an LaBr3 density of 5.08 g/ml). In addition, we considered a clinical whole body (WB) LSO PET/CT scanner with 82 cm ring diameter and 15.8 cm axial length to represent a reference system. BET consisted of distributed Autonomous Detector Arrays (ADAs) integrated into Intelligent Autonomous Detector Blocks (IADBs). The ADA comprised of an array of small LYSO scintillator volumes (voxels with base a×a: 1.0 50% better noise equivalent count (NEC) performance relative to the CYL geometry, and >1100% better performance than a WB geometry for 25 mm thick LSO and LaBr3. For 10 mm thick LaBr3 equivalent mass systems LSO (7 mm thick) performed ~40% higher NEC than LaBr3. Analytic and Monte Carlo simulations also showed that 1×1×3 mm scintillator crystals can achieve ~1.2 mm FWHM spatial resolution. Conclusions: This study shows that a spherical cap brain PET system can provide improved NEC while preserving spatial resolution when compared to an equivalent dedicated cylindrical PET brain camera and shows greatly improved PET performance relative to a conventional

  18. Comparing Structural Brain Connectivity by the Infinite Relational Model

    DEFF Research Database (Denmark)

    Ambrosen, Karen Marie Sandø; Herlau, Tue; Dyrby, Tim

    2013-01-01

    The growing focus in neuroimaging on analyzing brain connectivity calls for powerful and reliable statistical modeling tools. We examine the Infinite Relational Model (IRM) as a tool to identify and compare structure in brain connectivity graphs by contrasting its performance on graphs from...

  19. Impaired visual integration in children with traumatic brain injury: an observational study

    NARCIS (Netherlands)

    Konigs, M.; Weeda, W.D.; van Heurn, L.W.E.; Vermeulen, R.J.; Goslings, J.C.; Luitse, J.S.K.; Poll-The, B.T.; Beelen, A.; Wees, M.; Kemps, R.J.J.K.; Catsman-Berrevoets, C.E.; Oosterlaan, J.

    2015-01-01

    Background Axonal injury after traumatic brain injury (TBI) may cause impaired sensory integration. We aim to determine the effects of childhood TBI on visual integration in relation to general neurocognitive functioning. Methods We compared children aged 6-13 diagnosed with TBI (n = 103; M = 1.7

  20. Impaired Visual Integration in Children with Traumatic Brain Injury: An Observational Study

    NARCIS (Netherlands)

    M. Königs (Marsh); W.D. Weeda (Wouter D.); L.W.E. Van Heurn (L.W. Ernest); R.J. Vermeulen (R. Jeroen); J.C. Goslings (Carel); J.S.K. Luitse (Jan S.K.); B.T. Poll-Thé (Bwee Tien); A. Beelen (Anita); M. Van Der Wees (Marleen); R.J.J.K. Kemps (Rachèl J.J.K.); C.E. Catsman-Berrevoets (Coriene); J. Oosterlaan (Jaap)

    2015-01-01

    textabstractBackground Axonal injury after traumatic brain injury (TBI) may cause impaired sensory integration. We aim to determine the effects of childhood TBI on visual integration in relation to general neurocognitive functioning. Methods We compared children aged 6-13 diagnosed with TBI (n =

  1. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology have used each model component in an offline mode where the models are run in sequential steps and one model serves as a boundary condition or data input source to the other. Within recent years a new field of research has emerged where efforts have been made to dynamically couple existing climate....... The modelling tool consists of a fully dynamic two-way coupling of the HIRHAM regional climate model and the MIKE SHE hydrological model. The expected gain is twofold. Firstly, HIRHAM utilizes the land surface component of the combined MIKE SHE/SWET hydrology and land surface model (LSM), which is superior...

  2. Individual brain structure and modelling predict seizure propagation.

    Science.gov (United States)

    Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K

    2017-03-01

    See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

  3. Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

    DEFF Research Database (Denmark)

    Arbib, Michael A.; Bonaiuto, James J.; Bornkessel-Schlesewsky, Ina

    2014-01-01

    We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding - separately or together - neurocomputational models and empirical...

  4. Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

    Science.gov (United States)

    Bonaiuto, James J.; Bornkessel-Schlesewsky, Ina; Kemmerer, David; MacWhinney, Brian; Nielsen, Finn Årup; Oztop, Erhan

    2014-01-01

    We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding – separately or together – neurocomputational models and empirical data that serve systems and cognitive neuroscience. PMID:24234916

  5. Finite difference time domain (FDTD) modeling of implanted deep brain stimulation electrodes and brain tissue.

    Science.gov (United States)

    Gabran, S R I; Saad, J H; Salama, M M A; Mansour, R R

    2009-01-01

    This paper demonstrates the electromagnetic modeling and simulation of an implanted Medtronic deep brain stimulation (DBS) electrode using finite difference time domain (FDTD). The model is developed using Empire XCcel and represents the electrode surrounded with brain tissue assuming homogenous and isotropic medium. The model is created to study the parameters influencing the electric field distribution within the tissue in order to provide reference and benchmarking data for DBS and intra-cortical electrode development.

  6. Brain Wave Biofeedback: Benefits of Integrating Neurofeedback in Counseling

    Science.gov (United States)

    Myers, Jane E.; Young, J. Scott

    2012-01-01

    Consistent with the "2009 Standards" of the Council for Accreditation of Counseling and Related Educational Programs, counselors must understand neurobiological behavior in individuals of all developmental levels. This requires understanding the brain and strategies for applying neurobiological concepts in counseling practice, training, and…

  7. Integration of letters and speech sounds in the human brain

    NARCIS (Netherlands)

    van Atteveldt, Nienke; Formisano, Elia; Goebel, Rainer; Blomert, Leo

    2004-01-01

    Most people acquire literacy skills with remarkable ease, even though the human brain is not evolutionarily adapted to this relatively new cultural phenomenon. Associations between letters and speech sounds form the basis of reading in alphabetic scripts. We investigated the functional neuroanatomy

  8. Social Ecological Model Analysis for ICT Integration

    Science.gov (United States)

    Zagami, Jason

    2013-01-01

    ICT integration of teacher preparation programmes was undertaken by the Australian Teaching Teachers for the Future (TTF) project in all 39 Australian teacher education institutions and highlighted the need for guidelines to inform systemic ICT integration approaches. A Social Ecological Model (SEM) was used to positively inform integration…

  9. Epsilon Aminocaproic Acid Pretreatment Provides Neuroprotection Following Surgically Induced Brain Injury in a Rat Model.

    Science.gov (United States)

    Komanapalli, Esther S; Sherchan, Prativa; Rolland, William; Khatibi, Nikan; Martin, Robert D; Applegate, Richard L; Tang, Jiping; Zhang, John H

    2016-01-01

    Neurosurgical procedures can damage viable brain tissue unintentionally by a wide range of mechanisms. This surgically induced brain injury (SBI) can be a result of direct incision, electrocauterization, or tissue retraction. Plasmin, a serine protease that dissolves fibrin blood clots, has been shown to enhance cerebral edema and hemorrhage accumulation in the brain through disruption of the blood brain barrier. Epsilon aminocaproic acid (EAA), a recognized antifibrinolytic lysine analogue, can reduce the levels of active plasmin and, in doing so, potentially can preserve the neurovascular unit of the brain. We investigated the role of EAA as a pretreatment neuroprotective modality in a SBI rat model, hypothesizing that EAA therapy would protect brain tissue integrity, translating into preserved neurobehavioral function. Male Sprague-Dawley rats were randomly assigned to one of four groups: sham (n = 7), SBI (n = 7), SBI with low-dose EAA, 150 mg/kg (n = 7), and SBI with high-dose EAA, 450 mg/kg (n = 7). SBI was induced by partial right frontal lobe resection through a frontal craniotomy. Postoperative assessment at 24 h included neurobehavioral testing and measurement of brain water content. Results at 24 h showed both low- and high-dose EAA reduced brain water content and improved neurobehavioral function compared with the SBI groups. This suggests that EAA may be a useful pretherapeutic modality for SBI. Further studies are needed to clarify optimal therapeutic dosing and to identify mechanisms of neuroprotection in rat SBI models.

  10. The Brain on Stress: Toward an Integrative Approach to Brain, Body and Behavior

    OpenAIRE

    McEwen, Bruce S.

    2013-01-01

    The discovery of stress hormone receptors in the hippocampal formation has fostered research showing that the brain, including its higher cognitive centers, is the key organ of the response to stressors, both in terms of perception of what is stressful and for its ability to determine the consequences of stress for both brain and body via the neuroendocrine, autonomic, immune and metabolic systems. These systems are, in turn, responsible for either successful adaptation or pathophysiology due...

  11. The Brain on Stress: Toward an Integrative Approach to Brain, Body, and Behavior.

    Science.gov (United States)

    McEwen, Bruce S

    2013-11-01

    The discovery of stress-hormone receptors in the hippocampal formation has fostered research showing that the brain, including its higher cognitive centers, is the key organ of the response to stressors, in terms of both perception of what is stressful and its ability to determine the consequences of stress for brain and body via the neuroendocrine, autonomic, immune, and metabolic systems. These systems, in turn, are responsible for either successful adaptation or pathophysiology as a result of the cumulative burden of adaptation to stress and maladaptive lifestyle, which is known as "allostatic load." The brain itself is also a target of stress and stress-related hormones, and it undergoes structural and functional remodeling and significant changes in gene expression. These changes are adaptive under normal circumstances but can lead to damage when stress is excessive. The growing recognition of the adaptive plasticity and stress vulnerability of the brain itself, which began with research on the hippocampus, now includes other brain regions such as the amygdala and prefrontal cortex and fear-related memories, working memory, and self-regulatory behaviors. The interactions between these brain regions during the biological embedding of experiences over the life course determines whether events in the social and physical environment will lead to successful adaptation or to maladaptation and impaired mental and physical health, with implications for understanding health disparities and the impact of early life adversity and for intervention and prevention strategies. © The Author(s) 2013.

  12. Modeling Brain Circuitry over a Wide Range of Scales

    Directory of Open Access Journals (Sweden)

    Pascal eFua

    2015-04-01

    Full Text Available If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes (LM see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the topology and the connection strength are integral parts of the brain's wiring diagram, being able to combine these two modalities is critically important.In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. In this paper, we briefly review the Computer Vision techniques we have developed at EPFL to address this need. They include delineating dendritic arbors from LM imagery, segmenting organelles from EM, and combining the two into a consistent representation.

  13. Integrated Process Model on Intercultural Competence

    National Research Council Canada - National Science Library

    Diana Bebenova - Nikolova

    2016-01-01

    The paper proposes an integrated model on intercultural competence, which attempts to present intercultural communication and competence from the term point of the dialectical approach, described by Martin and Nakayama (2010...

  14. Population-averaged macaque brain atlas with high-resolution ex vivo DTI integrated into in vivo space.

    Science.gov (United States)

    Feng, Lei; Jeon, Tina; Yu, Qiaowen; Ouyang, Minhui; Peng, Qinmu; Mishra, Virendra; Pletikos, Mihovil; Sestan, Nenad; Miller, Michael I; Mori, Susumu; Hsiao, Steven; Liu, Shuwei; Huang, Hao

    2017-12-01

    Animal models of the rhesus macaque (Macaca mulatta), the most widely used nonhuman primate, have been irreplaceable in neurobiological studies. However, a population-averaged macaque brain diffusion tensor imaging (DTI) atlas, including comprehensive gray and white matter labeling as well as bony and facial landmarks guiding invasive experimental procedures, is not available. The macaque white matter tract pathways and microstructures have been rarely recorded. Here, we established a population-averaged macaque brain atlas with high-resolution ex vivo DTI integrated into in vivo space incorporating bony and facial landmarks, and delineated microstructures and three-dimensional pathways of major white matter tracts in vivo MRI/DTI and ex vivo (postmortem) DTI of ten rhesus macaque brains were acquired. Single-subject macaque brain DTI template was obtained by transforming the postmortem high-resolution DTI data into in vivo space. Ex vivo DTI of ten macaque brains was then averaged in the in vivo single-subject template space to generate population-averaged macaque brain DTI atlas. The white matter tracts were traced with DTI-based tractography. One hundred and eighteen neural structures including all cortical gyri, white matter tracts and subcortical nuclei, were labeled manually on population-averaged DTI-derived maps. The in vivo microstructural metrics of fractional anisotropy, axial, radial and mean diffusivity of the traced white matter tracts were measured. Population-averaged digital atlas integrated into in vivo space can be used to label the experimental macaque brain automatically. Bony and facial landmarks will be available for guiding invasive procedures. The DTI metric measurements offer unique insights into heterogeneous microstructural profiles of different white matter tracts.

  15. Galectin-1 suppresses methamphetamine induced neuroinflammation in human brain microvascular endothelial cells: Neuroprotective role in maintaining blood brain barrier integrity.

    Science.gov (United States)

    Parikh, Neil U; Aalinkeel, R; Reynolds, J L; Nair, B B; Sykes, D E; Mammen, M J; Schwartz, S A; Mahajan, S D

    2015-10-22

    Methamphetamine (Meth) abuse can lead to the breakdown of the blood-brain barrier (BBB) integrity leading to compromised CNS function. The role of Galectins in the angiogenesis process in tumor-associated endothelial cells (EC) is well established; however no data are available on the expression of Galectins in normal human brain microvascular endothelial cells and their potential role in maintaining BBB integrity. We evaluated the basal gene/protein expression levels of Galectin-1, -3 and -9 in normal primary human brain microvascular endothelial cells (BMVEC) that constitute the BBB and examined whether Meth altered Galectin expression in these cells, and if Galectin-1 treatment impacted the integrity of an in-vitro BBB. Our results showed that BMVEC expressed significantly higher levels of Galectin-1 as compared to Galectin-3 and -9. Meth treatment increased Galectin-1 expression in BMVEC. Meth induced decrease in TJ proteins ZO-1, Claudin-3 and adhesion molecule ICAM-1 was reversed by Galectin-1. Our data suggests that Galectin-1 is involved in BBB remodeling and can increase levels of TJ proteins ZO-1 and Claudin-3 and adhesion molecule ICAM-1 which helps maintain BBB tightness thus playing a neuroprotective role. Galectin-1 is thus an important regulator of immune balance from neurodegeneration to neuroprotection, which makes it an important therapeutic agent/target in the treatment of drug addiction and other neurological conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow.

    Science.gov (United States)

    Stockton, David B; Santamaria, Fidel

    2017-10-01

    We developed software tools to download, extract features, and organize the Cell Types Database from the Allen Brain Institute (ABI) in order to integrate its whole cell patch clamp characterization data into the automated modeling/data analysis cycle. To expand the potential user base we employed both Python and MATLAB. The basic set of tools downloads selected raw data and extracts cell, sweep, and spike features, using ABI's feature extraction code. To facilitate data manipulation we added a tool to build a local specialized database of raw data plus extracted features. Finally, to maximize automation, we extended our NeuroManager workflow automation suite to include these tools plus a separate investigation database. The extended suite allows the user to integrate ABI experimental and modeling data into an automated workflow deployed on heterogeneous computer infrastructures, from local servers, to high performance computing environments, to the cloud. Since our approach is focused on workflow procedures our tools can be modified to interact with the increasing number of neuroscience databases being developed to cover all scales and properties of the nervous system.

  17. Volumetric Intraoperative Brain Deformation Compensation: Model Development and Phantom Validation

    Science.gov (United States)

    DeLorenzo, Christine; Papademetris, Xenophon; Staib, Lawrence H.; Vives, Kenneth P.; Spencer, Dennis D.; Duncan, James S.

    2012-01-01

    During neurosurgery, nonrigid brain deformation may affect the reliability of tissue localization based on preoperative images. To provide accurate surgical guidance in these cases, preoperative images must be updated to reflect the intraoperative brain. This can be accomplished by warping these preoperative images using a biomechanical model. Due to the possible complexity of this deformation, intraoperative information is often required to guide the model solution. In this paper, a linear elastic model of the brain is developed to infer volumetric brain deformation associated with measured intraoperative cortical surface displacement. The developed model relies on known material properties of brain tissue, and does not require further knowledge about intraoperative conditions. To provide an initial estimation of volumetric model accuracy, as well as determine the model’s sensitivity to the specified material parameters and surface displacements, a realistic brain phantom was developed. Phantom results indicate that the linear elastic model significantly reduced localization error due to brain shift, from >16 mm to under 5 mm, on average. In addition, though in vivo quantitative validation is necessary, preliminary application of this approach to images acquired during neocortical epilepsy cases confirms the feasibility of applying the developed model to in vivo data. PMID:22562728

  18. Integrated climate and hydrology modelling

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl

    To ensure optimal management and sustainable strategies for water resources, infrastructures, food production and ecosystems there is a need for an improved understanding of feedback and interaction mechanisms between the atmosphere and the land surface. This is especially true in light of expected...... global warming and increased frequency of extreme events. The skill in developing projections of both the present and future climate depends essentially on the ability to numerically simulate the processes of atmospheric circulation, hydrology, energy and ecology. Previous modelling efforts of climate...... and hydrology models to more directly include the interaction between the atmosphere and the land surface. The present PhD study is motivated by an ambition of developing and applying a modelling tool capable of including the interaction and feedback mechanisms between the atmosphere and the land surface...

  19. Statistical Challenges in Modeling Big Brain Signals

    KAUST Repository

    Yu, Zhaoxia

    2017-11-01

    Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.

  20. Statistical Challenges in Modeling Big Brain Signals

    OpenAIRE

    Yu, Zhaoxia; Pluta, Dustin; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando

    2017-01-01

    Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.

  1. Animal models of brain dysfunction in phenylketonuria

    NARCIS (Netherlands)

    Martynyuk, A. E.; van Spronsen, F. J.; Van der Zee, E. A.

    2010-01-01

    Phenylketonuria (PKU) is a metabolic disorder that results in significant brain dysfunction if untreated. Although phenylalanine restricted diets instituted at birth have clearly improved PKU outcomes, neuropsychological deficits and neurological changes still represent substantial problems. The

  2. No need to talk, I know you: familiarity influences early multisensory integration in a songbird's brain

    Directory of Open Access Journals (Sweden)

    Isabelle GEORGE

    2011-01-01

    Full Text Available It is well known that visual information can affect auditory perception, as in the famous McGurk effect, but little is known concerning the processes involved. To address this issue, we used the best-developed animal model to study language-related processes in the brain: songbirds. European starlings were exposed to audiovisual compared to auditory-only playback of conspecific songs, while electrophysiological recordings were made in their primary auditory area (Field L. The results show that the audiovisual condition modulated the auditory responses. Enhancement and suppression were both observed, depending on the stimulus familiarity. Seeing a familiar bird led to suppressed auditory responses while seeing an unfamiliar bird led to response enhancement, suggesting that unisensory perception may be enough if the stimulus is familiar while redundancy may be required for unfamiliar items. This is to our knowledge the first evidence that multisensory integration may occur in a low-level, putatively unisensory area of a non-mammalian vertebrate brain, and also that familiarity of the stimuli may influence modulation of auditory responses by vision.

  3. Framework for describing community integration for people with acquired brain injury.

    Science.gov (United States)

    Parvaneh, Shahriar; Cocks, Errol

    2012-04-01

    Community integration is the ultimate goal of rehabilitation of adults with acquired brain injury which has a high incidence in the Australian population. The literature shows a need for a more comprehensive framework for community integration. This study developed a descriptive community integration framework drawn from views of five stakeholder groups and was compared with four similar frameworks. Thirty-seven experts in acquired brain injury, including practitioners, researchers, policy makers, people with acquired brain injury and family members participated. Using a Delphi method, an iterative process of surveys, interviews, and focus groups sought their views on community integration. Responses were analysed in three stages systematically to reduce a large quantity of raw data into a core set of descriptive themes. A final member checking process rated participants' agreement with the importance of each theme. Seven themes were identified and described: Relationships, Community Access, Acceptance, Occupation, Being at Home, Picking up Life Again, and Heightened Risks and Vulnerability. Themes were congruent with elements of the frameworks from the literature. Rich data came from the diverse stakeholders in the participant groups. Two unique themes reflected the importance of re-integration and recovering important aspects of previous lives, and identifying risks and vulnerabilities and providing safeguards. The framework reflected emphases that may be specific to acquired brain injury. It can be used as a basis for development of community integration programmes and outcome measures. © 2012 The Authors Australian Occupational Therapy Journal © 2012 Occupational Therapy Australia.

  4. NF-κB and epigenetic mechanisms as integrative regulators of brain resilience to anoxic stress.

    Science.gov (United States)

    Sarnico, Ilenia; Branca, Caterina; Lanzillotta, Annamaria; Porrini, Vanessa; Benarese, Marina; Spano, Pier Franco; Pizzi, Marina

    2012-10-02

    Brain cells display an amazing ability to respond to several different types of environmental stimuli and integrate this response physiologically. Some of these responses can outlive the original stimulus by days, weeks or even longer. Long-lasting changes in both physiological and pathological conditions occurring in response to external stimuli are almost always mediated by changes in gene expression. To effect these changes, cells have developed an impressive repertoire of signaling systems designed to modulate the activity of numerous transcription factors and epigenetic mechanisms affecting the chromatin structure. Since its initial characterization in the nervous system, NF-κB has shown to respond to multiple signals and elicit pleiotropic activities suggesting that it may play a pivotal role in integration of different types of information within the brain. Ample evidence demonstrates that NF-κB factors are engaged in and necessary for neuronal development and synaptic plasticity, but they also regulate brain response to environmental noxae. By focusing on the complexity of NF-κB transcriptional activity in neuronal cell death, it emerged that the composition of NF-κB active dimers finely tunes the neuronal vulnerability to brain ischemia. Even though we are only beginning to understand the contribution of distinct NF-κB family members to the regulation of gene transcription in the brain, an additional level of regulation of NF-κB activity has emerged as operated by the epigenetic mechanisms modulating histone acetylation. We will discuss NF-κB and epigenetic mechanisms as integrative regulators of brain resilience to anoxic stress and useful drug targets for restoration of brain function. This article is part of a Special Issue entitled: Brain Integration. Copyright © 2012 Elsevier B.V. All rights reserved.

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

    DEFF Research Database (Denmark)

    Albers, Kristoffer Jon

    of nodes with a shared connectivity pattern. Modelling the brain in great detail on a whole-brain scale is essential to fully understand the underlying organization of the brain and reveal the relations between structure and function, that allows sophisticated cognitive behaviour to emerge from ensembles...... of neurons. Relying on Markov Chain Monte Carlo (MCMC) simulations as the workhorse in Bayesian inference however poses significant computational challenges, especially when modelling networks at the scale and complexity supported by high-resolution whole-brain MRI. In this thesis, we present how to overcome...... these computational limitations and apply Bayesian stochastic block models for un-supervised data-driven clustering of whole-brain connectivity in full image resolution. We implement high-performance software that allows us to efficiently apply stochastic blockmodelling with MCMC sampling on large complex networks...

  6. Limited predictability of postmortem human brain tissue quality by RNA integrity numbers.

    Science.gov (United States)

    Sonntag, Kai-C; Tejada, George; Subburaju, Sivan; Berretta, Sabina; Benes, Francine M; Woo, Tsung-Ung W

    2016-07-01

    The RNA integrity number (RIN) is often considered to be a critical measure of the quality of postmortem human brains. However, it has been suggested that RINs do not necessarily reflect the availability of intact mRNA. Using the Agilent bioanalyzer and qRT-PCR, we explored whether RINs provide a meaningful way of assessing mRNA degradation and integrity in human brain samples by evaluating the expression of 3'-5' mRNA sequences of the cytochrome C-1 (CYC1) gene. Analysis of electropherograms showed that RINs were not consistently correlated with RNA or cDNA profiles and appeared to be poor predictors of overall cDNA quality. Cycle thresholds from qRT-PCR analysis to quantify the amount of CYC1 mRNA revealed positive correlations of RINs with amplification of full-length transcripts, despite the variable degree of linear degradation along the 3'-5' sequence. These data demonstrate that in postmortem human brain tissue the RIN is an indicator of mRNA quantity independent of degradation, but does not predict mRNA integrity, suggesting that RINs provide an incomplete measure of brain tissue quality. Quality assessment of postmortem human brains by RNA integrity numbers (RINs) may be misleading, as they do not measure intact mRNAs. We show that the RIN is an indicator of mRNA quantity independent of degradation, but does not predict mRNA integrity, suggesting that RINs provide an incomplete measure of brain tissue quality. Our results resolve controversial assumption on interpreting quality assessments of human postmortem brains by RINs. © 2016 International Society for Neurochemistry.

  7. Ontology modeling in physical asset integrity management

    CERN Document Server

    Yacout, Soumaya

    2015-01-01

    This book presents cutting-edge applications of, and up-to-date research on, ontology engineering techniques in the physical asset integrity domain. Though a survey of state-of-the-art theory and methods on ontology engineering, the authors emphasize essential topics including data integration modeling, knowledge representation, and semantic interpretation. The book also reflects novel topics dealing with the advanced problems of physical asset integrity applications such as heterogeneity, data inconsistency, and interoperability existing in design and utilization. With a distinctive focus on applications relevant in heavy industry, Ontology Modeling in Physical Asset Integrity Management is ideal for practicing industrial and mechanical engineers working in the field, as well as researchers and graduate concerned with ontology engineering in physical systems life cycles. This book also: Introduces practicing engineers, research scientists, and graduate students to ontology engineering as a modeling techniqu...

  8. The use of pigs in neuroscience: Modeling brains disorders

    DEFF Research Database (Denmark)

    Lind, Nanna Marie; Moustgaard, Anette; Jelsing, Jacob

    2007-01-01

    The use of pigs in neuroscience research has increased in the past decade, which has seen broader recognition of the potential of pigs as an animal for experimental modeling of human brain disorders. The volume of available background data concerning pig brain anatomy and neurochemistry has...

  9. Digital, three-dimensional average shaped atlas of the heliothis virescens brain with integrated gustatory and olfactory neurons

    Directory of Open Access Journals (Sweden)

    Pål Kvello

    2009-10-01

    Full Text Available We use the moth Heliothis virescens as model organism for studying the neural network involved in chemosensory coding and learning. The constituent neurons are characterised by intracellular recordings combined with staining, resulting in a single neuron identified in each brain preparation. In order to spatially relate the neurons of different preparations a common brain framework was required. We here present an average shaped atlas of the moth brain. It is based on 11 female brain preparations, each stained with a fluorescent synaptic marker and scanned in confocal laser-scanning microscope. Brain neuropils of each preparation were manually reconstructed in the computer software AMIRA, followed by generating the atlas using the Iterative Shape Average Procedure. To demonstrate the application of the atlas we have registered two olfactory and two gustatory interneurons, as well as the axonal projections of gustatory receptor neurons into the atlas, visualising their spatial relationships. The olfactory interneurons, showing the typical morphology of inner-tract antennal lobe projection neurons, projected in the calyces of the mushroom body and laterally in the protocerebral lobe. The two gustatory interneurons, responding to sucrose and quinine respectively, projected in different areas of the brain. The wide projections of the quinine responding neuron included a lateral area adjacent to the projections of the olfactory interneurons. The sucrose responding neuron was confined to the suboesophageal ganglion with dendritic arborizations overlapping the axonal projections of the gustatory receptor neurons on the proboscis. By serving as a tool for the integration of neurons, the atlas offers visual access to the spatial relationship between the neurons in three dimensions, and thus facilitates the study of neuronal networks in the Heliothis virescens brain. The moth standard brain is accessible at http://www.nt.ntnu.no/users/kvello/H_virescens_standardbrain/

  10. Development of integrated semiconductor optical sensors for functional brain imaging

    Science.gov (United States)

    Lee, Thomas T.

    Optical imaging of neural activity is a widely accepted technique for imaging brain function in the field of neuroscience research, and has been used to study the cerebral cortex in vivo for over two decades. Maps of brain activity are obtained by monitoring intensity changes in back-scattered light, called Intrinsic Optical Signals (IOS), that correspond to fluctuations in blood oxygenation and volume associated with neural activity. Current imaging systems typically employ bench-top equipment including lamps and CCD cameras to study animals using visible light. Such systems require the use of anesthetized or immobilized subjects with craniotomies, which imposes limitations on the behavioral range and duration of studies. The ultimate goal of this work is to overcome these limitations by developing a single-chip semiconductor sensor using arrays of sources and detectors operating at near-infrared (NIR) wavelengths. A single-chip implementation, combined with wireless telemetry, will eliminate the need for immobilization or anesthesia of subjects and allow in vivo studies of free behavior. NIR light offers additional advantages because it experiences less absorption in animal tissue than visible light, which allows for imaging through superficial tissues. This, in turn, reduces or eliminates the need for traumatic surgery and enables long-term brain-mapping studies in freely-behaving animals. This dissertation concentrates on key engineering challenges of implementing the sensor. This work shows the feasibility of using a GaAs-based array of vertical-cavity surface emitting lasers (VCSELs) and PIN photodiodes for IOS imaging. I begin with in-vivo studies of IOS imaging through the skull in mice, and use these results along with computer simulations to establish minimum performance requirements for light sources and detectors. I also evaluate the performance of a current commercial VCSEL for IOS imaging, and conclude with a proposed prototype sensor.

  11. Development of a generalized integral jet model

    DEFF Research Database (Denmark)

    Duijm, Nijs Jan; Kessler, A.; Markert, Frank

    2017-01-01

    Integral type models to describe stationary plumes and jets in cross-flows (wind) have been developed since about 1970. These models are widely used for risk analysis, to describe the consequences of many different scenarios. Alternatively, CFD codes are being applied, but computational...... model is needed to describe the rapid combustion of the flammable part of the plume (flash fire) and a third model has to be applied for the remaining jet fire. The objective of this paper is to describe the first steps of the development of an integral-type model describing the transient development...... and decay of a jet of flammable gas after a release from a pressure container. The intention is to transfer the stationary models to a fully transient model, capable to predict the maximum extension of short-duration, high pressure jets. The model development is supported by conducting a set of transient...

  12. Reptiles: a new model for brain evo-devo research.

    Science.gov (United States)

    Nomura, Tadashi; Kawaguchi, Masahumi; Ono, Katsuhiko; Murakami, Yasunori

    2013-03-01

    Vertebrate brains exhibit vast amounts of anatomical diversity. In particular, the elaborate and complex nervous system of amniotes is correlated with the size of their behavioral repertoire. However, the evolutionary mechanisms underlying species-specific brain morphogenesis remain elusive. In this review we introduce reptiles as a new model organism for understanding brain evolution. These animal groups inherited ancestral traits of brain architectures. We will describe several unique aspects of the reptilian nervous system with a special focus on the telencephalon, and discuss the genetic mechanisms underlying reptile-specific brain morphology. The establishment of experimental evo-devo approaches to studying reptiles will help to shed light on the origin of the amniote brains. Copyright © 2013 Wiley Periodicals, Inc.

  13. Integrating systems biology models and biomedical ontologies

    Science.gov (United States)

    2011-01-01

    Background Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. Results We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. Conclusions We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms. PMID:21835028

  14. An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States

    Science.gov (United States)

    2015-12-22

    AFRL-AFOSR-VA-TR-2016-0037 An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States Adrian Lee UNIVERSITY OF WASHINGTON...FORM TO THE ABOVE ORGANIZATION . 1. REPORT DATE (DD-MM-YYYY)      06-01-2016 2. REPORT TYPE Final Performance 3. DATES COVERED (From - To) 15-09-2012...to 14-09-2015 4. TITLE AND SUBTITLE An Integrated Neuroscience and Engineering Approach to Classifying Human Brain- States 5a.  CONTRACT NUMBER 5b

  15. Development of a generalized integral jet model

    DEFF Research Database (Denmark)

    Duijm, Nijs Jan; Kessler, A.; Markert, Frank

    2017-01-01

    and decay of a jet of flammable gas after a release from a pressure container. The intention is to transfer the stationary models to a fully transient model, capable to predict the maximum extension of short-duration, high pressure jets. The model development is supported by conducting a set of transient...... requirements still limit the number of scenarios that can be dealt with using CFD only. The integral models, however, are not suited to handle transient releases, such as releases from pressurized equipment, where the initially high release rate decreases rapidly with time. Further, on gas ignition, a second...... model is needed to describe the rapid combustion of the flammable part of the plume (flash fire) and a third model has to be applied for the remaining jet fire. The objective of this paper is to describe the first steps of the development of an integral-type model describing the transient development...

  16. New challenges in integrated water quality modelling

    NARCIS (Netherlands)

    Rode, M.; Arhonditsis, G.; Balin, D.; Kebede, T.; Krysanova, V.; Griensven, A.; Zee, van der S.E.A.T.M.

    2010-01-01

    There is an increasing pressure for development of integrated water quality models that effectively couple catchment and in-stream biogeochemical processes. This need stems from increasing legislative requirements and emerging demands related to contemporary climate and land use changes. Modelling

  17. The Integrated Developmental Model of Supervision.

    Science.gov (United States)

    Stoltenberg, Cal D.

    The Integrated Developmental Model (IDM) of supervision builds upon previous models of counselor and psychotherapist development. The IDM incorporates aspects of both a mechanistic view, using the machine as metaphor, and an organismic view, using the organism as metaphor, of development in describing trainee development through three levels and…

  18. An Integrated Model of Outplacement Counseling.

    Science.gov (United States)

    Aquilanti, Tara M.; Leroux, Janice

    1999-01-01

    The Aquilanti Integrated Model of Outplacement was developed from various aspects of existing grief and career theories. It comprises many practical elements that are present in the other models as well personal experience and knowledge of career counseling. It involves four phases: loss, grieving, and transition; personal development; job search;…

  19. Brain mechanisms in religion and spirituality : An integrative predictive processing framework

    NARCIS (Netherlands)

    van Elk, Michiel; Aleman, Andre

    We present the theory of predictive processing as a unifying framework to account for the neurocognitive basis of religion and spirituality. Our model is substantiated by discussing four different brain mechanisms that play a key role in religion and spirituality: temporal brain areas are associated

  20. Optically enhanced blood-brain-barrier crossing of plasmonic-active nanoparticles in preclinical brain tumor animal models

    Science.gov (United States)

    Yuan, Hsiangkuo; Wilson, Christy M.; Li, Shuqin; Fales, Andrew M.; Liu, Yang; Grant, Gerald; Vo-Dinh, Tuan

    2014-02-01

    Nanotechnology provides tremendous biomedical opportunities for cancer diagnosis, imaging, and therapy. In contrast to conventional chemotherapeutic agents where their actual target delivery cannot be easily imaged, integrating imaging and therapeutic properties into one platform facilitates the understanding of pharmacokinetic profiles, and enables monitoring of the therapeutic process in each individual. Such a concept dubbed "theranostics" potentiates translational research and improves precision medicine. One particular challenging application of theranostics involves imaging and controlled delivery of nanoplatforms across blood-brain-barrier (BBB) into brain tissues. Typically, the BBB hinders paracellular flux of drug molecules into brain parenchyma. BBB disrupting agents (e.g. mannitol, focused ultrasound), however, suffer from poor spatial confinement. It has been a challenge to design a nanoplatform not only acts as a contrast agent but also improves the BBB permeation. In this study, we demonstrated the feasibility of plasmonic gold nanoparticles as both high-resolution optical contrast agent and focalized tumor BBB permeation-inducing agent. We specifically examined the microscopic distribution of nanoparticles in tumor brain animal models. We observed that most nanoparticles accumulated at the tumor periphery or perivascular spaces. Nanoparticles were present in both endothelial cells and interstitial matrices. This study also demonstrated a novel photothermal-induced BBB permeation. Fine-tuning the irradiating energy induced gentle disruption of the vascular integrity, causing short-term extravasation of nanomaterials but without hemorrhage. We conclude that our gold nanoparticles are a powerful biocompatible contrast agent capable of inducing focal BBB permeation, and therefore envision a strong potential of plasmonic gold nanoparticle in future brain tumor imaging and therapy.

  1. Toward defining the anatomo-proteomic puzzle of the human brain: An integrative analysis.

    Science.gov (United States)

    Fernandez-Irigoyen, Joaquín; Labarga, Alberto; Zabaleta, Aintzane; de Morentin, Xabier Martínez; Perez-Valderrama, Estela; Zelaya, María Victoria; Santamaria, Enrique

    2015-10-01

    The human brain is exceedingly complex, constituted by billions of neurons and trillions of synaptic connections that, in turn, define ∼900 neuroanatomical subdivisions in the adult brain (Hawrylycz et al. An anatomically comprehensive atlas of the human brain transcriptome. Nature 2012, 489, 391-399). The human brain transcriptome has revealed specific regional transcriptional signatures that are regulated in a spatiotemporal manner, increasing the complexity of the structural and molecular organization of this organ (Kang et al. Spatio-temporal transcriptome of the human brain. Nature 2011, 478, 483-489). During the last decade, neuroproteomics has emerged as a powerful approach to profile neural proteomes using shotgun-based MS, providing complementary information about protein content and function at a global level. Here, we revise recent proteome profiling studies performed in human brain, with special emphasis on proteome mapping of anatomical macrostructures, specific subcellular compartments, and cerebrospinal fluid. Moreover, we have performed an integrative functional analysis of the protein compilation derived from these large-scale human brain proteomic studies in order to obtain a comprehensive view of human brain biology. Finally, we also discuss the potential contribution of our meta-analysis to the Chromosome-centric Human Proteome Project initiative. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. A propositional representation model of anatomical and functional brain data.

    Science.gov (United States)

    Maturana, Pablo; Batrancourt, Bénédicte

    2011-01-01

    Networks can represent a large number of systems. Recent advances in the domain of networks have been transferred to the field of neuroscience. For example, the graph model has been used in neuroscience research as a methodological tool to examine brain networks organization, topology and complex dynamics, as well as a framework to test the structure-function hypothesis using neuroimaging data. In the current work we propose a graph-theoretical framework to represent anatomical, functional and neuropsychological assessment instruments information. On the one hand, interrelationships between anatomic elements constitute an anatomical graph. On the other hand, a functional graph contains several cognitive functions and their more elementary cognitive processes. Finally, the neuropsychological assessment instruments graph includes several neuropsychological tests and scales linked with their different sub-tests and variables. The two last graphs are connected by relations of type "explore" linking a particular instrument with the cognitive function it explores. We applied this framework to a sample of patients with focal brain damage. Each patient was related to: (i) the cerebral entities injured (assessed with structural neuroimaging data) and (ii) the neusopsychological assessment tests carried out (weight by performance). Our model offers a suitable platform to visualize patients' relevant information, facilitating the representation, standardization and sharing of clinical data. At the same time, the integration of a large number of patients in this framework will make possible to explore relations between anatomy (injured entities) and function (performance in different tests assessing different cognitive functions) and the use of neurocomputational tools for graph analysis may help diagnostic and contribute to the comprehension of neural bases of cognitive functions. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. A novel three-phase model of brain tissue microstructure.

    Directory of Open Access Journals (Sweden)

    Jana L Gevertz

    Full Text Available We propose a novel biologically constrained three-phase model of the brain microstructure. Designing a realistic model is tantamount to a packing problem, and for this reason, a number of techniques from the theory of random heterogeneous materials can be brought to bear on this problem. Our analysis strongly suggests that previously developed two-phase models in which cells are packed in the extracellular space are insufficient representations of the brain microstructure. These models either do not preserve realistic geometric and topological features of brain tissue or preserve these properties while overestimating the brain's effective diffusivity, an average measure of the underlying microstructure. In light of the highly connected nature of three-dimensional space, which limits the minimum diffusivity of biologically constrained two-phase models, we explore the previously proposed hypothesis that the extracellular matrix is an important factor that contributes to the diffusivity of brain tissue. Using accurate first-passage-time techniques, we support this hypothesis by showing that the incorporation of the extracellular matrix as the third phase of a biologically constrained model gives the reduction in the diffusion coefficient necessary for the three-phase model to be a valid representation of the brain microstructure.

  4. Social Outcomes in Childhood Brain Disorder: A Heuristic Integration of Social Neuroscience and Developmental Psychology

    Science.gov (United States)

    Yeates, Keith Owen; Bigler, Erin D.; Dennis, Maureen; Gerhardt, Cynthia A.; Rubin, Kenneth H.; Stancin, Terry; Taylor, H. Gerry; Vannatta, Kathryn

    2010-01-01

    The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer interactions and relationships, social problem solving and communication, social-affective and cognitive-executive processes, and their neural substrates. The model is illustrated by research on a specific form of childhood brain disorder, traumatic brain injury. The heuristic model may promote research regarding the neural and cognitive-affective substrates of children’s social development. It also may engender more precise methods of measuring impairments and disabilities in children with brain disorder and suggest ways to promote their social adaptation. PMID:17469991

  5. Social outcomes in childhood brain disorder: a heuristic integration of social neuroscience and developmental psychology.

    Science.gov (United States)

    Yeates, Keith Owen; Bigler, Erin D; Dennis, Maureen; Gerhardt, Cynthia A; Rubin, Kenneth H; Stancin, Terry; Taylor, H Gerry; Vannatta, Kathryn

    2007-05-01

    The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer interactions and relationships, social problem solving and communication, social-affective and cognitive-executive processes, and their neural substrates. The model is illustrated by research on a specific form of childhood brain disorder, traumatic brain injury. The heuristic model may promote research regarding the neural and cognitive-affective substrates of children's social development. It also may engender more precise methods of measuring impairments and disabilities in children with brain disorder and suggest ways to promote their social adaptation. (c) 2007 APA, all rights reserved

  6. Brain activity related to integrative processes in visual object recognition

    DEFF Research Database (Denmark)

    Gerlach, Christian; Aaside, C T; Humphreys, G W

    2002-01-01

    to the involvement of re-entrant activation from stored structural knowledge. Evidence in favor of this interpretation comes from the additional finding that activation of the anterior part of the left fusiform gyrus and a more anterior part of the right inferior temporal gyrus, areas previously associated......We report evidence from a PET activation study that the inferior occipital gyri (likely to include area V2) and the posterior parts of the fusiform and inferior temporal gyri are involved in the integration of visual elements into perceptual wholes (single objects). Of these areas, the fusiform...... and inferior temporal gyri were more activated by tasks with recognizable stimuli than by tasks with unrecognizable stimuli. We propose that the posterior parts of the fusiform and inferior temporal gyri, compared with the inferior occipital gyri, are involved in higher level integration, due...

  7. From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval.

    Science.gov (United States)

    Geib, Benjamin R; Stanley, Matthew L; Dennis, Nancy A; Woldorff, Marty G; Cabeza, Roberto

    2017-04-01

    Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. Hum Brain Mapp 38:2242-2259, 2017. © 2017 Wiley

  8. MMM: A toolbox for integrative structure modeling.

    Science.gov (United States)

    Jeschke, Gunnar

    2017-08-11

    Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples. © 2017 The Protein Society.

  9. Data assimilation in integrated hydrological modelling

    DEFF Research Database (Denmark)

    Rasmussen, Jørn

    Integrated hydrological models are useful tools for water resource management and research, and advances in computational power and the advent of new observation types has resulted in the models generally becoming more complex and distributed. However, the models are often characterized by a high...... using both synthetic data and real observations. Groundwater head and stream discharge observations are assimilated in an integrated hydrological model, with the aim of updating the groundwater head, stream discharge and water level, and model parameters. When synthetically generated observations......, two bias-aware data assimilation algorithms are tested and were shown to successfully estimate the bias of most observations. The data assimilation framework was applied to real observations and an improvement in stream discharge was obtained compared to a deterministic model without data assimilation...

  10. Integrative Mechanisms of Oriented Neuronal Migration in the Developing Brain

    Science.gov (United States)

    Evsyukova, Irina; Plestant, Charlotte; Anton, E.S.

    2014-01-01

    The emergence of functional neuronal connectivity in the developing cerebral cortex depends on neuronal migration. This process enables appropriate positioning of neurons and the emergence of neuronal identity so that the correct patterns of functional synaptic connectivity between the right types and numbers of neurons can emerge. Delineating the complexities of neuronal migration is critical to our understanding of normal cerebral cortical formation and neurodevelopmental disorders resulting from neuronal migration defects. For the most part, the integrated cell biological basis of the complex behavior of oriented neuronal migration within the developing mammalian cerebral cortex remains an enigma. This review aims to analyze the integrative mechanisms that enable neurons to sense environmental guidance cues and translate them into oriented patterns of migration toward defined areas of the cerebral cortex. We discuss how signals emanating from different domains of neurons get integrated to control distinct aspects of migratory behavior and how different types of cortical neurons coordinate their migratory activities within the developing cerebral cortex to produce functionally critical laminar organization. PMID:23937349

  11. Development of a model for whole brain learning of physiology.

    Science.gov (United States)

    Eagleton, Saramarie; Muller, Anton

    2011-12-01

    In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed elaborates on these layers by relating the personality traits central to learning to the different quadrants of brain preference, as described by Neethling's brain profile, as the inner layer of the onion. This layer is encircled by the learning styles that describe different information-processing preferences for each brain quadrant. For the middle layer, the different stages of Kolb's learning cycle are classified into the four brain quadrants associated with the different brain processing strategies within the information processing circle. Each of the stages of Kolb's learning cycle is also associated with a specific cognitive learning strategy. These two inner circles are enclosed by the circle representing the role of the environment and instruction on learning. It relates environmental factors that affect learning and distinguishes between face-to-face and technology-assisted learning. This model informs on the design of instructional interventions for physiology to encourage whole brain learning.

  12. A porcine model of haematogenous brain infectionwith staphylococcus aureus

    DEFF Research Database (Denmark)

    Astrup, Lærke Boye; Agerholm, Jørgen Steen; Nielsen, Ole Lerberg

    2012-01-01

    A PORCINE MODEL OF HAEMATOGENOUS BRAIN INFECTION WITH STAPHYLOCOCCUS AUREUS Astrup Lærke1, Agerholm Jørgen1, Nielsen Ole1, Jensen Henrik1, Leifsson Páll1, Iburg Tine2. 1: Faculty of Health and Medical Sciences, University of Copenhagen, Denmark boye@life.ku.dk 2: National Veterinary Institute......, Uppsala, Sweden Introduction Staphylococcus aureus (S.aureus) is a common cause of sepsis and brain abscesses in man and a frequent cause of porcine pyaemia. Here we present a porcine model of haematogenous S. aureus-induced brain infection. Materials and Methods Four pigs had two intravenous catheters...

  13. Music plus Music Integration: A Model for Music Education Policy Reform That Reflects the Evolution and Success of Arts Integration Practices in 21st Century American Public Schools

    Science.gov (United States)

    Scripp, Lawrence; Gilbert, Josh

    2016-01-01

    This article explores the special case of integrative teaching and learning in music as a model for 21st century music education policy reform based on the principles that have evolved out of arts integration research and practices over the past century and informed by the recent rising tide of evidence of music's impact on brain capacity and…

  14. Integrating Sustainability in Organisations: An Activity-Based Sustainability Model

    National Research Council Canada - National Science Library

    Ana Rodríguez-Olalla; Carmen Aviles-Palacios

    2017-01-01

    .... Although global integration models address sustainability in organisations, these models present shortcomings and limitations and do not describe how to achieve the integration of sustainability...

  15. Integral equation models for endemic infectious diseases.

    Science.gov (United States)

    Hethcote, H W; Tudor, D W

    1980-03-01

    Endemic infectious diseases for which infection confers permanent immunity are described by a system of nonlinear Volterra integral equations of convolution type. These constant-parameter models include vital dynamics (birth and deaths), immunization and distributed infectious period. The models are shown to be well posed, the threshold criteria are determined and the asymptotic behavior is analysed. It is concluded that distributed delays do not change the thresholds and the asymptotic behaviors of the models.

  16. Modelling Brain Tissue using Magnetic Resonance Imaging

    DEFF Research Database (Denmark)

    Dyrby, Tim Bjørn

    2008-01-01

    Diffusion MRI, or diffusion weighted imaging (DWI), is a technique that measures the restricted diffusion of water molecules within brain tissue. Different reconstruction methods quantify water-diffusion anisotropy in the intra- and extra-cellular spaces of the neural environment. Fibre tracking...

  17. International summit on integrated environmental modeling

    Science.gov (United States)

    Gaber, Noha; Geller, Gary; Glynn, Pierre; Laniak, Gerry; Voinov, Alexey; Whelan, Gene; Roger, Moore; Hughes, Andrew

    2013-01-01

    This report describes the International Summit on Integrated Environmental Modeling (IEM), held in Reston, VA, on 7th-9th December 2010. The meeting brought together 57 scientists and managers from leading US and European government and non-governmental organizations, universities and companies together with international organizations convened over a number of years, including: the US Environmental Protection Agency (USEPA) workshop on Collaborative Approaches to Integrated Modeling: Better Integration for Better Decisionmaking (December, 2008); the AGU Fall Meeting, San Francisco (December 2009); and the International Congress on Environmental Modeling and Software (July 2010). From these meetings there is now recognition that many separate communities are involved in developing IEM. The aim of the Summit was to bring together two key groupings, the US and Europe, with the intention of creating a community open to all.

  18. Integrated Modelling - the next steps (Invited)

    Science.gov (United States)

    Moore, R. V.

    2010-12-01

    Integrated modelling (IM) has made considerable advances over the past decade but it has not yet been taken up as an operational tool in the way that its proponents had hoped. The reasons why will be discussed in Session U17. This talk will propose topics for a research and development programme and suggest an institutional structure which, together, could overcome the present obstacles. Their combined aim would be first to make IM into an operational tool useable by competent public authorities and commercial companies and, in time, to see it evolve into the modelling equivalent of Google Maps, something accessible and useable by anyone with a PC or an iphone and an internet connection. In a recent study, a number of government agencies, water authorities and utilities applied integrated modelling to operational problems. While the project demonstrated that IM could be used in an operational setting and had benefit, it also highlighted the advances that would be required for its widespread uptake. These were: greatly improving the ease with which models could be a) made linkable, b) linked and c) run; developing a methodology for applying integrated modelling; developing practical options for calibrating and validating linked models; addressing the science issues that arise when models are linked; extending the range of modelling concepts that can be linked; enabling interface standards to pass uncertainty information; making the interface standards platform independent; extending the range of platforms to include those for high performance computing; developing the concept of modelling components as web services; separating simulation code from the model’s GUI, so that all the results from the linked models can be viewed through a single GUI; developing scenario management systems so that that there is an audit trail of the version of each model and dataset used in each linked model run. In addition to the above, there is a need to build a set of integrated

  19. [Evaluation of the community integration of persons with lateralised post-acute acquired brain injury].

    Science.gov (United States)

    Huertas-Hoyas, E; Pedrero-Perez, E J; Aguila-Maturana, A M; Gonzalez-Alted, C

    2013-08-16

    INTRODUCTION. Hemispheric specialization is a topic of interest that has motivated an enormous amount of research in recent decades. After a unilateral brain injury, the consequences can affect various areas of specialization, leading, depending on the location of the injury, impairment in quality of life and community integration. PATIENTS AND METHODS. Cross-sectional study with a sample of 58 patients, 28 traumatic brain injury (TBI) and 30 cerebrovascular accidents, both lateralized. The level of integration in the community is measured by the Community Integration Questionnaire. RESULTS. There were three groups analyzed by considering unilateral injury (full sample, stroke sample, and TBI sample). Results showed a significantly high community integration of people with right hemisphere injury. However, to measure the level of community integration between TBI and stroke, the results showed no significant differences. CONCLUSION. According to the results of the study people with brain injury in the right hemisphere have a better community integration than people with lesions in the left hemisphere regardless of the origin of the lesions (vascular or traumatic). We discussed the reasons that may motivate the differences and clinical implications.

  20. Learning Computational Models of Video Memorability from fMRI Brain Imaging.

    Science.gov (United States)

    Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

    2015-08-01

    Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

  1. Integrated Model of Bioenergy and Agriculture System

    DEFF Research Database (Denmark)

    Sigurjonsson, Hafthor Ægir; Elmegaard, Brian; Clausen, Lasse Røngaard

    2015-01-01

    Due to increased burden on the environment caused by human activities, focus on industrial ecology designs are gaining more attention. In that perspective an environ- mentally effective integration of bionergy and agriculture systems has significant potential. This work introduces a modeling...... approach that builds on Life Cycle Inventory and carries out Life Cycle Impact Assessment for a con- sequential Life Cycle Assessment on integrated bioenergy and agriculture systems. The model framework is built in Python which connects various freely available soft- ware that handle different aspects...

  2. A Multiscale Model for the Brain Vascular Network

    Science.gov (United States)

    Grinberg, Leopold; Karniadakis, George

    2007-11-01

    Simulations of blood flow in arterial networks requires physiologicaly correct boundary condition at inlets and outlets. Outflow boundary conditions for the Macrovascular Network (MaN) can be imposed by solving a closure problem based on modeling the rest of the flow in ten millions arterioles (Mesovascular Network, MeN) and one billion capillaries (Microvascular Network, MiN). Numerical solution of the three-level MaN-MeN-MiN integration can be performed on the future generation of petaflop supercomputers. An alternative approach for the MaN simulation is to impose the clinically measured flow rates at outlets. We have developed a new method to incorporate such measurements at multiple outlets, it is based on imposing Neumann boundary condition for the velocity and time-dependent resistance boundary conditions for the pressure. The convergence of numerical solution for the outlet flow-rates is achieved immediately. The computational complexity of the method is comparable to the widely used constant pressure boundary condition. Our approach is verified on a model of Brain Vascular Network with tens of arterial segments and outlets.

  3. An integrative model of organizational safety behavior.

    Science.gov (United States)

    Cui, Lin; Fan, Di; Fu, Gui; Zhu, Cherrie Jiuhua

    2013-06-01

    This study develops an integrative model of safety management based on social cognitive theory and the total safety culture triadic framework. The purpose of the model is to reveal the causal linkages between a hazardous environment, safety climate, and individual safety behaviors. Based on primary survey data from 209 front-line workers in one of the largest state-owned coal mining corporations in China, the model is tested using structural equation modeling techniques. An employee's perception of a hazardous environment is found to have a statistically significant impact on employee safety behaviors through a psychological process mediated by the perception of management commitment to safety and individual beliefs about safety. The integrative model developed here leads to a comprehensive solution that takes into consideration the environmental, organizational and employees' psychological and behavioral aspects of safety management. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

  4. Fuzzy object models for newborn brain MR image segmentation

    Science.gov (United States)

    Kobashi, Syoji; Udupa, Jayaram K.

    2013-03-01

    Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

  5. CTBT integrated verification system evaluation model supplement

    Energy Technology Data Exchange (ETDEWEB)

    EDENBURN,MICHAEL W.; BUNTING,MARCUS; PAYNE JR.,ARTHUR C.; TROST,LAWRENCE C.

    2000-03-02

    Sandia National Laboratories has developed a computer based model called IVSEM (Integrated Verification System Evaluation Model) to estimate the performance of a nuclear detonation monitoring system. The IVSEM project was initiated in June 1994, by Sandia's Monitoring Systems and Technology Center and has been funded by the U.S. Department of Energy's Office of Nonproliferation and National Security (DOE/NN). IVSEM is a simple, ''top-level,'' modeling tool which estimates the performance of a Comprehensive Nuclear Test Ban Treaty (CTBT) monitoring system and can help explore the impact of various sensor system concepts and technology advancements on CTBT monitoring. One of IVSEM's unique features is that it integrates results from the various CTBT sensor technologies (seismic, in sound, radionuclide, and hydroacoustic) and allows the user to investigate synergy among the technologies. Specifically, IVSEM estimates the detection effectiveness (probability of detection), location accuracy, and identification capability of the integrated system and of each technology subsystem individually. The model attempts to accurately estimate the monitoring system's performance at medium interfaces (air-land, air-water) and for some evasive testing methods such as seismic decoupling. The original IVSEM report, CTBT Integrated Verification System Evaluation Model, SAND97-25 18, described version 1.2 of IVSEM. This report describes the changes made to IVSEM version 1.2 and the addition of identification capability estimates that have been incorporated into IVSEM version 2.0.

  6. Development of a Model for Whole Brain Learning of Physiology

    Science.gov (United States)

    Eagleton, Saramarie; Muller, Anton

    2011-01-01

    In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed…

  7. Renewed mer model of integral management

    Directory of Open Access Journals (Sweden)

    Janko Belak

    2015-12-01

    Full Text Available Background: The research work on entrepreneurship, enterprise's policy and management, which started in 1992, successfully continued in the following years. Between 1992 and 2011, more than 400 academics and other researchers have participated in research work (MER research program whose main orientation has been the creation of their own model of integral management. Results: In past years, academics (researchers and authors of published papers from Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Byelorussia, Canada, the Czech Republic, Croatia, Estonia, France, Germany, Hungary, Italy, Poland, Romania, Russia, the Slovak Republic, Slovenia, Switzerland, Ukraine, and the US have cooperated in MER programs, coming from more than fifty institutions. Thus, scientific doctrines of different universities influenced the development of the MER model which is based on both horizontal and vertical integration of the enterprises' governance and management processes, instruments and institutions into a consistently operating unit. Conclusions: The presented MER model is based on the multi-layer integration of governance and management with an enterprise and its environment, considering the fundamental desires for the enterprises' existence and, thus, their quantitative as well as qualitative changes. The process, instrumental, and institutional integrity of the governance and management is also the initial condition for the implementation of all other integration factors.

  8. Alteration of blood-brain barrier integrity by retroviral infection.

    Directory of Open Access Journals (Sweden)

    Philippe V Afonso

    2008-11-01

    Full Text Available The blood-brain barrier (BBB, which forms the interface between the blood and the cerebral parenchyma, has been shown to be disrupted during retroviral-associated neuromyelopathies. Human T Lymphotropic Virus (HTLV-1 Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP is a slowly progressive neurodegenerative disease associated with BBB breakdown. The BBB is composed of three cell types: endothelial cells, pericytes and astrocytes. Although astrocytes have been shown to be infected by HTLV-1, until now, little was known about the susceptibility of BBB endothelial cells to HTLV-1 infection and the impact of such an infection on BBB function. We first demonstrated that human cerebral endothelial cells express the receptors for HTLV-1 (GLUT-1, Neuropilin-1 and heparan sulfate proteoglycans, both in vitro, in a human cerebral endothelial cell line, and ex vivo, on spinal cord autopsy sections from HAM/TSP and non-infected control cases. In situ hybridization revealed HTLV-1 transcripts associated with the vasculature in HAM/TSP. We were able to confirm that the endothelial cells could be productively infected in vitro by HTLV-1 and that blocking of either HSPGs, Neuropilin 1 or Glut1 inhibits this process. The expression of the tight-junction proteins within the HTLV-1 infected endothelial cells was altered. These cells were no longer able to form a functional barrier, since BBB permeability and lymphocyte passage through the monolayer of endothelial cells were increased. This work constitutes the first report of susceptibility of human cerebral endothelial cells to HTLV-1 infection, with implications for HTLV-1 passage through the BBB and subsequent deregulation of the central nervous system homeostasis. We propose that the susceptibility of cerebral endothelial cells to retroviral infection and subsequent BBB dysfunction is an important aspect of HAM/TSP pathogenesis and should be considered in the design of future therapeutics strategies.

  9. Image guided constitutive modeling of the silicone brain phantom

    Science.gov (United States)

    Puzrin, Alexander; Skrinjar, Oskar; Ozan, Cem; Kim, Sihyun; Mukundan, Srinivasan

    2005-04-01

    The goal of this work is to develop reliable constitutive models of the mechanical behavior of the in-vivo human brain tissue for applications in neurosurgery. We propose to define the mechanical properties of the brain tissue in-vivo, by taking the global MR or CT images of a brain response to ventriculostomy - the relief of the elevated intracranial pressure. 3D image analysis translates these images into displacement fields, which by using inverse analysis allow for the constitutive models of the brain tissue to be developed. We term this approach Image Guided Constitutive Modeling (IGCM). The presented paper demonstrates performance of the IGCM in the controlled environment: on the silicone brain phantoms closely simulating the in-vivo brain geometry, mechanical properties and boundary conditions. The phantom of the left hemisphere of human brain was cast using silicon gel. An inflatable rubber membrane was placed inside the phantom to model the lateral ventricle. The experiments were carried out in a specially designed setup in a CT scanner with submillimeter isotropic voxels. The non-communicative hydrocephalus and ventriculostomy were simulated by consequently inflating and deflating the internal rubber membrane. The obtained images were analyzed to derive displacement fields, meshed, and incorporated into ABAQUS. The subsequent Inverse Finite Element Analysis (based on Levenberg-Marquardt algorithm) allowed for optimization of the parameters of the Mooney-Rivlin non-linear elastic model for the phantom material. The calculated mechanical properties were consistent with those obtained from the element tests, providing justification for the future application of the IGCM to in-vivo brain tissue.

  10. Integration of thermophysiological body model in CFD

    Science.gov (United States)

    Pichurov, George; Stankov, Peter

    2013-09-01

    A two-node mathematical model of the human thermophysiological system has been integrated into a Computational Fluid Dynamic (CFD) simulation of the airflow in a room. Temperature inputs from the CFD are used by the model to evaluate the dry and latent heat flux from the body surface and output them as boundary conditions. This is an iterative process and convergence is ensured by under-relaxation of the latent heat flux. The model also considers the dry and latent heat resistance of clothing. Numerical predictions of the body heat loss and airflow are compared against physical measurements in a climate chamber. Good agreement was observed when using the low Reynolds number turbulence model. The integrated simulation performs well under wide set of conditions, predicting body core and skin temperature, blood flow, skin wittedness, as well as the transfer of heat and moisture released by the body into the room.

  11. Which coordinate system for modelling path integration?

    Science.gov (United States)

    Vickerstaff, Robert J; Cheung, Allen

    2010-03-21

    Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate, called the home vector, of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature, and has been studied for over a century. In that time, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural representation of space needed for biological path integration. This paper presents a scheme to classify path integration systems on the basis of the way the home vector records and updates the spatial relationship between the animal and its home location. Four extended classes of coordinate systems are used to unify and review both canonical and neural network models of path integration, from the arthropod and mammalian literature. This scheme demonstrates analytical equivalence between models which may otherwise appear unrelated, and distinguishes between models which may superficially appear similar. A thorough analysis is carried out of the equational forms of important facets of path integration including updating, steering, searching and systematic errors, using each of the four coordinate systems. The type of available directional cue, namely allothetic or idiothetic, is also considered. It is shown that on balance, the class of home vectors which includes the geocentric Cartesian coordinate system, appears to be the most robust for biological systems. A key conclusion is that deducing computational structure from behavioural data alone will be difficult or impossible, at least in the absence of an analysis of random errors. Consequently it is likely that further theoretical insights into path integration will require an in-depth study of the effect of noise on the four classes of home vectors. Copyright 2009 Elsevier Ltd

  12. Integrated modelling of two xenobiotic organic compounds

    DEFF Research Database (Denmark)

    Lindblom, Erik Ulfson; Gernaey, K.V.; Henze, Mogens

    2006-01-01

    This paper presents a dynamic mathematical model that describes the fate and transport of two selected xenobiotic organic compounds (XOCs) in a simplified representation. of an integrated urban wastewater system. A simulation study, where the xenobiotics bisphenol A and pyrene are used as reference...

  13. Fingernail Injuries and NASA's Integrated Medical Model

    Science.gov (United States)

    Kerstman, Eric; Butler, Doug

    2008-01-01

    The goal of space medicine is to optimize both crew health and performance. Currently, expert opinion is primarily relied upon for decision-making regarding medical equipment and supplies flown in space. Evidence-based decisions are preferred due to mass and volume limitations and the expense of space flight. The Integrated Medical Model (IMM) is an attempt to move us in that direction!

  14. Rethinking School Bullying: Towards an Integrated Model

    Science.gov (United States)

    Dixon, Roz; Smith, Peter K.

    2011-01-01

    What would make anti-bullying initiatives more successful? This book offers a new approach to the problem of school bullying. The question of what constitutes a useful theory of bullying is considered and suggestions are made as to how priorities for future research might be identified. The integrated, systemic model of school bullying introduced…

  15. Accurate Electromagnetic Modeling Methods for Integrated Circuits

    NARCIS (Netherlands)

    Sheng, Z.

    2010-01-01

    The present development of modern integrated circuits (IC’s) is characterized by a number of critical factors that make their design and verification considerably more difficult than before. This dissertation addresses the important questions of modeling all electromagnetic behavior of features on

  16. Towards an Integrative Model of Knowledge Transfer

    DEFF Research Database (Denmark)

    Turcan, Romeo V.; Heslop, Ben

    This paper aims to contribute towards the advancement of an efficient architecture of a single market for knowledge through the development of an integrative model of knowledge transfer. Within this aim, several points of departure can be singled out. One, the article builds on the call of the Eu......This paper aims to contribute towards the advancement of an efficient architecture of a single market for knowledge through the development of an integrative model of knowledge transfer. Within this aim, several points of departure can be singled out. One, the article builds on the call...... and (iii) the meaning/reality that is construed as a result of these relationships. To address the above research objectives, grounded theory research was undertaken in four universities in the UK and one in Australia. Coding of the data revealed thirteen constructs, which became the building blocks...... of the emergent integrative model of knowledge transfer. In an attempt to bring it to a higher level of generalizability, the integrative model of KT is further conceptualized from a ‘sociology of markets’ perspective resulting in an emergent architecture of a single market for knowledge. Future research...

  17. Systems biology and integrative physiological modelling.

    Science.gov (United States)

    Hester, Robert L; Iliescu, Radu; Summers, Richard; Coleman, Thomas G

    2011-03-01

    Over the last 10 years, 'Systems Biology' has focused on the integration of biology and medicine with information technology and computation. The current challenge is to use the discoveries of the last 20 years, such as genomics and proteomics, to develop targeted therapeutical strategies. These strategies are the result of understanding the aetiologies of complex diseases. Scientists predict the data will make personalized medicine rapidly available. However, the data need to be considered as a highly complex system comprising multiple inputs and feedback mechanisms. Translational medicine requires the functional and conceptual linkage of genetics to proteins, proteins to cells, cells to organs, organs to systems and systems to the organism. To help understand the complex integration of these systems, a mathematical model of the entire human body, which accurately links the functioning of all organs and systems together, could provide a framework for the development and testing of new hypotheses that will be important in clinical outcomes. There are several efforts to develop a 'Human Physiome', with the strengths and weaknesses of each being presented here. The development of a 'Human Model', with verification, documentation and validation of the underlying and integrative responses, is essential to provide a usable environment. Future development of a 'Human Model' requires integrative physiologists working in collaboration with other scientists, who have expertise in all areas of human biology, to develop the most accurate and usable human model.

  18. In vivo modeling and molecular characterization: a path towards targeted therapy of melanoma brain metastasis

    Directory of Open Access Journals (Sweden)

    Avital eGaziel-Sovran

    2013-05-01

    Full Text Available Brain metastasis from melanoma remains mostly incurable and the main cause of death from the disease. Early stage clinical trials and case studies show some promise for targeted therapies in the treatment of melanoma brain metastasis. However, the progression-free survival for currently available therapies, although significantly improved, is still very short. The development of new potent agents to eradicate melanoma brain metastasis relies on the elucidation of the molecular mechanisms that drive melanoma cells to reach and colonize the brain. The discovery of such mechanisms depends heavily on pre-clinical models that enable the testing of candidate factors and therapeutic agents in vivo. In this review we summarize the effects of available targeted therapies on melanoma brain metastasis in the clinic. We provide an overview of existing pre-clinical models to study the disease and discuss specific molecules and mechanisms reported to modulate different aspects of melanoma brain metastasis and finally, by integrating both clinical and basic data, we summarize both opportunities and challenges currently presented to researchers in the field.

  19. A family of hyperelastic models for human brain tissue

    Science.gov (United States)

    Mihai, L. Angela; Budday, Silvia; Holzapfel, Gerhard A.; Kuhl, Ellen; Goriely, Alain

    2017-09-01

    Experiments on brain samples under multiaxial loading have shown that human brain tissue is both extremely soft when compared to other biological tissues and characterized by a peculiar elastic response under combined shear and compression/tension: there is a significant increase in shear stress with increasing axial compression compared to a moderate increase with increasing axial tension. Recent studies have revealed that many widely used constitutive models for soft biological tissues fail to capture this characteristic response. Here, guided by experiments of human brain tissue, we develop a family of modeling approaches that capture the elasticity of brain tissue under varying simple shear superposed on varying axial stretch by exploiting key observations about the behavior of the nonlinear shear modulus, which can be obtained directly from the experimental data.

  20. Exposure to lipopolysaccharide and/or unconjugated bilirubin impair the integrity and function of brain microvascular endothelial cells.

    Science.gov (United States)

    Cardoso, Filipa L; Kittel, Agnes; Veszelka, Szilvia; Palmela, Inês; Tóth, Andrea; Brites, Dora; Deli, Mária A; Brito, Maria A

    2012-01-01

    Sepsis and jaundice are common conditions in newborns that can lead to brain damage. Though lipopolysaccharide (LPS) is known to alter the integrity of the blood-brain barrier (BBB), little is known on the effects of unconjugated bilirubin (UCB) and even less on the joint effects of UCB and LPS on brain microvascular endothelial cells (BMEC). Monolayers of primary rat BMEC were treated with 1 µg/ml LPS and/or 50 µM UCB, in the presence of 100 µM human serum albumin, for 4 or 24 h. Co-cultures of BMEC with astroglial cells, a more complex BBB model, were used in selected experiments. LPS led to apoptosis and UCB induced both apoptotic and necrotic-like cell death. LPS and UCB led to inhibition of P-glycoprotein and activation of matrix metalloproteinases-2 and -9 in mono-cultures. Transmission electron microscopy evidenced apoptotic bodies, as well as damaged mitochondria and rough endoplasmic reticulum in BMEC by either insult. Shorter cell contacts and increased caveolae-like invaginations were noticeable in LPS-treated cells and loss of intercellular junctions was observed upon treatment with UCB. Both compounds triggered impairment of endothelial permeability and transendothelial electrical resistance both in mono- and co-cultures. The functional changes were confirmed by alterations in immunostaining for junctional proteins β-catenin, ZO-1 and claudin-5. Enlargement of intercellular spaces, and redistribution of junctional proteins were found in BMEC after exposure to LPS and UCB. LPS and/or UCB exert direct toxic effects on BMEC, with distinct temporal profiles and mechanisms of action. Therefore, the impairment of brain endothelial integrity upon exposure to these neurotoxins may favor their access to the brain, thus increasing the risk of injury and requiring adequate clinical management of sepsis and jaundice in the neonatal period.

  1. Nonlinear integral equations for the sausage model

    Science.gov (United States)

    Ahn, Changrim; Balog, Janos; Ravanini, Francesco

    2017-08-01

    The sausage model, first proposed by Fateev, Onofri, and Zamolodchikov, is a deformation of the O(3) sigma model preserving integrability. The target space is deformed from the sphere to ‘sausage’ shape by a deformation parameter ν. This model is defined by a factorizable S-matrix which is obtained by deforming that of the O(3) sigma model by a parameter λ. Clues for the deformed sigma model are provided by various UV and IR information through the thermodynamic Bethe ansatz (TBA) analysis based on the S-matrix. Application of TBA to the sausage model is, however, limited to the case of 1/λ integer where the coupled integral equations can be truncated to a finite number. In this paper, we propose a finite set of nonlinear integral equations (NLIEs), which are applicable to generic value of λ. Our derivation is based on T-Q relations extracted from the truncated TBA equations. For a consistency check, we compute next-leading order corrections of the vacuum energy and extract the S-matrix information in the IR limit. We also solved the NLIE both analytically and numerically in the UV limit to get the effective central charge and compared with that of the zero-mode dynamics to obtain exact relation between ν and λ. Dedicated to the memory of Petr Petrovich Kulish.

  2. Integrated and Contextual Basic Science Instruction in Preclinical Education: Problem-Based Learning Experience Enriched with Brain/Mind Learning Principles

    Science.gov (United States)

    Gülpinar, Mehmet Ali; Isoglu-Alkaç, Ümmühan; Yegen, Berrak Çaglayan

    2015-01-01

    Recently, integrated and contextual learning models such as problem-based learning (PBL) and brain/mind learning (BML) have become prominent. The present study aimed to develop and evaluate a PBL program enriched with BML principles. In this study, participants were 295 first-year medical students. The study used both quantitative and qualitative…

  3. How the brain integrates costs and benefits during decision making

    NARCIS (Netherlands)

    Basten, U.; Biele, G.; Heekeren, H.R.; Fiebach, C.J.

    2010-01-01

    When we make decisions, the benefits of an option often need to be weighed against accompanying costs. Little is known, however, about the neural systems underlying such cost-benefit computations. Using functional magnetic resonance imaging and choice modeling, we show that decision making based on

  4. Application of Texture Analysis to Study Small Vessel Disease and Blood–Brain Barrier Integrity

    Directory of Open Access Journals (Sweden)

    Maria del C. Valdés Hernández

    2017-07-01

    Full Text Available ObjectivesWe evaluate the alternative use of texture analysis for evaluating the role of blood–brain barrier (BBB in small vessel disease (SVD.MethodsWe used brain magnetic resonance imaging from 204 stroke patients, acquired before and 20 min after intravenous gadolinium administration. We segmented tissues, white matter hyperintensities (WMH and applied validated visual scores. We measured textural features in all tissues pre- and post-contrast and used ANCOVA to evaluate the effect of SVD indicators on the pre-/post-contrast change, Kruskal–Wallis for significance between patient groups and linear mixed models for pre-/post-contrast variations in cerebrospinal fluid (CSF with Fazekas scores.ResultsTextural “homogeneity” increase in normal tissues with higher presence of SVD indicators was consistently more overt than in abnormal tissues. Textural “homogeneity” increased with age, basal ganglia perivascular spaces scores (p < 0.01 and SVD scores (p < 0.05 and was significantly higher in hypertensive patients (p < 0.002 and lacunar stroke (p = 0.04. Hypertension (74% patients, WMH load (median = 1.5 ± 1.6% of intracranial volume, and age (mean = 65.6 years, SD = 11.3 predicted the pre/post-contrast change in normal white matter, WMH, and index stroke lesion. CSF signal increased with increasing SVD post-contrast.ConclusionA consistent general pattern of increasing textural “homogeneity” with increasing SVD and post-contrast change in CSF with increasing WMH suggest that texture analysis may be useful for the study of BBB integrity.

  5. Animal models and integrated nested Laplace approximations.

    Science.gov (United States)

    Holand, Anna Marie; Steinsland, Ingelin; Martino, Sara; Jensen, Henrik

    2013-08-07

    Animal models are generalized linear mixed models used in evolutionary biology and animal breeding to identify the genetic part of traits. Integrated Nested Laplace Approximation (INLA) is a methodology for making fast, nonsampling-based Bayesian inference for hierarchical Gaussian Markov models. In this article, we demonstrate that the INLA methodology can be used for many versions of Bayesian animal models. We analyze animal models for both synthetic case studies and house sparrow (Passer domesticus) population case studies with Gaussian, binomial, and Poisson likelihoods using INLA. Inference results are compared with results using Markov Chain Monte Carlo methods. For model choice we use difference in deviance information criteria (DIC). We suggest and show how to evaluate differences in DIC by comparing them with sampling results from simulation studies. We also introduce an R package, AnimalINLA, for easy and fast inference for Bayesian Animal models using INLA.

  6. Modeling and analysis of extracellular field potentials in the brain

    OpenAIRE

    Lindén, Henrik

    2010-01-01

    In order to model processes occuring in the brain it is necessary to have reliable measures of neural activity, with a clear intepretation rooted in the biophysics of the neural tissue. One of the most important probes of neural activity is the measurement of extracellular field potentials. The potential picked up by an electrode placed inside the brain is typically filtered in to two distinct frequency bands: the high-frequency part (>500 Hz) captures the spiking output of nearby cells (term...

  7. Spatio-temporal modeling of connectome-scale brain network interactions via time-evolving graphs.

    Science.gov (United States)

    Yuan, Jing; Li, Xiang; Zhang, Jinhe; Luo, Liao; Dong, Qinglin; Lv, Jinglei; Zhao, Yu; Jiang, Xi; Zhang, Shu; Zhang, Wei; Liu, Tianming

    2017-11-09

    Many recent literature studies have revealed interesting dynamics patterns of functional brain networks derived from fMRI data. However, it has been rarely explored how functional networks spatially overlap (or interact) and how such connectome-scale network interactions temporally evolve. To explore these unanswered questions, this paper presents a novel framework for spatio-temporal modeling of connectome-scale functional brain network interactions via two main effective computational methodologies. First, to integrate, pool and compare brain networks across individuals and their cognitive states under task performances, we designed a novel group-wise dictionary learning scheme to derive connectome-scale consistent brain network templates that can be used to define the common reference space of brain network interactions. Second, the temporal dynamics of spatial network interactions is modeled by a weighted time-evolving graph, and then a data-driven unsupervised learning algorithm based on the dynamic behavioral mixed-membership model (DBMM) is adopted to identify behavioral patterns of brain networks during the temporal evolution process of spatial overlaps/interactions. Experimental results on the Human Connectome Project (HCP) task fMRI data showed that our methods can reveal meaningful, diverse behavior patterns of connectome-scale network interactions. In particular, those networks' behavior patterns are distinct across HCP tasks such as motor, working memory, language and social tasks, and their dynamics well correspond to the temporal changes of specific task designs. In general, our framework offers a new approach to characterizing human brain function by quantitative description for the temporal evolution of spatial overlaps/interactions of connectome-scale brain networks in a standard reference space. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Multi-Scale Computational Models for Electrical Brain Stimulation

    Science.gov (United States)

    Seo, Hyeon; Jun, Sung C.

    2017-01-01

    Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed. PMID:29123476

  9. Model of brain activation predicts the neural collective influence map of the brain.

    Science.gov (United States)

    Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Stanley, H Eugene; Makse, Hernán A

    2017-04-11

    Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory.

  10. Evidence of altered DNA integrity in the brain regions of suicidal victims of Bipolar Depression.

    Science.gov (United States)

    Mustak, Mohammed S; Hegde, Muralidhar L; Dinesh, Athira; Britton, Gabrielle B; Berrocal, Ruben; Subba Rao, K; Shamasundar, N M; Rao, K S J; Sathyanarayana Rao, T S

    2010-07-01

    Deoxyribonucleic acid (DNA) integrity plays a significant role in cell function. There are limited studies with regard to the role of DNA damage in bipolar affective disorder (BP). In the present study, we have assessed DNA integrity, conformation, and stability in the brain region of bipolar depression (BD) patients (n=10) compared to age-matched controls (n=8). Genomic DNA was isolated from 10 postmortem BD patients' brain regions (frontal cortex, Pons, medulla, thalamus, cerebellum, hypothalamus, Parietal, temporal, occipital lobe, and hippocampus) and from the age-matched control subjects. DNA from the frontal cortex, pons, medulla, and thalamus showed significantly higher number of strand breaks in BD (P<0.01) compared to the age-matched controls. However, DNA from the hippocampus region was intact and did not show any strand breaks. The stability studies also indicated that the melting temperature and ethidium bromide binding pattern were altered in the DNA of BD patients' brain regions, except in the hippocampus. The conformation studies showed B-A or secondary B-DNA conformation (instead of the normal B-DNA) in BD patients' brain regions, with the exception of the hippocampus. The levels of redox metals such as Copper (Cu) and Iron (Fe) were significantly elevated in the brain regions of the sufferers of BD, while the Zinc (Zn) level was decreased. In the hippocampus, there was no change in the Fe or Cu levels, whereas, the Zn level was elevated. There was a clear correlation between Cu and Fe levels versus strand breaks in the brain regions of the BD. To date, as far as we are aware, this is a new comprehensive database on stability and conformations of DNA in different brain regions of patients affected with BD. The biological significance of these findings is discussed here.

  11. Paradox of integration-A computational model

    Science.gov (United States)

    Krawczyk, Małgorzata J.; Kułakowski, Krzysztof

    2017-02-01

    The paradoxical aspect of integration of a social group has been highlighted by Blau (1964). During the integration process, the group members simultaneously compete for social status and play the role of the audience. Here we show that when the competition prevails over the desire of approval, a sharp transition breaks all friendly relations. However, as was described by Blau, people with high status are inclined to bother more with acceptance of others; this is achieved by praising others and revealing her/his own weak points. In our model, this action smooths the transition and improves interpersonal relations.

  12. Development of the Integrated Environmental Control Model

    Energy Technology Data Exchange (ETDEWEB)

    Rubin, E.S.; Berkenpas, M.B.; Kalagnanam, J.

    1993-04-01

    The purpose of this contract is to develop and refine the Integrated Environmental Control Model (IECM) created and enhanced by Carnegie Mellon University (CMU) for the US Department of Energy's Pittsburgh Energy Technology Center (DOE/PETC) under contract Numbers FG22-83PC60271 and AC22-87PC79864. In its current configuration, the IECM provides a capability to model various conventional and advanced processes for controlling air pollutant emissions from coal-fired power plants before, during, or after combustion. The principal purpose of the model is to calculate the performance, emissions, and cost of power plant configurations employing alternative environmental control methods. The model consists of various control technology modules, which may be integrated into a complete utility plant in any desired combination. In contrast to conventional deterministic models, the IECM offers the unique capability to assign probabilistic values to all model input parameters, and to obtain probabilistic outputs in the form of cumulative distribution functions indicating the likelihood of different costs and performance results. The work in this contract is divided into two phases. Phase I deals with further developing the existing version of the IECM and training PETC personnel on the effective use of the model. Phase II deals with creating new technology modules, linking the IECM with PETC databases, and training PETC personnel on the effective use of the updated model.

  13. Planarian shows decision-making behavior in response to multiple stimuli by integrative brain function.

    Science.gov (United States)

    Inoue, Takeshi; Hoshino, Hajime; Yamashita, Taiga; Shimoyama, Seira; Agata, Kiyokazu

    2015-01-01

    Planarians belong to an evolutionarily early group of organisms that possess a central nervous system including a well-organized brain with a simple architecture but many types of neurons. Planarians display a number of behaviors, such as phototaxis and thermotaxis, in response to external stimuli, and it has been shown that various molecules and neural pathways in the brain are involved in controlling these behaviors. However, due to the lack of combinatorial assay methods, it remains obscure whether planarians possess higher brain functions, including integration in the brain, in which multiple signals coming from outside are coordinated and used in determining behavioral strategies. In the present study, we designed chemotaxis and thigmotaxis/kinesis tracking assays to measure several planarian behaviors in addition to those measured by phototaxis and thermotaxis assays previously established by our group, and used these tests to analyze planarian chemotactic and thigmotactic/kinetic behaviors. We found that headless planarian body fragments and planarians that had specifically lost neural activity following regeneration-dependent conditional gene knockdown (Readyknock) of synaptotagmin in the brain lost both chemotactic and thigmotactic behaviors, suggesting that neural activity in the brain is required for the planarian's chemotactic and thigmotactic behaviors. Furthermore, we compared the strength of phototaxis, chemotaxis, thigmotaxis/kinesis, and thermotaxis by presenting simultaneous binary stimuli to planarians. We found that planarians showed a clear order of predominance of these behaviors. For example, when planarians were simultaneously exposed to 400 lux of light and a chemoattractant, they showed chemoattractive behavior irrespective of the direction of the light source, although exposure to light of this intensity alone induces evasive behavior away from the light source. In contrast, when the light intensity was increased to 800 or 1600 lux and

  14. Integrated Process Model on Intercultural Competence

    Directory of Open Access Journals (Sweden)

    Diana Bebenova - Nikolova

    2016-08-01

    Full Text Available The paper proposes an integrated model on intercultural competence, which attempts to present intercultural communication and competence from the term point of the dialectical approach, described by Martin and Nakayama (2010. The suggested concept deploys from previously developed and accepted models, both structure-oriented and process-oriented. At the same time it replies to the principles of the “Theory of Models” as outlined by Balboni and Caon (2014. In the near future, the model will be applied to assess intercultural competence of cross-border project teams, working under the CBC program between Romania – Bulgaria 2007-2014.

  15. Beyond neural cubism: promoting a multidimensional view of brain disorders by enhancing the integration of neurology and psychiatry in education.

    Science.gov (United States)

    Taylor, Joseph J; Williams, Nolan R; George, Mark S

    2015-05-01

    Cubism was an influential early-20th-century art movement characterized by angular, disjointed imagery. The two-dimensional appearance of Cubist figures and objects is created through juxtaposition of angles. The authors posit that the constrained perspectives found in Cubism may also be found in the clinical classification of brain disorders. Neurological disorders are often separated from psychiatric disorders as if they stemmed from different organ systems. Maintaining two isolated clinical disciplines fractionalizes the brain in the same way that Pablo Picasso fractionalized figures and objects in his Cubist art. This Neural Cubism perpetuates a clinical divide that does not reflect the scope and depth of neuroscience. All brain disorders are complex and multidimensional, with aberrant circuitry and resultant psychopharmacology manifesting as altered behavior, affect, mood, or cognition. Trainees should receive a multidimensional education based on modern neuroscience, not a partial education based on clinical precedent. The authors briefly outline the rationale for increasing the integration of neurology and psychiatry and discuss a nested model with which clinical neuroscientists (neurologists and psychiatrists) can approach and treat brain disorders.

  16. Beyond Neural Cubism: Promoting a Multidimensional View of Brain Disorders by Enhancing the Integration of Neurology and Psychiatry in Education

    Science.gov (United States)

    Taylor, Joseph J.; Williams, Nolan R.; George, Mark S.

    2014-01-01

    Cubism was an influential early 20th century art movement characterized by angular, disjointed imagery. The two-dimensional appearance of Cubist figures and objects is created through juxtaposition of angles. The authors posit that the constrained perspectives found in Cubism may also be found in the clinical classification of brain disorders. Neurological disorders are often separated from psychiatric disorders as if they stem from different organ systems. Maintaining two isolated clinical disciplines fractionalizes the brain in the same way that Pablo Picasso fractionalized figures and objects in his Cubist art. This Neural Cubism perpetuates a clinical divide that does not reflect the scope and depth of neuroscience. All brain disorders are complex and multidimensional, with aberrant circuitry and resultant psychopharmacology manifesting as altered behavior, affect, mood or cognition. Trainees should receive a multidimensional education based on modern neuroscience, not a partial education based on clinical precedent. The authors briefly outline the rationale for increasing the integration of neurology and psychiatry and discuss a nested model with which clinical neuroscientists (neurologists and psychiatrists) can approach and treat brain disorders. PMID:25340364

  17. An Integrative Model of Internationalization Strategies

    DEFF Research Database (Denmark)

    Li, Xin; Gammelgaard, Jens

    2012-01-01

    This paper critically reviews the ownership, location, and internalization (OLI) model, and the Uppsala internationalization process (UIP) framework. Both the OLI model and the UIP model ignore to incorporate the insights of each other and fail to include corporate entrepreneurship in their analy......This paper critically reviews the ownership, location, and internalization (OLI) model, and the Uppsala internationalization process (UIP) framework. Both the OLI model and the UIP model ignore to incorporate the insights of each other and fail to include corporate entrepreneurship...... in their analyses. We argue that regulatory focus theory can unify the managerial choice of internationalization between internalization and networking. In addition, host country institutions affect this managerial choice with regard to internationalization. Thus, we suggest that the inclusion of concepts...... such as corporate entrepreneurship, institutional environment, and regulatory focus in an integrated framework helps to explain firm internationalization....

  18. Dynamic causal modelling of brain-behaviour relationships.

    Science.gov (United States)

    Rigoux, L; Daunizeau, J

    2015-08-15

    In this work, we expose a mathematical treatment of brain-behaviour relationships, which we coin behavioural Dynamic Causal Modelling or bDCM. This approach aims at decomposing the brain's transformation of stimuli into behavioural outcomes, in terms of the relative contribution of brain regions and their connections. In brief, bDCM places the brain at the interplay between stimulus and behaviour: behavioural outcomes arise from coordinated activity in (hidden) neural networks, whose dynamics are driven by experimental inputs. Estimating neural parameters that control network connectivity and plasticity effectively performs a neurobiologically-constrained approximation to the brain's input-outcome transform. In other words, neuroimaging data essentially serves to enforce the realism of bDCM's decomposition of input-output relationships. In addition, post-hoc artificial lesions analyses allow us to predict induced behavioural deficits and quantify the importance of network features for funnelling input-output relationships. This is important, because this enables one to bridge the gap with neuropsychological studies of brain-damaged patients. We demonstrate the face validity of the approach using Monte-Carlo simulations, and its predictive validity using empirical fMRI/behavioural data from an inhibitory control task. Lastly, we discuss promising applications of this work, including the assessment of functional degeneracy (in the healthy brain) and the prediction of functional recovery after lesions (in neurological patients). Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Dual integral porosity shallow water model for urban flood modelling

    Science.gov (United States)

    Guinot, Vincent; Sanders, Brett F.; Schubert, Jochen E.

    2017-05-01

    With CPU times 2 to 3 orders of magnitude smaller than classical shallow water-based models, the shallow water equations with porosity are a promising tool for large-scale modelling of urban floods. In this paper, a new model formulation called the Dual Integral Porosity (DIP) model is presented and examined analytically and computationally with a series of benchmark tests. The DIP model is established from an integral mass and momentum balance whereby both porosity and flow variables are defined separately for control volumes and boundaries, and a closure scheme is introduced to link control volume- and boundary-based flow variables. Previously developed Integral Porosity (IP) models were limited to a single set of flow variables. A new transient momentum dissipation model is also introduced to account for the effects of sub-grid scale wave action on porosity model solutions, effects which are validated by fine-grid solutions of the classical shallow-water equations and shown to be important for achieving similarity in dam-break solutions. One-dimensional numerical test cases show that the proposed DIP model outperforms the IP model, with significantly improved wave propagation speeds, water depths and discharge calculations. A two-dimensional field scale test case shows that the DIP model performs better than the IP model in mapping the floods extent and is slightly better in reproducing the anisotropy of the flow field when momentum dissipation parameters are calibrated.

  20. A mechanical model predicts morphological abnormalities in the developing human brain

    Science.gov (United States)

    Budday, Silvia; Raybaud, Charles; Kuhl, Ellen

    2014-07-01

    The developing human brain remains one of the few unsolved mysteries of science. Advancements in developmental biology, neuroscience, and medical imaging have brought us closer than ever to understand brain development in health and disease. However, the precise role of mechanics throughout this process remains underestimated and poorly understood. Here we show that mechanical stretch plays a crucial role in brain development. Using the nonlinear field theories of mechanics supplemented by the theory of finite growth, we model the human brain as a living system with a morphogenetically growing outer surface and a stretch-driven growing inner core. This approach seamlessly integrates the two popular but competing hypotheses for cortical folding: axonal tension and differential growth. We calibrate our model using magnetic resonance images from very preterm neonates. Our model predicts that deviations in cortical growth and thickness induce morphological abnormalities. Using the gyrification index, the ratio between the total and exposed surface area, we demonstrate that these abnormalities agree with the classical pathologies of lissencephaly and polymicrogyria. Understanding the mechanisms of cortical folding in the developing human brain has direct implications in the diagnostics and treatment of neurological disorders, including epilepsy, schizophrenia, and autism.

  1. Regional mechanical properties of human brain tissue for computational models of traumatic brain injury.

    Science.gov (United States)

    Finan, John D; Sundaresh, Sowmya N; Elkin, Benjamin S; McKhann, Guy M; Morrison, Barclay

    2017-06-01

    To determine viscoelastic shear moduli, stress relaxation indentation tests were performed on samples of human brain tissue resected in the course of epilepsy surgery. Through the use of a 500µm diameter indenter, regional mechanical properties were measured in cortical grey and white matter and subregions of the hippocampus. All regions were highly viscoelastic. Cortical grey matter was significantly more compliant than the white matter or hippocampus which were similar in modulus. Although shear modulus was not correlated with the age of the donor, cortex from male donors was significantly stiffer than from female donors. The presented material properties will help to populate finite element models of the brain as they become more anatomically detailed. We present the first mechanical characterization of fresh, post-operative human brain tissue using an indentation loading mode. Indentation generates highly localized data, allowing structure-specific mechanical properties to be determined from small tissue samples resected during surgery. It also avoids pitfalls of cadaveric tissue and allows data to be collected before degenerative processes alter mechanical properties. To correctly predict traumatic brain injury, finite element models must calculate intracranial deformation during head impact. The functional consequences of injury depend on the anatomical structures injured. Therefore, morbidity depends on the distribution of deformation across structures. Accurate prediction of structure-specific deformation requires structure-specific mechanical properties. This data will facilitate deeper understanding of the physical mechanisms that lead to traumatic brain injury. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  2. CTBT Integrated Verification System Evaluation Model

    Energy Technology Data Exchange (ETDEWEB)

    Edenburn, M.W.; Bunting, M.L.; Payne, A.C. Jr.

    1997-10-01

    Sandia National Laboratories has developed a computer based model called IVSEM (Integrated Verification System Evaluation Model) to estimate the performance of a nuclear detonation monitoring system. The IVSEM project was initiated in June 1994, by Sandia`s Monitoring Systems and Technology Center and has been funded by the US Department of Energy`s Office of Nonproliferation and National Security (DOE/NN). IVSEM is a simple, top-level, modeling tool which estimates the performance of a Comprehensive Nuclear Test Ban Treaty (CTBT) monitoring system and can help explore the impact of various sensor system concepts and technology advancements on CTBT monitoring. One of IVSEM`s unique features is that it integrates results from the various CTBT sensor technologies (seismic, infrasound, radionuclide, and hydroacoustic) and allows the user to investigate synergy among the technologies. Specifically, IVSEM estimates the detection effectiveness (probability of detection) and location accuracy of the integrated system and of each technology subsystem individually. The model attempts to accurately estimate the monitoring system`s performance at medium interfaces (air-land, air-water) and for some evasive testing methods such as seismic decoupling. This report describes version 1.2 of IVSEM.

  3. Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction.

    Directory of Open Access Journals (Sweden)

    Zude Zhu

    Full Text Available While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25-75 year-old adults read sentences with high cloze (HC and low cloze (LC probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC was found in several regions, especially the left middle frontal gyrus (MFG and right inferior frontal gyrus (IFG, which play an important role in semantic integration. Moreover, when accounting for global gray matter volume reduction, the age-cloze correlation in the left MFG and right IFG was absent. The results suggest that brain structural atrophy may disrupt brain response in aging brains, which then show less brain engagement in semantic integration.

  4. Organization, maturation and plasticity of multisensory integration: Insights from computational modelling studies

    Directory of Open Access Journals (Sweden)

    Cristiano eCuppini

    2011-05-01

    Full Text Available In this paper, we present two neural network models - devoted to two specific and widely investigated aspects of multisensory integration - in order to evidence the potentialities of computational models to gain insight into the neural mechanisms underlying organization, development and plasticity of multisensory integration in the brain. The first model considers visual-auditory interaction in a midbrain structure named Superior Colliculus (SC. The model is able to reproduce and explain the main physiological features of multisensory integration in SC neurons and to describe how SC integrative capability – not present at birth - develops gradually during postnatal life depending on sensory experience with cross-modal stimuli. The second model tackles the problem of how tactile stimuli on a body part and visual (or auditory stimuli close to the same body part are integrated in multimodal parietal neurons to form the perception of peripersonal (i.e., near space. The model investigates how the extension of peripersonal space - where multimodal integration occurs - may be modified by experience such as use of a tool to interact with the far space. The utility of the modelling approach relies on several aspects: i The two models, although devoted to different problems and simulating different brain regions, share some common mechanisms (lateral inhibition and excitation, non-linear neuron characteristics, recurrent connections, competition, Hebbian rules of potentiation and depression that may govern more generally the fusion of senses in the brain, and the learning and plasticity of multisensory integration. ii The models may help interpretation of behavioural and psychophysical responses in terms of neural activity and synaptic connections. iii The models can make testable predictions that can help guiding future experiments in order to validate, reject, or modify the main assumptions.

  5. Misconceptions and Misattributions About Traumatic Brain Injury: An Integrated Conceptual Framework.

    Science.gov (United States)

    Block, Cady K; West, Sarah E; Goldin, Yelena

    2016-01-01

    The objective of the present narrative review was to provide a conceptual framework to address common misconceptions in the field of traumatic brain injury (TBI) and enhance clinical and research practices. This framework is based on review of the literature on TBI knowledge and beliefs. The comprehensive search of the literature included seminal and current texts as well as relevant articles on TBI knowledge and education, misconceptions, and misattributions. Reviewed materials ranged from 1970 to 2013 and were obtained from PubMed and PubMed Central online research databases. Research findings from the reviewed literature were integrated with existing social and cognitive psychological concepts to develop a framework that includes: (1) the identification antecedents of TBI-related misconceptions and misattribution; (2) understanding of how inaccurate beliefs form and persist as the result of pre- and postinjury cognitive operations such as informational cascades and attribution biases; and (3) a discussion of ways in which these beliefs can result in consequences in all domains of a survivor's life, including physical and mental health, stigma, and discrimination. This framework is intended to serve as a first stage of development of a model that will improve treatment endeavors and service delivery to individuals with TBI and their families. Copyright © 2016 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

  6. Evaluation of cat brain infarction model using microPET

    Energy Technology Data Exchange (ETDEWEB)

    Lee, J. J.; Lee, D. S.; Kim, J. H.; Hwang, D. W.; Jung, J. G.; Lee, M. C [College of Medicine, Seoul National University, Seoul (Korea, Republic of); Lim, S. M [Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2004-07-01

    PET has some disadvantage in the imaging of small animal due to poor resolution. With the advance of microPET scanner, it is possible to image small animals. However, the image quality was not so much satisfactory as human image. As cats have relatively large sized brain, cat brain imaging was superior to mice or rat. In this study, we established the cat brain infarction model and evaluate it and its temporal change using microPET scanner. Two adult male cats were used. Anesthesia was done with xylazine and ketamine HCl. A burr hole was made at 1cm right lateral to the bregma. Collagenase type IV 10 ul was injected using 30G needle for 5 minutes to establish the infarction model. F-18 FDG microPET (Concorde Microsystems Inc., Knoxville. TN) scans were performed 1. 11 and 32 days after the infarction. In addition. 18F-FDG PET scans were performed using Gemini PET scanner (Philips medical systems. CA, USA) 13 and 47 days after the infarction. Two cat brain infarction models were established. The glucose metabolism of an infraction lesion improved with time. An infarction lesion was also distinguishable in the Gemini PET scan. We successfully established the cat brain infarction model and evaluated the infarcted lesion and its temporal change using F-18 FDG microPET scanner.

  7. Evaluation of cat brain infarction model using microPET

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jong Jin; Lee, Dong Soo; Kim, Yun Hui; Hwang, Do Won; Kim, Jin Su; Chung, June Key; Lee, Myung Chul [College of Medicine, Seoul National Univ., Seoul (Korea, Republic of); Lim, Sang Moo [Korea Institite of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2004-12-01

    PET has some disadvantage in the imaging of small animal due to poor resolution. With the advent of microPET scanner, it is possible to image small animals. However, the image quality was not good enough as human image. Due to larger brain, cat brain imaging was superior to mouse or rat. In this study, we established the cat brain infarction model and evaluate it and its temporal change using microPET scanner. Two adult male cats were used. Anesthesia was done with xylazine and ketamine HCI. A burr hole was made at 1 cm right lateral to the bregma. Collagenase type IV 10 {mu}l was injected using 30 G needle for 5 minutes to establish the infarction model. {sup 18}F-FDG microPET (Concorde Microsystems Inc., Knoxville, TN) scans were performed 1, 11 and 32 days after the infarction. In addition, {sup 18}F-FDG PET scans were performed using human PET scanner (Gemini, Philips medical systems, CA, USA) 13 and 47 days after the infarction. Two cat brain infarction models were established. The glucose metabolism of an infarction lesion improved with time. An infarction lesion was also distinguishable in the human PET scan. We successfully established the cat brain infarction model and evaluated the infarcted lesion and its temporal change using {sup 18}F-FDG microPET scanner.

  8. Data-driven forward model inference for EEG brain imaging

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

    2016-01-01

    Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

  9. Pedagogic process modeling: Humanistic-integrative approach

    Directory of Open Access Journals (Sweden)

    Boritko Nikolaj M.

    2007-01-01

    Full Text Available The paper deals with some current problems of modeling the dynamics of the subject-features development of the individual. The term "process" is considered in the context of the humanistic-integrative approach, in which the principles of self education are regarded as criteria for efficient pedagogic activity. Four basic characteristics of the pedagogic process are pointed out: intentionality reflects logicality and regularity of the development of the process; discreteness (stageability in dicates qualitative stages through which the pedagogic phenomenon passes; nonlinearity explains the crisis character of pedagogic processes and reveals inner factors of self-development; situationality requires a selection of pedagogic conditions in accordance with the inner factors, which would enable steering the pedagogic process. Offered are two steps for singling out a particular stage and the algorithm for developing an integrative model for it. The suggested conclusions might be of use for further theoretic research, analyses of educational practices and for realistic predicting of pedagogical phenomena. .

  10. Search of novel model for integrative medicine.

    Science.gov (United States)

    Patwardhan, Bhushan; Mutalik, Gururaj

    2014-03-01

    This article provides global and Indian scenario with strengths and limitations of present health care system. Affordability, accessibility and availability of health care coupled with disproportionate growth and double burden of diseases have become major concerns in India. This article emphasizes need for mindset change from illness-disease-drug centric curative to person-health-wellness centric preventive and promotive approaches. It highlights innovation deficit faced pharmaceutical industry and drugs being withdrawn from market for safety reasons. Medical pluralism is a growing trend and people are exploring various options including modern, traditional, complementary and alternative medicine. In such a situation, knowledge from Ayurveda, yoga, Chinese medicine and acupuncture may play an important role. We can evolve a suitable model by integrating modern and traditional systems of medicine for affordable health care. In the larger interest of global community, Indian and Chinese systems should share knowledge and experiences for mutual intellectual enrichments and work together to evolve a novel model of integrative medicine.

  11. Pedagogic process modeling: Humanistic-integrative approach

    OpenAIRE

    Boritko Nikolaj M.

    2007-01-01

    The paper deals with some current problems of modeling the dynamics of the subject-features development of the individual. The term "process" is considered in the context of the humanistic-integrative approach, in which the principles of self education are regarded as criteria for efficient pedagogic activity. Four basic characteristics of the pedagogic process are pointed out: intentionality reflects logicality and regularity of the development of the process; discreteness (stageability) in ...

  12. Which coordinate system for modelling path integration?

    OpenAIRE

    Vickerstaff, Robert J.; Cheung, Allen

    2012-01-01

    Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature. Over the past century or so, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural re...

  13. Improvement of Blood-Brain Barrier Integrity in Traumatic Brain Injury and Hemorrhagic Shock Following Treatment With Valproic Acid and Fresh Frozen Plasma.

    Science.gov (United States)

    Nikolian, Vahagn C; Dekker, Simone E; Bambakidis, Ted; Higgins, Gerald A; Dennahy, Isabel S; Georgoff, Patrick E; Williams, Aaron M; Andjelkovic, Anuska V; Alam, Hasan B

    2018-01-01

    Combined traumatic brain injury and hemorrhagic shock are highly lethal. Following injuries, the integrity of the blood-brain barrier can be impaired, contributing to secondary brain insults. The status of the blood-brain barrier represents a potential factor impacting long-term neurologic outcomes in combined injuries. Treatment strategies involving plasma-based resuscitation and valproic acid therapy have shown efficacy in this setting. We hypothesize that a component of this beneficial effect is related to blood-brain barrier preservation. Following controlled traumatic brain injury, hemorrhagic shock, various resuscitation and treatment strategies were evaluated for their association with blood-brain barrier integrity. Analysis of gene expression profiles was performed using Porcine Gene ST 1.1 microarray. Pathway analysis was completed using network analysis tools (Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene Set Enrichment Analysis). Female Yorkshire swine were subjected to controlled traumatic brain injury and 2 hours of hemorrhagic shock (40% blood volume, mean arterial pressure 30-35 mmHg). Subjects were resuscitated with 1) normal saline, 2) fresh frozen plasma, 3) hetastarch, 4) fresh frozen plasma + valproic acid, or 5) hetastarch + valproic acid (n = 5 per group). After 6 hours of observation, brains were harvested for evaluation. Immunofluoroscopic evaluation of the traumatic brain injury site revealed significantly increased expression of tight-junction associated proteins (zona occludin-1, claudin-5) following combination therapy (fresh frozen plasma + valproic acid and hetastarch + valproic acid). The extracellular matrix protein laminin was found to have significantly improved expression with combination therapies. Pathway analysis indicated that valproic acid significantly modulated pathways involved in endothelial barrier function and cell signaling. Resuscitation with fresh frozen plasma results in improved expression of

  14. Integrated Modelling in CRUCIAL Science Education

    Science.gov (United States)

    Mahura, Alexander; Nuterman, Roman; Mukhamedzhanova, Elena; Nerobelov, Georgiy; Sedeeva, Margarita; Suhodskiy, Alexander; Mostamandy, Suleiman; Smyshlyaev, Sergey

    2017-04-01

    The NordForsk CRUCIAL project (2016-2017) "Critical steps in understanding land surface - atmosphere interactions: from improved knowledge to socioeconomic solutions" as a part of the Pan-Eurasian EXperiment (PEEX; https://www.atm.helsinki.fi/peex) programme activities, is looking for a deeper collaboration between Nordic-Russian science communities. In particular, following collaboration between Danish and Russian partners, several topics were selected for joint research and are focused on evaluation of: (1) urbanization processes impact on changes in urban weather and climate on urban-subregional-regional scales and at contribution to assessment studies for population and environment; (2) effects of various feedback mechanisms on aerosol and cloud formation and radiative forcing on urban-regional scales for better predicting extreme weather events and at contribution to early warning systems, (3) environmental contamination from continues emissions and industrial accidents for better assessment and decision making for sustainable social and economic development, and (4) climatology of atmospheric boundary layer in northern latitudes to improve understanding of processes, revising parameterizations, and better weather forecasting. These research topics are realized employing the online integrated Enviro-HIRLAM (Environment - High Resolution Limited Area Model) model within students' research projects: (1) "Online integrated high-resolution modelling of Saint-Petersburg metropolitan area influence on weather and air pollution forecasting"; (2) "Modeling of aerosol impact on regional-urban scales: case study of Saint-Petersburg metropolitan area"; (3) "Regional modeling and GIS evaluation of environmental pollution from Kola Peninsula sources"; and (4) "Climatology of the High-Latitude Planetary Boundary Layer". The students' projects achieved results and planned young scientists research training on online integrated modelling (Jun 2017) will be presented and

  15. EEG-fMRI integration for the study of human brain function.

    Science.gov (United States)

    Jorge, João; van der Zwaag, Wietske; Figueiredo, Patrícia

    2014-11-15

    Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have proved to be extremely valuable tools for the non-invasive study of human brain function. Moreover, due to a notable degree of complementarity between the two modalities, the combination of EEG and fMRI data has been actively sought in the last two decades. Although initially focused on epilepsy, EEG-fMRI applications were rapidly extended to the study of healthy brain function, yielding new insights into its underlying mechanisms and pathways. Nevertheless, EEG and fMRI have markedly different spatial and temporal resolutions, and probe neuronal activity through distinct biophysical processes, many aspects of which are still poorly understood. The remarkable conceptual and methodological challenges associated with EEG-fMRI integration have motivated the development of a wide range of analysis approaches over the years, each relying on more or less restrictive assumptions, and aiming to shed further light on the mechanisms of brain function along with those of the EEG-fMRI coupling itself. Here, we present a review of the most relevant EEG-fMRI integration approaches yet proposed for the study of brain function, supported by a general overview of our current understanding of the biophysical mechanisms coupling the signals obtained from the two modalities. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. An integrated neuromechanical model of insect locomotion

    Science.gov (United States)

    Kukillaya, Raghavendra

    We develop a biologically-plausible feedforward neuromechanical model for running insects that includes a simplified hexapedal leg geometry with agonist-antagonist muscle pairs actuating each leg joint. It is driven by a neural network modeling the central pattern generator (CPG) and the motoneurons which activate the muscles. This final goal is achieved in three stages. First, a relatively simple mechanical hexapedal model is constructed in which the joint torques are produced via actuated linear torsional springs with constant stiffness. In the second stage, this system is upgraded to a muscle-actuated hexapedal model in which each joint is actuated by a pair of agonist-antagonist Hill-type muscles. Muscles are driven by stylized action potentials that are characteristic of fast motoneurons, and modeled using an activation function and nonlinear length and shortening velocity dependence. In the final stage, the full neuromechanical model is obtained by integrating the above muscle-actuated hexapedal model with a CPG-motoneuron complex, feedforward input to the muscles now being supplied by action potentials from motoneurons. Restricting to dynamics in the horizontal plane and neglecting leg masses, we reduce the model (at each stage) to three degrees of freedom describing translational and yawing motions of the body. Collectively for all the models, parameter values are based on measurements from depressor motoneurons and muscles, and observations of kinematics and dynamics of the cockroach Blaberus discoidalis. Specifically, actuation inputs for the mechanical and muscle-actuated models are chosen to approximately achieve joint torques that are consistent with measured ground reaction forces. This is done by optimizing the time-dependent torque-free joint angles in the first model, and by optimizing motoneuronal outputs and muscle force levels in the second and third models. We show that the model (at each stage) has stable double-tripod gaits over the animal

  17. Postnatal experiences influence how the brain integrates information from different senses

    Directory of Open Access Journals (Sweden)

    Barry E Stein

    2009-09-01

    Full Text Available Sensory Processing Disorder (SPD is characterized by anomalous reactions to, and integration of, sensory cues. Although the underlying etiology of SPD is unknown, one brain region likely to reflect these sensory and behavioral anomalies is the Superior Colliculus (SC; a structure involved in the synthesis of information from multiple sensory modalities and the control of overt orientation responses. In this review we describe normal functional properties of this structure, the manner in which its individual neurons integrate cues from different senses, and the overt SC-mediated behaviors that are believed to manifest this “multisensory integration.” Of particular interest here is how SC neurons develop their capacity to engage in multisensory integration during early postnatal life as a consequence of early sensory experience, and that it is the intimate communication between cortex and the midbrain makes this developmental process possible.

  18. Toward an integrative science of the developing human mind and brain: Focus on the developing cortex ?

    OpenAIRE

    Jernigan, Terry L.; Brown, Timothy T.; Bartsch, Hauke; Dale, Anders M.

    2015-01-01

    © 2015 The Authors. Based on the Huttenlocher lecture, this article describes the need for a more integrative scientific paradigm for addressing important questions raised by key observations made over 2 decades ago. Among these are the early descriptions by Huttenlocher of variability in synaptic density in cortex of postmortem brains of children of different ages and the almost simultaneous reports of cortical volume reductions on MR imaging in children and adolescents. In spite of much pro...

  19. Biochemical Markers of Brain Injury: An Integrated Proteomics-Based Approach

    Science.gov (United States)

    2006-02-01

    thapsigargin ( T24 )-treated PC12 cells compared with PC12 cells pre-treated with the Z-D-DCB pan- caspase inhibitor (Inh) before thapsigargin treatment or with...neuroproteomics analysis of traumatic brain injury in rats. Mol. Cell Proteom. web published in 2006. Abstracts 1. Ronald L. Hayes. An integrated...Electrophoresis 1997, 18, 533-537. (4) Gygi, S. P.; Rochon, Y.; Franza, B. R.; Aebersold, R. Mol. Cell . Biol. 1999, 19, 1720-1730. (5) Hanash, S. Nature

  20. Pomegranate extract protects against cerebral ischemia/reperfusion injury and preserves brain DNA integrity in rats.

    Science.gov (United States)

    Ahmed, Maha A E; El Morsy, Engy M; Ahmed, Amany A E

    2014-08-21

    Interruption to blood flow causes ischemia and infarction of brain tissues with consequent neuronal damage and brain dysfunction. Pomegranate extract is well tolerated, and safely consumed all over the world. Interestingly, pomegranate extract has shown remarkable antioxidant and anti-inflammatory effects in experimental models. Many investigators consider natural extracts as novel therapies for neurodegenerative disorders. Therefore, this study was carried out to investigate the protective effects of standardized pomegranate extract against cerebral ischemia/reperfusion-induced brain injury in rats. Adult male albino rats were randomly divided into sham-operated control group, ischemia/reperfusion (I/R) group, and two other groups that received standardized pomegranate extract at two dose levels (250, 500 mg/kg) for 15 days prior to ischemia/reperfusion (PMG250+I/R, and PMG500+I/R groups). After I/R or sham operation, all rats were sacrificed and brains were harvested for subsequent biochemical analysis. Results showed reduction in brain contents of MDA (malondialdehyde), and NO (nitric oxide), in addition to enhancement of SOD (superoxide dismutase), GPX (glutathione peroxidase), and GRD (glutathione reductase) activities in rats treated with pomegranate extract prior to cerebral I/R. Moreover, pomegranate extract decreased brain levels of NF-κB p65 (nuclear factor kappa B p65), TNF-α (tumor necrosis factor-alpha), caspase-3 and increased brain levels of IL-10 (interleukin-10), and cerebral ATP (adenosine triphosphate) production. Comet assay showed less brain DNA (deoxyribonucleic acid) damage in rats protected with pomegranate extract. The present study showed, for the first time, that pre-administration of pomegranate extract to rats, can offer a significant dose-dependent neuroprotective activity against cerebral I/R brain injury and DNA damage via antioxidant, anti-inflammatory, anti-apoptotic and ATP-replenishing effects. Copyright © 2014 Elsevier Inc

  1. Brain network analysis: separating cost from topology using cost-integration.

    Directory of Open Access Journals (Sweden)

    Cedric E Ginestet

    Full Text Available A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i differences in weighted costs and (ii differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration.

  2. Brain network analysis: separating cost from topology using cost-integration.

    Science.gov (United States)

    Ginestet, Cedric E; Nichols, Thomas E; Bullmore, Ed T; Simmons, Andrew

    2011-01-01

    A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i) differences in weighted costs and (ii) differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration.

  3. Integrated Model for E-Learning Acceptance

    Science.gov (United States)

    Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.

    2016-01-01

    E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.

  4. An Integrative Model of Internationalization Strategies

    DEFF Research Database (Denmark)

    Li, Xin; Gammelgaard, Jens

    2014-01-01

    Purpose – This paper aims to critically review the ownership, location and internalization (OLI) model and the Uppsala internationalization process (UIP) framework. We suggest that the inclusion of concepts such as corporate entrepreneurship, host country institutions and regulatory focus...... in an integrated framework helps to explain firm internationalization. Design/methodology/approach – This paper is based on a review of the literature on the OLI and UIP models. In addition, it presents a conceptual model that encompasses corporate entrepreneurship, regulatory focus and institutions. Findings...... choice with regard to internationalization. Practical implications – Regulatory focus theory originates from managerial psychology. The model is, therefore, relevant for managers, and it shows how the outcomes and processes of corporate entrepreneurial activity should manifest themselves in managerial...

  5. MODELS OF TECHNOLOGY ADOPTION: AN INTEGRATIVE APPROACH

    Directory of Open Access Journals (Sweden)

    Andrei OGREZEANU

    2015-06-01

    Full Text Available The interdisciplinary study of information technology adoption has developed rapidly over the last 30 years. Various theoretical models have been developed and applied such as: the Technology Acceptance Model (TAM, Innovation Diffusion Theory (IDT, Theory of Planned Behavior (TPB, etc. The result of these many years of research is thousands of contributions to the field, which, however, remain highly fragmented. This paper develops a theoretical model of technology adoption by integrating major theories in the field: primarily IDT, TAM, and TPB. To do so while avoiding mess, an approach that goes back to basics in independent variable type’s development is proposed; emphasizing: 1 the logic of classification, and 2 psychological mechanisms behind variable types. Once developed these types are then populated with variables originating in empirical research. Conclusions are developed on which types are underpopulated and present potential for future research. I end with a set of methodological recommendations for future application of the model.

  6. Sparse model selection via integral terms

    Science.gov (United States)

    Schaeffer, Hayden; McCalla, Scott G.

    2017-08-01

    Model selection and parameter estimation are important for the effective integration of experimental data, scientific theory, and precise simulations. In this work, we develop a learning approach for the selection and identification of a dynamical system directly from noisy data. The learning is performed by extracting a small subset of important features from an overdetermined set of possible features using a nonconvex sparse regression model. The sparse regression model is constructed to fit the noisy data to the trajectory of the dynamical system while using the smallest number of active terms. Computational experiments detail the model's stability, robustness to noise, and recovery accuracy. Examples include nonlinear equations, population dynamics, chaotic systems, and fast-slow systems.

  7. Integrated statistical modelling of spatial landslide probability

    Science.gov (United States)

    Mergili, M.; Chu, H.-J.

    2015-09-01

    Statistical methods are commonly employed to estimate spatial probabilities of landslide release at the catchment or regional scale. Travel distances and impact areas are often computed by means of conceptual mass point models. The present work introduces a fully automated procedure extending and combining both concepts to compute an integrated spatial landslide probability: (i) the landslide inventory is subset into release and deposition zones. (ii) We employ a simple statistical approach to estimate the pixel-based landslide release probability. (iii) We use the cumulative probability density function of the angle of reach of the observed landslide pixels to assign an impact probability to each pixel. (iv) We introduce the zonal probability i.e. the spatial probability that at least one landslide pixel occurs within a zone of defined size. We quantify this relationship by a set of empirical curves. (v) The integrated spatial landslide probability is defined as the maximum of the release probability and the product of the impact probability and the zonal release probability relevant for each pixel. We demonstrate the approach with a 637 km2 study area in southern Taiwan, using an inventory of 1399 landslides triggered by the typhoon Morakot in 2009. We observe that (i) the average integrated spatial landslide probability over the entire study area corresponds reasonably well to the fraction of the observed landside area; (ii) the model performs moderately well in predicting the observed spatial landslide distribution; (iii) the size of the release zone (or any other zone of spatial aggregation) influences the integrated spatial landslide probability to a much higher degree than the pixel-based release probability; (iv) removing the largest landslides from the analysis leads to an enhanced model performance.

  8. Global fractional anisotropy and mean diffusivity together with segmented brain volumes assemble a predictive discriminant model for young and elderly healthy brains: a pilot study at 3T

    Science.gov (United States)

    Garcia-Lazaro, Haydee Guadalupe; Becerra-Laparra, Ivonne; Cortez-Conradis, David; Roldan-Valadez, Ernesto

    2016-01-01

    Summary Several parameters of brain integrity can be derived from diffusion tensor imaging. These include fractional anisotropy (FA) and mean diffusivity (MD). Combination of these variables using multivariate analysis might result in a predictive model able to detect the structural changes of human brain aging. Our aim was to discriminate between young and older healthy brains by combining structural and volumetric variables from brain MRI: FA, MD, and white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) volumes. This was a cross-sectional study in 21 young (mean age, 25.71±3.04 years; range, 21–34 years) and 10 elderly (mean age, 70.20±4.02 years; range, 66–80 years) healthy volunteers. Multivariate discriminant analysis, with age as the dependent variable and WM, GM and CSF volumes, global FA and MD, and gender as the independent variables, was used to assemble a predictive model. The resulting model was able to differentiate between young and older brains: Wilks’ λ = 0.235, χ2 (6) = 37.603, p = .000001. Only global FA, WM volume and CSF volume significantly discriminated between groups. The total accuracy was 93.5%; the sensitivity, specificity and positive and negative predictive values were 91.30%, 100%, 100% and 80%, respectively. Global FA, WM volume and CSF volume are parameters that, when combined, reliably discriminate between young and older brains. A decrease in FA is the strongest predictor of membership of the older brain group, followed by an increase in WM and CSF volumes. Brain assessment using a predictive model might allow the follow-up of selected cases that deviate from normal aging. PMID:27027893

  9. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks.

    Science.gov (United States)

    Vértes, Petra E; Alexander-Bloch, Aaron; Bullmore, Edward T

    2014-10-05

    Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  10. Causation model of autism: Audiovisual brain specialization in infancy competes with social brain networks.

    Science.gov (United States)

    Heffler, Karen Frankel; Oestreicher, Leonard M

    2016-06-01

    Earliest identifiable findings in autism indicate that the autistic brain develops differently from the typical brain in the first year of life, after a period of typical development. Twin studies suggest that autism has an environmental component contributing to causation. Increased availability of audiovisual (AV) materials and viewing practices of infants parallel the time frame of the rise in prevalence of autism spectrum disorder (ASD). Studies have shown an association between ASD and increased TV/cable screen exposure in infancy, suggesting AV exposure in infancy as a possible contributing cause of ASD. Infants are attracted to the saliency of AV materials, yet do not have the experience to recognize these stimuli as socially relevant. The authors present a developmental model of autism in which exposure to screen-based AV input in genetically susceptible infants stimulates specialization of non-social sensory processing in the brain. Through a process of neuroplasticity, the autistic infant develops the skills that are driven by the AV viewing. The AV developed neuronal pathways compete with preference for social processing, negatively affecting development of social brain pathways and causing global developmental delay. This model explains atypical face and speech processing, as well as preference for AV synchrony over biological motion in ASD. Neural hyper-connectivity, enlarged brain size and special abilities in visual, auditory and motion processing in ASD are also explained by the model. Positive effects of early intervention are predicted by the model. Researchers studying causation of autism have largely overlooked AV exposure in infancy as a potential contributing factor. The authors call for increased public awareness of the association between early screen viewing and ASD, and a concerted research effort to determine the extent of causal relationship. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  11. Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

    Science.gov (United States)

    Iturria-Medina, Yasser; Carbonell, Félix M; Sotero, Roberto C; Chouinard-Decorte, Francois; Evans, Alan C

    2017-05-15

    Generative models focused on multifactorial causal mechanisms in brain disorders are scarce and generally based on limited data. Despite the biological importance of the multiple interacting processes, their effects remain poorly characterized from an integrative analytic perspective. Here, we propose a spatiotemporal multifactorial causal model (MCM) of brain (dis)organization and therapeutic intervention that accounts for local causal interactions, effects propagation via physical brain networks, cognitive alterations, and identification of optimum therapeutic interventions. In this article, we focus on describing the model and applying it at the population-based level for studying late onset Alzheimer's disease (LOAD). By interrelating six different neuroimaging modalities and cognitive measurements, this model accurately predicts spatiotemporal alterations in brain amyloid-β (Aβ) burden, glucose metabolism, vascular flow, resting state functional activity, structural properties, and cognitive integrity. The results suggest that a vascular dysregulation may be the most-likely initial pathologic event leading to LOAD. Nevertheless, they also suggest that LOAD it is not caused by a unique dominant biological factor (e.g. vascular or Aβ) but by the complex interplay among multiple relevant direct interactions. Furthermore, using theoretical control analysis of the identified population-based multifactorial causal network, we show the crucial advantage of using combinatorial over single-target treatments, explain why one-target Aβ based therapies might fail to improve clinical outcomes, and propose an efficiency ranking of possible LOAD interventions. Although still requiring further validation at the individual level, this work presents the first analytic framework for dynamic multifactorial brain (dis)organization that may explain both the pathologic evolution of progressive neurological disorders and operationalize the influence of multiple interventional

  12. Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI

    Science.gov (United States)

    Pei, Linmin; Reza, Syed M. S.; Li, Wei; Davatzikos, Christos; Iftekharuddin, Khan M.

    2017-03-01

    In this work, we propose a novel method to improve texture based tumor segmentation by fusing cell density patterns that are generated from tumor growth modeling. To model tumor growth, we solve the reaction-diffusion equation by using Lattice-Boltzmann method (LBM). Computational tumor growth modeling obtains the cell density distribution that potentially indicates the predicted tissue locations in the brain over time. The density patterns is then considered as novel features along with other texture (such as fractal, and multifractal Brownian motion (mBm)), and intensity features in MRI for improved brain tumor segmentation. We evaluate the proposed method with about one hundred longitudinal MRI scans from five patients obtained from public BRATS 2015 data set, validated by the ground truth. The result shows significant improvement of complete tumor segmentation using ANOVA analysis for five patients in longitudinal MR images.

  13. Multigrid Nonlocal Gaussian Mixture Model for Segmentation of Brain Tissues in Magnetic Resonance Images

    Directory of Open Access Journals (Sweden)

    Yunjie Chen

    2016-01-01

    Full Text Available We propose a novel segmentation method based on regional and nonlocal information to overcome the impact of image intensity inhomogeneities and noise in human brain magnetic resonance images. With the consideration of the spatial distribution of different tissues in brain images, our method does not need preestimation or precorrection procedures for intensity inhomogeneities and noise. A nonlocal information based Gaussian mixture model (NGMM is proposed to reduce the effect of noise. To reduce the effect of intensity inhomogeneity, the multigrid nonlocal Gaussian mixture model (MNGMM is proposed to segment brain MR images in each nonoverlapping multigrid generated by using a new multigrid generation method. Therefore the proposed model can simultaneously overcome the impact of noise and intensity inhomogeneity and automatically classify 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid. To maintain the statistical reliability and spatial continuity of the segmentation, a fusion strategy is adopted to integrate the clustering results from different grid. The experiments on synthetic and clinical brain MR images demonstrate the superior performance of the proposed model comparing with several state-of-the-art algorithms.

  14. Typological and Integrative Models of Sexual Abuse

    Directory of Open Access Journals (Sweden)

    Demidova L.Y.,

    2014-11-01

    Full Text Available We discuss the basic typological and integrative theoretical models that explain the occurrence of child sexual abuse and the differences detected among the perpetrators of crimes against sexual integrity of minors. A comprehensive review of the theoretical concepts of sexual abuse in our country, in fact has not been carried out, and in this paper for the first time we made such an attempt. It is shown that the existing notions of sexual abuse largely overlap each other, but each of the models somehow takes into account the factors not explicitly addressed in other concepts. Systematic consideration of the theoretical models of sexual abuse can generalize and systematize the available data on the mechanisms of pedophile behavior. This review provides an opportunity to develop a new benchmark in the study of sexual abuse, get closer to building the most accurate and comprehensive model. In turn, this may contribute to solving the questions about the factors, dynamics, and the prevention of criminal sexual conduct against children

  15. The Gold Coast Integrated Care Model

    Directory of Open Access Journals (Sweden)

    Martin Connor

    2016-07-01

    Full Text Available This article outlines the development of the Australian Gold Coast Integrated Care Model based on the elements identified in contemporary research literature as essential for successful integration of care between primary care, and acute hospital services. The objectives of the model are to proactively manage high risk patients with complex and chronic conditions in collaboration with General Practitioners to ultimately reduce presentations to the health service emergency department, improve the capacity of specialist outpatients, and decrease planned and unplanned admission rates. Central to the model is a shared care record which is maintained and accessed by staff in the Coordination Centre. We provide a process map outlining the care protocols from initial assessment to care of the patient presenting for emergency care. The model is being evaluated over a pilot three year proof of concept phase to determine economic and process perspectives. If found to be cost-effective, acceptable to patients and professionals and as good as or better than usual care in terms of outcomes, the strategic intent is to scale the programme beyond the local health service.

  16. Integration of miRNA and protein profiling reveals coordinated neuroadaptations in the alcohol-dependent mouse brain.

    Directory of Open Access Journals (Sweden)

    Giorgio Gorini

    Full Text Available The molecular mechanisms underlying alcohol dependence involve different neurochemical systems and are brain region-dependent. Chronic Intermittent Ethanol (CIE procedure, combined with a Two-Bottle Choice voluntary drinking paradigm, represents one of the best available animal models for alcohol dependence and relapse drinking. MicroRNAs, master regulators of the cellular transcriptome and proteome, can regulate their targets in a cooperative, combinatorial fashion, ensuring fine tuning and control over a large number of cellular functions. We analyzed cortex and midbrain microRNA expression levels using an integrative approach to combine and relate data to previous protein profiling from the same CIE-subjected samples, and examined the significance of the data in terms of relative contribution to alcohol consumption and dependence. MicroRNA levels were significantly altered in CIE-exposed dependent mice compared with their non-dependent controls. More importantly, our integrative analysis identified modules of coexpressed microRNAs that were highly correlated with CIE effects and predicted target genes encoding differentially expressed proteins. Coexpressed CIE-relevant proteins, in turn, were often negatively correlated with specific microRNA modules. Our results provide evidence that microRNA-orchestrated translational imbalances are driving the behavioral transition from alcohol consumption to dependence. This study represents the first attempt to combine ex vivo microRNA and protein expression on a global scale from the same mammalian brain samples. The integrative systems approach used here will improve our understanding of brain adaptive changes in response to drug abuse and suggests the potential therapeutic use of microRNAs as tools to prevent or compensate multiple neuroadaptations underlying addictive behavior.

  17. Hypnosis, suggestion, and suggestibility: an integrative model.

    Science.gov (United States)

    Lynn, Steven Jay; Laurence, Jean-Roch; Kirsch, Irving

    2015-01-01

    This article elucidates an integrative model of hypnosis that integrates social, cultural, cognitive, and neurophysiological variables at play both in and out of hypnosis and considers their dynamic interaction as determinants of the multifaceted experience of hypnosis. The roles of these variables are examined in the induction and suggestion stages of hypnosis, including how they are related to the experience of involuntariness, one of the hallmarks of hypnosis. It is suggested that studies of the modification of hypnotic suggestibility; cognitive flexibility; response sets and expectancies; the default-mode network; and the search for the neurophysiological correlates of hypnosis, more broadly, in conjunction with research on social psychological variables, hold much promise to further understanding of hypnosis.

  18. Toward an Integrative Model of Global Business Strategy

    DEFF Research Database (Denmark)

    Li, Xin

    fragmentation-integration-fragmentation-integration upward spiral. In response to the call for integrative approach to strategic management research, we propose an integrative model of global business strategy that aims at integrating not only strategy and IB but also the different paradigms within the strategy...

  19. Directions for Mind, Brain, and Education: Methods, Models, and Morality

    Science.gov (United States)

    Stein, Zachary; Fischer, Kurt W.

    2011-01-01

    In this article we frame a set of important issues in the emerging field of Mind, Brain, and Education in terms of three broad headings: methods, models, and morality. Under the heading of methods we suggest that the need for synthesis across scientific and practical disciplines entails the pursuit of usable knowledge via a catalytic symbiosis…

  20. Human cadaver brain infusion skull model for neurosurgical training.

    Science.gov (United States)

    Olabe, Jon; Olabe, Javier; Roda, Jose Maria; Sancho, Vidal

    2011-01-01

    Microsurgical technique and anatomical knowledge require extensive laboratory training. Human cadaver models are especially valuable as they supply a good microsurgical training environment simultaneously providing authentic brain anatomy. We developed the "skull infusion model" as an extension of our previous "brain infusion model" taking it a step further maintaining simplicity but enhancing realism. Four human cadaveric brains donated for educational purposes were explanted at autopsy. The specimens were prepared cannulating carotid and vertebral arteries with plastic tubings, flushed with abundant water and fixed for 1 month in formaldehyde. They were then enclosed with white silk clothing (emulating the dura mater) and inserted into human skulls cut previously into two pieces. Tap water at a flow rate of 10 L/h was infused through the arterial tubings. Diverse microsurgical procedures were performed by two trainees, including craniotomies with microsurgical approaches and techniques such as sylvian fissure exposure, extra-intracranial and intra-intracranial bypass, approaches to the ventricles and choroidal fissure opening. The water infusion fills the arterial system, leaking into the interstitial and cisternal space and finally moistening the whole specimen. This makes vascular microsurgical techniques become extremely realistic, increasing its compliance making manipulations easier and more authentic. Standard microsurgical laboratories frequently have difficulties to work with decapitated human cadaver heads but could have human brains readily available. Using the infusion model and inserting it in a human skull makes the environment much more realistic. Its simplicity and inexpensiveness make it a good alternative for developing microsurgical techniques.

  1. Stochastic model of Tsc1 lesions in mouse brain.

    Directory of Open Access Journals (Sweden)

    Shilpa Prabhakar

    Full Text Available Tuberous sclerosis complex (TSC is an autosomal dominant disorder due to mutations in either TSC1 or TSC2 that affects many organs with hamartomas and tumors. TSC-associated brain lesions include subependymal nodules, subependymal giant cell astrocytomas and tubers. Neurologic manifestations in TSC comprise a high frequency of mental retardation and developmental disorders including autism, as well as epilepsy. Here, we describe a new mouse model of TSC brain lesions in which complete loss of Tsc1 is achieved in multiple brain cell types in a stochastic pattern. Injection of an adeno-associated virus vector encoding Cre recombinase into the cerebral ventricles of mice homozygous for a Tsc1 conditional allele on the day of birth led to reduced survival, and pathologic findings of enlarged neurons, cortical heterotopias, subependymal nodules, and hydrocephalus. The severity of clinical and pathologic findings as well as survival was shown to be dependent upon the dose and serotype of Cre virus injected. Although several other models of TSC brain disease exist, this model is unique in that the pathology reflects a variety of TSC-associated lesions involving different numbers and types of cells. This model provides a valuable and unique addition for therapeutic assessment.

  2. Brain mechanisms in religion and spirituality: An integrative predictive processing framework.

    Science.gov (United States)

    van Elk, Michiel; Aleman, André

    2017-02-01

    We present the theory of predictive processing as a unifying framework to account for the neurocognitive basis of religion and spirituality. Our model is substantiated by discussing four different brain mechanisms that play a key role in religion and spirituality: temporal brain areas are associated with religious visions and ecstatic experiences; multisensory brain areas and the default mode network are involved in self-transcendent experiences; the Theory of Mind-network is associated with prayer experiences and over attribution of intentionality; top-down mechanisms instantiated in the anterior cingulate cortex and the medial prefrontal cortex could be involved in acquiring and maintaining intuitive supernatural beliefs. We compare the predictive processing model with two-systems accounts of religion and spirituality, by highlighting the central role of prediction error monitoring. We conclude by presenting novel predictions for future research and by discussing the philosophical and theological implications of neuroscientific research on religion and spirituality. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Cellular immortality in brain tumours: an integration of the cancer stem cell paradigm.

    Science.gov (United States)

    Rahman, Ruman; Heath, Rachel; Grundy, Richard

    2009-04-01

    Brain tumours are a diverse group of neoplasms that continue to present a formidable challenge in our attempt to achieve curable intervention. Our conceptual framework of human brain cancer has been redrawn in the current decade. There is a gathering acceptance that brain tumour formation is a phenotypic outcome of dysregulated neurogenesis, with tumours viewed as abnormally differentiated neural tissue. In relation, there is accumulating evidence that brain tumours, similar to leukaemia and many solid tumours, are organized as a developmental hierarchy which is maintained by a small fraction of cells endowed with many shared properties of tissue stem cells. Proof that neurogenesis persists throughout adult life, compliments this concept. Although the cancer cell of origin is unclear, the proliferative zones that harbour stem cells in the embryonic, post-natal and adult brain are attractive candidates within which tumour-initiation may ensue. Dysregulated, unlimited proliferation and an ability to bypass senescence are acquired capabilities of cancerous cells. These abilities in part require the establishment of a telomere maintenance mechanism for counteracting the shortening of chromosomal termini. A strategy based upon the synthesis of telomeric repeat sequences by the ribonucleoprotein telomerase, is prevalent in approximately 90% of human tumours studied, including the majority of brain tumours. This review will provide a developmental perspective with respect to normal (neurogenesis) and aberrant (tumourigenesis) cellular turnover, differentiation and function. Within this context our current knowledge of brain tumour telomere/telomerase biology will be discussed with respect to both its developmental and therapeutic relevance to the hierarchical model of brain tumourigenesis presented by the cancer stem cell paradigm.

  4. Using Data-Driven Model-Brain Mappings to Constrain Formal Models of Cognition

    OpenAIRE

    Borst, Jelmer P; Menno Nijboer; Taatgen, Niels A.; Hedderik van Rijn; John R Anderson

    2015-01-01

    In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-bas...

  5. Quantification of Brain Access of Exendin-4 in the C57BL Mouse Model by SPIM Fluorescence Imaging and the Allen Mouse Brain Reference Model

    DEFF Research Database (Denmark)

    Jensen, Casper Bo; Secher, Anna; Hecksher-Sørensen, Jacob

    2015-01-01

    construct a SPIM brain atlas based on the Allen mouse brain 3D reference model and use it to analyze the access of peripherally injected Exendin-4 into the brain compared to a negative control group. The constructed atlas consists of an average SPIM volume obtained from eight C57BL mouse brains using group......-wise registration. A cross-modality registration is performed between the constructed average volume and the Allen mouse brain reference model to allow propagation of annotations to the SPIM average brain. Finally, manual corrections of the annotations are performed and validated by visual inspection. The study...

  6. How Anatomy Shapes Dynamics: A Semi-Analytical Study of the Brain at Rest by a Simple Spin Model

    Directory of Open Access Journals (Sweden)

    Gustavo eDeco

    2012-09-01

    Full Text Available Resting state networks show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found the presence of latent ghost multi-stable attractors, which can be studied analytically. The multistable attractor landscape defines a functionally meaningful dynamic repertoire of the brain network that is inherently present in the neuroanatomical connectivity. We demonstrate that the more entropy of attractors exists, the richer is the dynamical repertoire and consequently the brain network displays more capabilities of computation. We hypothesize therefore that human brain connectivity developed a scale free type of architecture in order to be able to store a large number of different and flexibly accessible brain functions

  7. How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model.

    Science.gov (United States)

    Deco, Gustavo; Senden, Mario; Jirsa, Viktor

    2012-01-01

    Resting state networks (RSNs) show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI-(Diffusion Tensor Imaging/Diffusion Spectrum Imaging)based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found a system with multiple attractors, which can be studied analytically. The multistable attractor landscape thus defines a functionally meaningful dynamic repertoire of the brain network that is inherently present in the neuroanatomical connectivity. We demonstrate that the more entropy of attractors exists, the richer is the dynamical repertoire and consequently the brain network displays more capabilities of computation. We hypothesize therefore that human brain connectivity developed a scale free type of architecture in order to be able to store a large number of different and flexibly accessible brain functions.

  8. CSF transthyretin neuroprotection in a mouse model of brain ischemia

    DEFF Research Database (Denmark)

    Santos, Sofia Duque; Lambertsen, Kate Lykke; Clausen, Bettina Hjelm

    2010-01-01

    Brain injury caused by ischemia is a major cause of human mortality and physical/cognitive disability worldwide. Experimentally, brain ischemia can be induced surgically by permanent middle cerebral artery occlusion. Using this model, we studied the influence of transthyretin in ischemic stroke....... However, TTR null mice, heterozygous for the heat-shock transcription factor 1 (TTR(-/-) HSF1(+/-) mice), which compromised the stress response, showed a significant increase in cortical infarction, cerebral edema and the microglial-leukocyte response compared with TTR(+/+) HSF1(+/-) mice. Unexpectedly...

  9. Through the Immune Looking Glass: A Model for Brain Memory Strategies.

    Directory of Open Access Journals (Sweden)

    Silvia eSánchez-Ramón

    2016-02-01

    Full Text Available The immune system (IS and the central nervous system (CNS are complex cognitive networks involved in defining the identity (self of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e. danger-fear memories and would drive the formation of long-term and highly specific or explicit memories (i.e. the taste of the Proust’s madeleine cake by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective.

  10. Epistemic Games in Integration: Modeling Resource Choice

    Science.gov (United States)

    Black, Katrina E.; Wittmann, Michael C.

    2007-11-01

    As part of an ongoing project to understand how mathematics is used in advanced physics to guide one's conceptual understanding of physics, we focus on students' interpretation and use of boundary and initial conditions when solving integrals. We discuss an interaction between two students working on a group quiz problem. After describing the interaction, we briefly discuss the procedural resources that we use to model the students' solutions. We then use the procedural resources introduced earlier to draw resources graphs describing the two epistemic game facets used by the students in our transcript.

  11. Organizational buying behavior: An integrated model

    Directory of Open Access Journals (Sweden)

    Rakić Beba

    2002-01-01

    Full Text Available Organizational buying behavior is decision making process by which formal organizations establish the need for purchased products and services, and identify, evaluate, and choose among alternative brands and suppliers. Understanding the buying decision processes is essential to developing the marketing programs of companies that sell to organizations, or to 'industrial customers'. In business (industrial marketing, exchange relationships between the organizational selling center and the organizational buying center are crucial. Integrative model of organizational buying behavior offers a systematic framework in analyzing the complementary factors and what effect they have on the behavior of those involved in making buying decisions.

  12. Differential and Integral Models of TOKAMAK

    Directory of Open Access Journals (Sweden)

    Ivo Dolezel

    2004-01-01

    Full Text Available Modeling of 3D electromagnetic phenomena in TOKAMAK with typically distributed main and additional coils is not an easy business. Evaluated must be not only distribution of the magnetic field, but also forces acting in particular coils. Use of differential methods (such as FDM or FEM for this purpose may be complicated because of geometrical incommensurability of particular subregions in the investigated area or problems with the boundary conditions. That is why integral formulation of the problem may sometimes be an advantages. The theoretical analysis is illustrated on an example processed by both methods, whose results are compared and discussed.

  13. An integrated dielectric elastomer generator model

    Science.gov (United States)

    McKay, Thomas; O'Brien, Benjamin; Calius, Emilio; Anderson, Iain

    2010-04-01

    Dielectric Elastomer Generator(s) (DEG), are essentially variable capacitor power generators formed by hyper-elastic dielectric materials sandwiched between flexible electrodes. Electrical energy can be produced from a stretched, charged DEG by relaxing the mechanical deformation whilst maintaining the amount of charge on its electrodes. This increases the distance between opposite charges and packs likecharges more densely, increasing the amount of electrical energy. DEG show promise for harvesting energy from environmental sources such as wind and ocean waves. DEG can undergo large inhomogeneous deformations and electric fields during operation, meaning it can be difficult to experimentally determine optimal designs. Also, the circuit that is used for harnessing DEG energy influences the DEG output by controlling the amount of charge on the DEG. In this paper an integrated DEG model was developed where an ABAQUS finite element model is used to model the DEG and data from this model is input to a system level LT-Spice circuit simulation. As a case-study, the model was used as a design tool for analysing a diaphragm DEG connected to a self-priming circuit. That is, a circuit capable of overcoming electrical losses by using some of the DEG energy to boost the charge in the system. Our ABAQUS model was experimentally validated to predict the varying capacitance of a diaphragm DEG deformed inhomogeneously to within 6% error.

  14. [School re-integration after child brain dislocation : The trauma surgeon's role].

    Science.gov (United States)

    Gänsslen, A; Neubauer, T; Hartl, C; Moser, N; Rickels, E; Lüngen, H; Nerlich, M; Krutsch, W

    2017-05-01

    Concussion injury of the brain is still a frequently underestimated injury, which can be associated with long-lasting consequences. Compared to adults, the recovery phase is often prolonged in childhood. Primary treatment consists of symptom-dependent physical and mental activities. Re-integration into daily life is crucial. In childhood, the primary focus is therefore on returning to school. New symptoms, or an increased presence of symptoms must be detected, to avoid prolonged recovery courses. School restrictions have to be minimized. Corresponding concepts are already implemented in North America. Comparable concepts are not established in Germany. In addition to well-known standard return-to-play protocols for sport re-integration, it is urgently recommended to integrate gradual return-to-learn protocols.Thus, academic adaptations and support must be established as well as symptom-oriented organizational and teaching modules.

  15. Fusion of Regionally Specified hPSC-Derived Organoids Models Human Brain Development and Interneuron Migration.

    Science.gov (United States)

    Xiang, Yangfei; Tanaka, Yoshiaki; Patterson, Benjamin; Kang, Young-Jin; Govindaiah, Gubbi; Roselaar, Naomi; Cakir, Bilal; Kim, Kun-Yong; Lombroso, Adam P; Hwang, Sung-Min; Zhong, Mei; Stanley, Edouard G; Elefanty, Andrew G; Naegele, Janice R; Lee, Sang-Hun; Weissman, Sherman M; Park, In-Hyun

    2017-09-07

    Organoid techniques provide unique platforms to model brain development and neurological disorders. Whereas several methods for recapitulating corticogenesis have been described, a system modeling human medial ganglionic eminence (MGE) development, a critical ventral brain domain producing cortical interneurons and related lineages, has been lacking until recently. Here, we describe the generation of MGE and cortex-specific organoids from human pluripotent stem cells that recapitulate the development of MGE and cortex domains, respectively. Population and single-cell RNA sequencing (RNA-seq) profiling combined with bulk assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) analyses revealed transcriptional and chromatin accessibility dynamics and lineage relationships during MGE and cortical organoid development. Furthermore, MGE and cortical organoids generated physiologically functional neurons and neuronal networks. Finally, fusing region-specific organoids followed by live imaging enabled analysis of human interneuron migration and integration. Together, our study provides a platform for generating domain-specific brain organoids and modeling human interneuron migration and offers deeper insight into molecular dynamics during human brain development. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Treatment of pathological gambling - integrative systemic model.

    Science.gov (United States)

    Mladenović, Ivica; Lažetić, Goran; Lečić-Toševski, Dušica; Dimitrijević, Ivan

    2015-03-01

    Pathological gambling was classified under impulse control disorders within the International Classification of Diseases (ICD-10) (WHO 1992), but the most recent Diagnostic and Statistical Manual, 5th edition (DSM-V), (APA 2013), has recognized pathological gambling as a first disorder within a new diagnostic category of behavioral addictions - Gambling disorder. Pathological gambling is a disorder in progression, and we hope that our experience in the treatment of pathological gambling in the Daily Hospital for Addictions at The Institute of Mental Health, through the original "Integrative - systemic model" would be of use to colleagues, dealing with this pathology. This model of treatment of pathological gambling is based on multi-systemic approach and it primarily represents an integration of family and cognitive-behavioral therapy, with traces of psychodynamic, existential and pharmacotherapy. The model is based on the book "Pathological gambling - with self-help manual" by Dr Mladenovic and Dr Lazetic, and has been designed in the form of a program that lasts 10 weeks in the intensive phase, and then continues for two years in the form of "extended treatment" ("After care"). The intensive phase is divided into three segments: educational, insight with initial changes and analysis of the achieved changes with the definition of plans and areas that need to be addressed in the extended treatment. "Extended treatment" lasts for two years in the form of group therapy, during which there is a second order change of the identified patient, but also of other family members. Pathological gambling has been treated in the form of systemic-family therapy for more than 10 years at the Institute of Mental Health (IMH), in Belgrade. For second year in a row the treatment is carried out by the modern "Integrative-systemic model". If abstinence from gambling witihin the period of one year after completion of the intensive phase of treatment is taken as the main criterion of

  17. Modeling and Targeting MYC Genes in Childhood Brain Tumors.

    Science.gov (United States)

    Hutter, Sonja; Bolin, Sara; Weishaupt, Holger; Swartling, Fredrik J

    2017-03-23

    Brain tumors are the second most common group of childhood cancers, accounting for about 20%-25% of all pediatric tumors. Deregulated expression of the MYC family of transcription factors, particularly c-MYC and MYCN genes, has been found in many of these neoplasms, and their expression levels are often correlated with poor prognosis. Elevated c-MYC/MYCN initiates and drives tumorigenesis in many in vivo model systems of pediatric brain tumors. Therefore, inhibition of their oncogenic function is an attractive therapeutic target. In this review, we explore the roles of MYC oncoproteins and their molecular targets during the formation, maintenance, and recurrence of childhood brain tumors. We also briefly summarize recent progress in the development of therapeutic approaches for pharmacological inhibition of MYC activity in these tumors.

  18. A Mixed Approach for Modeling Blood Flow in Brain Microcirculation

    Science.gov (United States)

    Lorthois, Sylvie; Peyrounette, Myriam; Davit, Yohan; Quintard, Michel; Groupe d'Etude sur les Milieux Poreux Team

    2015-11-01

    Consistent with its distribution and exchange functions, the vascular system of the human brain cortex is a superposition of two components. At small-scale, a homogeneous and space-filling mesh-like capillary network. At large scale, quasi-fractal branched veins and arteries. From a modeling perspective, this is the superposition of: (a) a continuum model resulting from the homogenization of slow transport in the small-scale capillary network; and (b) a discrete network approach describing fast transport in the arteries and veins, which cannot be homogenized because of their fractal nature. This problematic is analogous to fast conducting wells embedded in a reservoir rock in petroleum engineering. An efficient method to reduce the computational cost is to use relatively large grid blocks for the continuum model. This makes it difficult to accurately couple both components. We solve this issue by adapting the ``well model'' concept used in petroleum engineering to brain specific 3D situations. We obtain a unique linear system describing the discrete network, the continuum and the well model. Results are presented for realistic arterial and venous geometries. The mixed approach is compared with full network models including various idealized capillary networks of known permeability. ERC BrainMicroFlow GA615102.

  19. Dosha brain-types: A neural model of individual differences

    Directory of Open Access Journals (Sweden)

    Frederick T Travis

    2015-01-01

    Full Text Available This paper explores brain patterns associated with the three categories of regulatory principles of the body, mind, and behavior in Ayurveda, called Vata, Pitta, and Kapha dosha. A growing body of research has reported patterns of blood chemistry, genetic expression, physiological states, and chronic diseases associated with each dosha type. Since metabolic and growth factors are controlled by the nervous system, each dosha type should be associated with patterns of functioning of six major areas of the nervous system: The prefrontal cortex, the reticular activating system, the autonomic nervous system, the enteric nervous system, the limbic system, and the hypothalamus. For instance, the prefrontal cortex, which includes the anterior cingulate, ventral medial, and the dorsal lateral cortices, would exhibit a high range of functioning in the Vata brain-type leading to the possibility of being easily overstimulated. The Vata brain-type performs activity quickly. Learns quickly and forgets quickly. Their fast mind gives them an edge in creative problem solving. The Pitta brain-type reacts strongly to all challenges leading to purposeful and resolute actions. They never give up and are very dynamic and goal oriented. The Kapha brain-type is slow and steady leading to methodical thinking and action. They prefer routine and needs stimulation to get going. A model of dosha brain-types could provide a physiological foundation to understand individual differences. This model could help individualize treatment modalities to address different mental and physical dysfunctions. It also could explain differences in behavior seen in clinical as well as in normal populations.

  20. Dosha brain-types: A neural model of individual differences.

    Science.gov (United States)

    Travis, Frederick T; Wallace, Robert Keith

    2015-01-01

    This paper explores brain patterns associated with the three categories of regulatory principles of the body, mind, and behavior in Ayurveda, called Vata, Pitta, and Kapha dosha. A growing body of research has reported patterns of blood chemistry, genetic expression, physiological states, and chronic diseases associated with each dosha type. Since metabolic and growth factors are controlled by the nervous system, each dosha type should be associated with patterns of functioning of six major areas of the nervous system: The prefrontal cortex, the reticular activating system, the autonomic nervous system, the enteric nervous system, the limbic system, and the hypothalamus. For instance, the prefrontal cortex, which includes the anterior cingulate, ventral medial, and the dorsal lateral cortices, would exhibit a high range of functioning in the Vata brain-type leading to the possibility of being easily overstimulated. The Vata brain-type performs activity quickly. Learns quickly and forgets quickly. Their fast mind gives them an edge in creative problem solving. The Pitta brain-type reacts strongly to all challenges leading to purposeful and resolute actions. They never give up and are very dynamic and goal oriented. The Kapha brain-type is slow and steady leading to methodical thinking and action. They prefer routine and needs stimulation to get going. A model of dosha brain-types could provide a physiological foundation to understand individual differences. This model could help individualize treatment modalities to address different mental and physical dysfunctions. It also could explain differences in behavior seen in clinical as well as in normal populations.

  1. A spatio-temporal reference model of the aging brain.

    Science.gov (United States)

    Huizinga, W; Poot, D H J; Vernooij, M W; Roshchupkin, G V; Bron, E E; Ikram, M A; Rueckert, D; Niessen, W J; Klein, S

    2017-12-05

    Both normal aging and neurodegenerative disorders such as Alzheimer's disease (AD) cause morphological changes of the brain. It is generally difficult to distinguish these two causes of morphological change by visual inspection of magnetic resonance (MR) images. To facilitate making this distinction and thus aid the diagnosis of neurodegenerative disorders, we propose a method for developing a spatio-temporal model of morphological differences in the brain due to normal aging. The method utilizes groupwise image registration to characterize morphological variation across brain scans of people with different ages. To extract the deformations that are due to normal aging we use partial least squares regression, which yields modes of deformations highly correlated with age, and corresponding scores for each input subject. Subsequently, we determine a distribution of morphologies as a function of age by fitting smooth percentile curves to these scores. This distribution is used as a reference to which a person's morphology score can be compared. We validate our method on two different datasets, using images from both cognitively normal subjects and patients with Alzheimer disease (AD). Results show that the proposed framework extracts the expected atrophy patterns. Moreover, the morphology scores of cognitively normal subjects are on average lower than the scores of AD subjects, indicating that morphology differences between AD subjects and healthy subjects can be partly explained by accelerated aging. With our methods we are able to assess accelerated brain aging on both population and individual level. A spatio-temporal aging brain model derived from 988 T1-weighted MR brain scans from a large population imaging study (age range 45.9-91.7y, mean age 68.3y) is made publicly available at www.agingbrain.nl. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  2. General solutions to poroviscoelastic model of hydrocephalic human brain tissue.

    Science.gov (United States)

    Mehrabian, Amin; Abousleiman, Younane

    2011-12-21

    Hydrocephalus is a well-known disorder of brain fluidic system. It is commonly associated with complexities in cerebrospinal fluid (CSF) circulation in brain. In this paper, hydrocephalus and shunting surgery which is used in its treatment are modeled. Brain tissues are considered to follow a poroviscoelastic constitutive model in order to address the effects of time dependence of mechanical properties of soft tissues and fluid flow hydraulics. Our solution draws from Biot's theory of poroelasticity, generalized to account for viscoelastic effects through the correspondence principle. Geometrically, the brain is conceived to be spherically symmetric, where the ventricles are assumed to be a hollow concentric space filled with cerebrospinal fluid. A generalized Kelvin model is considered for the rheological properties of brain tissues. The solution presented is useful in the analysis of the disorder of hydrocephalus as well as the treatment associated with it, namely, ventriclostomy surgery. The sensitivity of the solution to various factors such as aqueduct blockage level and trabeculae stiffness is thoroughly analyzed using numerical examples. Results indicate that partial aqueduct stenosis may be a cause of hydrocephalus. However, only severe occlusion of the aqueduct can cause a significant increase in the ventricle and brain's extracellular fluid pressure. Ventriculostomy shunts are commonly used as a remedy to hydrocephalus. They serve to reduce the ventricular pressure to the normal level. However, sensitivity analysis on the shunt's fluid deliverability parameter has shown that inappropriate design or selection of design shunt may cause under-drainage or over-drainage of the ventricles. Excessive drainage of CSF may increase the normal tensile stress on trabeculae. It can cause rupture of superior cerebral veins or damage to trabeculae or even brain tissues which in turn may lead to subdural hematoma, a common side-effect of the surgery. These Post

  3. Development of a fidelity measure for community integration programmes for people with acquired brain injury.

    Science.gov (United States)

    Parvaneh, Shahriar; Cocks, Errol; Buchanan, Angus; Ghahari, Setareh

    2015-01-01

    The paper describes development of the Assessment of Community Integration Programme Attributes (ACIPA) measure based on a descriptive community integration framework. The purpose of this measure is to allow evaluation of community integration programmes for adults with acquired brain injury (ABI). The Community Integration Framework (CIF) was used to design a fidelity evaluation measure through consultation with 37 participants from five stakeholder groups (practitioners, researchers, policy-makers, people with ABI and family members of people with ABI) using semi-structured interviews, focus groups, iterative surveys and a multi-attribute utility (MAU) method. The resultant measure included seven themes and 21 attributes. Each attribute included indicators and probing questions. Weights were assigned to each theme and constituent attributes. Programme evaluation commonly focuses on outcomes, often overlooking analysis of programme processes. Although it requires further psychometric (reliability and validity) development, the Assessment of Community Integration Programme Attributes may be used to assess the relationship between programme processes and specific outcomes and also to inform the development of programmes aiming to enhance community integration for adults with ABI.

  4. Industrial ecology in integrated assessment models

    Science.gov (United States)

    Pauliuk, Stefan; Arvesen, Anders; Stadler, Konstantin; Hertwich, Edgar G.

    2017-01-01

    Technology-rich integrated assessment models (IAMs) address possible technology mixes and future costs of climate change mitigation by generating scenarios for the future industrial system. Industrial ecology (IE) focuses on the empirical analysis of this system. We conduct an in-depth review of five major IAMs from an IE perspective and reveal differences between the two fields regarding the modelling of linkages in the industrial system, focussing on AIM/CGE, GCAM, IMAGE, MESSAGE, and REMIND. IAMs ignore material cycles and recycling, incoherently describe the life-cycle impacts of technology, and miss linkages regarding buildings and infrastructure. Adding IE system linkages to IAMs adds new constraints and allows for studying new mitigation options, both of which may lead to more robust and policy-relevant mitigation scenarios.

  5. Dietetic Internship: Evaluation of an Integrated Model.

    Science.gov (United States)

    Lordly, Daphne J.; Travers, Kim D.

    1998-01-01

    The purpose of this study was to utilize graduate and employer perceptions of outcomes of the Mount Saint Vincent University (MSVU) Co-operative Education (Co-op) Dietetics program to determine if an integrated model was an acceptable alternate method of dietetic education. Acceptable alternate was defined as: "facilitating achievement of entry level competence for dietetic practice". A self-administered, validated and piloted questionnaire was utilized to collect qualitative and quantitative information concerning employability, professional preparedness and program outcomes. Surveys were mailed to all program graduates (1989-1993) (n=24) and their first employers (n=19). Response rates were 96% and 89% respectively. Close-ended questions were analyzed quantitatively by determining frequency distributions. Data were also subjected to Chi-square to identify dependent factors. Qualitative responses to open-ended questions were analyzed by thematic content analysis. Results revealed all graduates were employed by six months after graduation. Competency development, a component of professional preparedness, was rated as average or above average by the majority of graduates and employers. Analysis of open-ended responses indicated that the introduction of experience while students were establishing theoretical foundations was perceived as beneficial. An integration of qualitative findings led to the development of a model depicting how professional competency development, readiness for practice, a realistic approach to dietetic practice and a high standard of practice were developed within an evolving personal and contextual framework. Socialization and mentoring opportunities, evaluation processes and the integration of theory and practice influenced professional development. In conclusion, both employer and graduate responses indicated overall program satisfaction suggesting that the Co-op program is an acceptable alternate method of dietetic education.

  6. MR Vascular Fingerprinting in Stroke and Brain Tumors Models

    Science.gov (United States)

    Lemasson, B.; Pannetier, N.; Coquery, N.; Boisserand, Ligia S. B.; Collomb, Nora; Schuff, N.; Moseley, M.; Zaharchuk, G.; Barbier, E. L.; Christen, T.

    2016-11-01

    In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases.

  7. Impact of geological model uncertainty on integrated catchment hydrological modeling

    Science.gov (United States)

    He, Xin; Jørgensen, Flemming; Refsgaard, Jens Christian

    2014-05-01

    Various types of uncertainty can influence hydrological model performance. Among them, uncertainty originated from geological model may play an important role in process-based integrated hydrological modeling, if the model is used outside the calibration base. In the present study, we try to assess the hydrological model predictive uncertainty caused by uncertainty of the geology using an ensemble of geological models with equal plausibility. The study is carried out in the 101 km2 Norsminde catchment in western Denmark. Geostatistical software TProGS is used to generate 20 stochastic geological realizations for the west side the of study area. This process is done while incorporating the borehole log data from 108 wells and high resolution airborne transient electromagnetic (AEM) data for conditioning. As a result, 10 geological models are generated based solely on borehole data, and another 10 geological models are based on both borehole and AEM data. Distributed surface water - groundwater models are developed using MIKE SHE code for each of the 20 geological models. The models are then calibrated using field data collected from stream discharge and groundwater head observations. The model simulation results are evaluated based on the same two types of field data. The results show that the differences between simulated discharge flows caused by using different geological models are relatively small. The model calibration is shown to be able to account for the systematic bias in different geological realizations and hence varies the calibrated model parameters. This results in an increase in the variance between the hydrological realizations compared to the uncalibrated models that uses the same parameter values in all 20 models. Furthermore, borehole based hydrological models in general show more variance between simulations than the AEM based models; however, the combined total uncertainty, bias plus variance, is not necessarily higher.

  8. Vascular Functions and Brain Integrity in Midlife: Effects of Obesity and Metabolic Syndrome

    Directory of Open Access Journals (Sweden)

    Andreana P. Haley

    2014-01-01

    Full Text Available Intact cognitive function is the best predictor of quality of life and functional ability in older age. Thus, preventing cognitive decline is central to any effort to guarantee successful aging for our growing population of elderly. The purpose of the work discussed in this outlook paper is to bridge knowledge from basic and clinical neuroscience with the aim of improving how we understand, predict, and treat age- and disease-related cognitive impairment. Over the past six years, our research team has focused on intermediate neuroimaging phenotypes of brain vulnerability in midlife and isolating the underlying physiological mechanisms. The ultimate goal of this work was to pave the road for the development of early interventions to enhance cognitive function and preserve brain integrity throughout the lifespan.

  9. Interleukin-34 restores blood-brain barrier integrity by upregulating tight junction proteins in endothelial cells.

    Directory of Open Access Journals (Sweden)

    Shijie Jin

    Full Text Available Interleukin-34 (IL-34 is a newly discovered cytokine as an additional ligand for colony stimulating factor-1 receptor (CSF1R, and its functions are expected to overlap with colony stimulating factor-1/macrophage-colony stimulating factor. We have previously shown that the IL-34 is primarily produced by neurons in the central nervous system (CNS and induces proliferation and neuroprotective properties of microglia which express CSF1R. However, the functions of IL-34 in the CNS are still elucidative. Here we show that CNS capillary endothelial cells also express CSF1R. IL-34 protected blood-brain barrier integrity by restored expression levels of tight junction proteins, which were downregulated by pro-inflammatory cytokines. The novel function of IL-34 on the blood-brain barrier may give us a clue for new therapeutic strategies in neuroinflammatory and neurodegenerative diseases such as multiple sclerosis and Alzheimer's disease.

  10. Toward an integrative science of the developing human mind and brain: Focus on the developing cortex☆

    Science.gov (United States)

    Jernigan, Terry L.; Brown, Timothy T.; Bartsch, Hauke; Dale, Anders M.

    2015-01-01

    Based on the Huttenlocher lecture, this article describes the need for a more integrative scientific paradigm for addressing important questions raised by key observations made over 2 decades ago. Among these are the early descriptions by Huttenlocher of variability in synaptic density in cortex of postmortem brains of children of different ages and the almost simultaneous reports of cortical volume reductions on MR imaging in children and adolescents. In spite of much progress in developmental neurobiology, developmental cognitive neuroscience, and behavioral and imaging genetics, we still do not know how these early observations relate to each other. It is argued that large scale, collaborative research programs are needed to establish the associations between behavioral differences among children and imaging biomarkers, and to link the latter to cellular changes in the developing brain. Examples of progress and challenges remaining are illustrated with data from the Pediatric Imaging, Neurocognition, and Genetics Project (PING). PMID:26347228

  11. Toward an integrative science of the developing human mind and brain: Focus on the developing cortex.

    Science.gov (United States)

    Jernigan, Terry L; Brown, Timothy T; Bartsch, Hauke; Dale, Anders M

    2016-04-01

    Based on the Huttenlocher lecture, this article describes the need for a more integrative scientific paradigm for addressing important questions raised by key observations made over 2 decades ago. Among these are the early descriptions by Huttenlocher of variability in synaptic density in cortex of postmortem brains of children of different ages and the almost simultaneous reports of cortical volume reductions on MR imaging in children and adolescents. In spite of much progress in developmental neurobiology, developmental cognitive neuroscience, and behavioral and imaging genetics, we still do not know how these early observations relate to each other. It is argued that large scale, collaborative research programs are needed to establish the associations between behavioral differences among children and imaging biomarkers, and to link the latter to cellular changes in the developing brain. Examples of progress and challenges remaining are illustrated with data from the Pediatric Imaging, Neurocognition, and Genetics Project (PING). Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. A generic framework for modeling brain deformation as a constrained parametric optimization problem to aid non-diffeomorphic image registration in brain tumor imaging.

    Science.gov (United States)

    Mang, A; Toma, A; Schuetz, T A; Becker, S; Buzug, T M

    2012-01-01

    In the present paper a novel computational framework for modeling tumor induced brain deformation as a biophysical prior for non-rigid image registration is described. More precisely, we aim at providing a generic building block for non-rigid image registration that can be used to resolve inherent irregularities in non-diffeomorphic registration problems that naturally arise in serial and cross-population brain tumor imaging studies due to the presence (or progression) of pathology. The model for the description of brain cancer dynamics on a tissue level is based on an initial boundary value problem (IBVP). The IBVP follows the accepted assumption that the progression of primary brain tumors on a tissue level is governed by proliferation and migration of cancerous cells into surrounding healthy tissue. The model of tumor induced brain deformation is phrased as a parametric, constrained optimization problem. As a basis of comparison and to demonstrate generalizability additional soft constraints (penalties) are considered. A back-tracking line search is implemented in conjunction with a limited memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) method in order to handle the numerically delicate log-barrier strategy for confining volume change. Numerical experiments are performed to test the flexible control of the computed deformation patterns in terms of varying model parameters. The results are qualitatively and quantitatively related to patterns in patient individual magnetic resonance imaging data. Numerical experiments demonstrate the flexible control of the computed deformation patterns. This in turn strongly suggests that the model can be adapted to patient individual imaging patterns of brain tumors. Qualitative and quantitative comparison of the computed cancer profiles to patterns in medical imaging data of an exemplary patient demonstrates plausibility. The designed optimization problem is based on computational tools widely used in non-rigid image

  13. Evaluation of a monthly hydrological model for Integrated Assessment Models

    Science.gov (United States)

    Liu, Y.; Hejazi, M. I.; Li, H. Y.; Zhang, X.; Leng, G.

    2016-12-01

    The Integrated Assessment modeling (IAM) community, which generated the four representative concentration pathways (RCPs), is actively moving toward including endogenous representations of water supply and demand in their economic modeling frameworks. Toward integrating the water supply module, we build an efficient object-oriented and open-source hydrologic model (HM) to be embedded in IAMs - Global Change Assessment Model (GCAM). The main objective for this new HM is to strike a balance between model complexity and computational efficiency; i.e., possessing sufficient fidelity to capture both the annual and the seasonal signals of water fluxes and pools and being highly computationally efficient so that it can be used for large number of simulations or uncertainty quantification analyses. To this end, we build a monthly gridded hydrological model based on the ABCD model with some additional features such as a snow scheme and the effects of land use and land cover change (LULCC) on the hydrological cycle. In this framework, we mainly simulate the pools of soil moisture, snowpack and groundwater storage, and the fluxes of evapotranspiration, recharge to groundwater, direct runoff and groundwater discharge. We assess the performance of the model by comparing the model results against runoff simulation from the model of Variable Infiltration Capacity (VIC) as well as historical streamflow observations at various gauge stations. We will present results on the model performance, the gains of adding different model components (e.g., snow scheme, effects of LULCC), and the variations of hydrological cycle globally over the historical period of 1901-2010.

  14. Dimethyl fumarate attenuates cerebral edema formation by protecting the blood-brain barrier integrity.

    Science.gov (United States)

    Kunze, Reiner; Urrutia, Andrés; Hoffmann, Angelika; Liu, Hui; Helluy, Xavier; Pham, Mirko; Reischl, Stefan; Korff, Thomas; Marti, Hugo H

    2015-04-01

    Brain edema is a hallmark of various neuropathologies, but the underlying mechanisms are poorly understood. We aim to characterize how tissue hypoxia, together with oxidative stress and inflammation, leads to capillary dysfunction and breakdown of the blood-brain barrier (BBB). In a mouse stroke model we show that systemic treatment with dimethyl fumarate (DMF), an antioxidant drug clinically used for psoriasis and multiple sclerosis, significantly prevented edema formation in vivo. Indeed, DMF stabilized the BBB by preventing disruption of interendothelial tight junctions and gap formation, and decreased matrix metalloproteinase activity in brain tissue. In vitro, DMF directly sustained endothelial tight junctions, inhibited inflammatory cytokine expression, and attenuated leukocyte transmigration. We also demonstrate that these effects are mediated via activation of the redox sensitive transcription factor NF-E2 related factor 2 (Nrf2). DMF activated the Nrf2 pathway as shown by up-regulation of several Nrf2 target genes in the brain in vivo, as well as in cerebral endothelial cells and astrocytes in vitro, where DMF also increased protein abundance of nuclear Nrf2. Finally, Nrf2 knockdown in endothelial cells aggravated subcellular delocalization of tight junction proteins during ischemic conditions, and attenuated the protective effect exerted by DMF. Overall, our data suggest that DMF protects from cerebral edema formation during ischemic stroke by targeting interendothelial junctions in an Nrf2-dependent manner, and provide the basis for a completely new approach to treat brain edema. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Reading skill in adult survivors of childhood brain tumor: a theory-based neurocognitive model.

    Science.gov (United States)

    Smith, Kristen M; King, Tricia Z; Jayakar, Reema; Morris, Robin D

    2014-05-01

    This study investigated the relationship between word reading and white matter (WM) integrity within a neuroanatomical-based reading system comparing adult survivors of childhood brain tumors and controls. It was predicted that the association between WM integrity and word reading would be mediated by processing speed, and this indirect effect would be moderated by group. Thirty-seven adult survivors of childhood brain tumor and typically developing adults participated (age M = 24.19 ± 4.51 years, 62% female). DTI Tractography identified the WM tract for 3 of the reading system connections: inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus (AF), and parietotemporal-occipitotemporal connection (PT-OT). Fractional anisotropy values (FA) of the PT-OT tract were significantly correlated with word reading in survivors and controls (r = .45, .58, respectively; p reading in survivors only (r = .59, p reading system in adults. The finding that processing speed was the mechanism by which WM was associated with reading in survivors is in alignment with the developmental cascade model. Current findings bolster the existing theory-based models of reading using innovative diffusion tensor imaging and moderated mediation statistical neurodevelopmental model, establishing the role of processing speed and specific WM pathway integrity in word reading skill.

  16. Lateral fluid percussion: model of traumatic brain injury in mice.

    Science.gov (United States)

    Alder, Janet; Fujioka, Wendy; Lifshitz, Jonathan; Crockett, David P; Thakker-Varia, Smita

    2011-08-22

    Traumatic brain injury (TBI) research has attained renewed momentum due to the increasing awareness of head injuries, which result in morbidity and mortality. Based on the nature of primary injury following TBI, complex and heterogeneous secondary consequences result, which are followed by regenerative processes (1,2). Primary injury can be induced by a direct contusion to the brain from skull fracture or from shearing and stretching of tissue causing displacement of brain due to movement (3,4). The resulting hematomas and lacerations cause a vascular response (3,5), and the morphological and functional damage of the white matter leads to diffuse axonal injury (6-8). Additional secondary changes commonly seen in the brain are edema and increased intracranial pressure (9). Following TBI there are microscopic alterations in biochemical and physiological pathways involving the release of excitotoxic neurotransmitters, immune mediators and oxygen radicals (10-12), which ultimately result in long-term neurological disabilities (13,14). Thus choosing appropriate animal models of TBI that present similar cellular and molecular events in human and rodent TBI is critical for studying the mechanisms underlying injury and repair. Various experimental models of TBI have been developed to reproduce aspects of TBI observed in humans, among them three specific models are widely adapted for rodents: fluid percussion, cortical impact and weight drop/impact acceleration (1). The fluid percussion device produces an injury through a craniectomy by applying a brief fluid pressure pulse on to the intact dura. The pulse is created by a pendulum striking the piston of a reservoir of fluid. The percussion produces brief displacement and deformation of neural tissue (1,15). Conversely, cortical impact injury delivers mechanical energy to the intact dura via a rigid impactor under pneumatic pressure (16,17). The weight drop/impact model is characterized by the fall of a rod with a specific

  17. Integrating Visualizations into Modeling NEST Simulations

    Science.gov (United States)

    Nowke, Christian; Zielasko, Daniel; Weyers, Benjamin; Peyser, Alexander; Hentschel, Bernd; Kuhlen, Torsten W.

    2015-01-01

    Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work. PMID:26733860

  18. Avoiding Boltzmann Brain domination in holographic dark energy models

    Science.gov (United States)

    Horvat, R.

    2015-11-01

    In a spatially infinite and eternal universe approaching ultimately a de Sitter (or quasi-de Sitter) regime, structure can form by thermal fluctuations as such a space is thermal. The models of Dark Energy invoking holographic principle fit naturally into such a category, and spontaneous formation of isolated brains in otherwise empty space seems the most perplexing, creating the paradox of Boltzmann Brains (BB). It is thus appropriate to ask if such models can be made free from domination by Boltzmann Brains. Here we consider only the simplest model, but adopt both the local and the global viewpoint in the description of the Universe. In the former case, we find that if a dimensionless model parameter c, which modulates the Dark Energy density, lies outside the exponentially narrow strip around the most natural c = 1 line, the theory is rendered BB-safe. In the latter case, the bound on c is exponentially stronger, and seemingly at odds with those bounds on c obtained from various observational tests.

  19. Avoiding Boltzmann Brain domination in holographic dark energy models

    Directory of Open Access Journals (Sweden)

    R. Horvat

    2015-11-01

    Full Text Available In a spatially infinite and eternal universe approaching ultimately a de Sitter (or quasi-de Sitter regime, structure can form by thermal fluctuations as such a space is thermal. The models of Dark Energy invoking holographic principle fit naturally into such a category, and spontaneous formation of isolated brains in otherwise empty space seems the most perplexing, creating the paradox of Boltzmann Brains (BB. It is thus appropriate to ask if such models can be made free from domination by Boltzmann Brains. Here we consider only the simplest model, but adopt both the local and the global viewpoint in the description of the Universe. In the former case, we find that if a dimensionless model parameter c, which modulates the Dark Energy density, lies outside the exponentially narrow strip around the most natural c=1 line, the theory is rendered BB-safe. In the latter case, the bound on c is exponentially stronger, and seemingly at odds with those bounds on c obtained from various observational tests.

  20. Integrated semiconductor optical sensors for chronic, minimally-invasive imaging of brain function.

    Science.gov (United States)

    Lee, Thomas T; Levi, Ofer; Cang, Jianhua; Kaneko, Megumi; Stryker, Michael P; Smith, Stephen J; Shenoy, Krishna V; Harris, James S

    2006-01-01

    Intrinsic optical signal (IOS) imaging is a widely accepted technique for imaging brain activity. We propose an integrated device consisting of interleaved arrays of gallium arsenide (GaAs) based semiconductor light sources and detectors operating at telecommunications wavelengths in the near-infrared. Such a device will allow for long-term, minimally invasive monitoring of neural activity in freely behaving subjects, and will enable the use of structured illumination patterns to improve system performance. In this work we describe the proposed system and show that near-infrared IOS imaging at wavelengths compatible with semiconductor devices can produce physiologically significant images in mice, even through skull.

  1. Integration of Simulink Models with Component-based Software Models

    DEFF Research Database (Denmark)

    Marian, Nicolae

    2008-01-01

    , communication and constraints, using computational blocks and aggregates for both discrete and continuous behaviour, different interconnection and execution disciplines for event-based and time-based controllers, and so on, to encompass the demands to more functionality, at even lower prices, and with opposite...... of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical...... to be analyzed. One way of doing that is to integrate in wrapper files the model back into Simulink S-functions, and use its extensive simulation features, thus allowing an early exploration of the possible design choices over multiple disciplines. The paper describes a safe translation of a restricted set...

  2. Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain

    Directory of Open Access Journals (Sweden)

    Laura Fanea

    2012-01-01

    Full Text Available Neurological disorders represent major causes of lost years of healthy life and mortality worldwide. Development of their quantitative interdisciplinary in vivo evaluation is required. Compartment modeling (CM of brain data acquired in vivo using magnetic resonance imaging techniques with clinically available contrast agents can be performed to quantitatively assess brain perfusion. Transport of 1H spins in water molecules across physiological compartmental brain barriers in three different pools was mathematically modeled and theoretically evaluated in this paper and the corresponding theoretical compartment modeling of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI data was analyzed. The pools considered were blood, tissue, and cerebrospinal fluid (CSF. The blood and CSF data were mathematically modeled assuming continuous flow of the 1H spins in these pools. Tissue data was modeled using three CMs. Results in this paper show that transport across physiological brain barriers such as the blood to brain barrier, the extracellular space to the intracellular space barrier, or the blood to CSF barrier can be evaluated quantitatively. Statistical evaluations of this quantitative information may be performed to assess tissue perfusion, barriers' integrity, and CSF flow in vivo in the normal or disease-affected brain or to assess response to therapy.

  3. Modelling Spark Integration in Science Classroom

    Directory of Open Access Journals (Sweden)

    Marie Paz E. Morales

    2014-02-01

    Full Text Available The study critically explored how a PASCO-designed technology (SPARK ScienceLearning System is meaningfully integrated into the teaching of selected topics in Earth and Environmental Science. It highlights on modelling the effectiveness of using the SPARK Learning System as a primary tool in learning science that leads to learning and achievement of the students. Data and observation gathered and correlation of the ability of the technology to develop high intrinsic motivation to student achievement were used to design framework on how to meaningfully integrate SPARK ScienceLearning System in teaching Earth and Environmental Science. Research instruments used in this study were adopted from standardized questionnaires available from literature. Achievement test and evaluation form were developed and validated for the purpose of deducing data needed for the study. Interviews were done to delve into the deeper thoughts and emotions of the respondents. Data from the interviews served to validate all numerical data culled from this study. Cross-case analysis of the data was done to reveal some recurring themes, problems and benefits derived by the students in using the SPARK Science Learning System to further establish its effectiveness in the curriculum as a forerunner to the shift towards the 21st Century Learning.

  4. Genetic mouse models of brain ageing and Alzheimer's disease.

    Science.gov (United States)

    Bilkei-Gorzo, Andras

    2014-05-01

    Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Human cadaver brain infusion model for neurosurgical training.

    Science.gov (United States)

    Olabe, Jon; Olabe, Javier; Sancho, Vidal

    2009-12-01

    Microneurosurgical technique and anatomical knowledge require extensive laboratory training before mastering these skills. There are diverse training models based on synthetic materials, anesthetized animals, cadaver animals, or human cadaver. Human cadaver models are especially beneficial because they are the closest to live surgery with the greatest disadvantage of lacking hemodynamic factors. We developed the "brain infusion model" to provide a simple but realistic training method minimizing animal use or needs for special facilities. Four human cadaveric brains donated for educational purposes were explanted at autopsy. Carotids and vertebral arteries were cannulated with plastic tubes and fixed with suture. Water was flushed through the tubings until the whole arterial vasculature was observed as clean. The cannulated specimens were fixed with formaldehyde. Tap water infusion at a flow rate of 10 L/h was infused through the arterial tubings controlled with a drip regulator filling the arterial tree and leaking into the interstitial and cisternal space. Multiple microneurosurgical procedures were performed by 4 trainees. Cisternal and vascular dissection was executed in a very realistic fashion. Bypass anastomosis was created as well as aneurysm simulation with venous pouches. Vessel and aneurysm clipping and rupture situations were emulated and solution techniques were trained. Standard microsurgical laboratories regularly have scarce opportunities for working with decapitated human cadaver heads but could have human brains readily available. The human brain infusion model presents a realistic microneurosurgical training method. It is inexpensive and easy to set up. Such simplicity provides the adequate environment for developing microsurgical techniques. Copyright 2009 Elsevier Inc. All rights reserved.

  6. Social competence in pediatric brain tumor survivors: application of a model from social neuroscience and developmental psychology.

    Science.gov (United States)

    Hocking, Matthew C; McCurdy, Mark; Turner, Elise; Kazak, Anne E; Noll, Robert B; Phillips, Peter; Barakat, Lamia P

    2015-03-01

    Pediatric brain tumor (BT) survivors are at risk for psychosocial late effects across many domains of functioning, including neurocognitive and social. The literature on the social competence of pediatric BT survivors is still developing and future research is needed that integrates developmental and cognitive neuroscience research methodologies to identify predictors of survivor social adjustment and interventions to ameliorate problems. This review discusses the current literature on survivor social functioning through a model of social competence in childhood brain disorder and suggests future directions based on this model. Interventions pursuing change in survivor social adjustment should consider targeting social ecological factors. © 2014 Wiley Periodicals, Inc.

  7. Social Competence in Pediatric Brain Tumor Survivors: Application of a Model from Social Neuroscience and Developmental Psychology

    Science.gov (United States)

    Hocking, Matthew C.; McCurdy, Mark; Turner, Elise; Kazak, Anne E.; Noll, Robert B.; Phillips, Peter; Barakat, Lamia P.

    2014-01-01

    Pediatric brain tumor (BT) survivors are at risk for psychosocial late effects across many domains of functioning, including neurocognitive and social. The literature on the social competence of pediatric BT survivors is still developing and future research is needed that integrates developmental and cognitive neuroscience research methodologies to identify predictors of survivor social adjustment and interventions to ameliorate problems. This review discusses the current literature on survivor social functioning through a model of social competence in childhood brain disorder and suggests future directions based on this model. Interventions pursuing change in survivor social adjustment should consider targeting social ecological factors. PMID:25382825

  8. Multivariate Modeling and Inference for Brain Networks: ERGMs and Mixed Models

    OpenAIRE

    Simpson, Sean L.

    2017-01-01

    Talk given during the "How To Be a Skeptical Neuroimager: Functional Connectivity & Causal Modelling" Half-Day Educational Course at the 2017 Organisation for Human Brain Mapping meeting, Monday 25 June.

  9. The forgotten artist: Why to consider intentions and interaction in a model of aesthetic experience. Comment on "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

    Science.gov (United States)

    Brattico, Elvira; Brattico, Pauli; Vuust, Peter

    2017-07-01

    In their target article published in this journal issue, Pelowski et al. [1] address the question of how humans experience, and respond to, visual art. They propose a multi-layered model of the representations and processes involved in assessing visual art objects that, furthermore, involves both bottom-up and top-down elements. Their model provides predictions for seven different outcomes of human aesthetic experience, based on few distinct features (schema congruence, self-relevance, and coping necessity), and connects the underlying processing stages to ;specific correlates of the brain; (a similar attempt was previously done for music by [2-4]). In doing this, the model aims to account for the (often profound) experience of an individual viewer in front of an art object.

  10. Callosal Function in Pediatric Traumatic Brain Injury Linked to Disrupted White Matter Integrity.

    Science.gov (United States)

    Dennis, Emily L; Ellis, Monica U; Marion, Sarah D; Jin, Yan; Moran, Lisa; Olsen, Alexander; Kernan, Claudia; Babikian, Talin; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

    2015-07-15

    Traumatic brain injury (TBI) often results in traumatic axonal injury and white matter (WM) damage, particularly to the corpus callosum (CC). Damage to the CC can lead to impaired performance on neurocognitive tasks, but there is a high degree of heterogeneity in impairment following TBI. Here we examined the relation between CC microstructure and function in pediatric TBI. We used high angular resolution diffusion-weighted imaging (DWI) to evaluate the structural integrity of the CC in humans following brain injury in a sample of 32 children (23 males and 9 females) with moderate-to-severe TBI (msTBI) at 1-5 months postinjury, compared with well matched healthy control children. We assessed CC function through interhemispheric transfer time (IHTT) as measured using event-related potentials (ERPs), and related this to DWI measures of WM integrity. Finally, the relation between DWI and IHTT results was supported by additional results of neurocognitive performance assessed using a single composite performance scale. Half of the msTBI participants (16 participants) had significantly slower IHTTs than the control group. This slow IHTT group demonstrated lower CC integrity (lower fractional anisotropy and higher mean diffusivity) and poorer neurocognitive functioning than both the control group and the msTBI group with normal IHTTs. Lower fractional anisotropy-a common sign of impaired WM-and slower IHTTs also predicted poor neurocognitive function. This study reveals that there is a subset of pediatric msTBI patients during the post-acute phase of injury who have markedly impaired CC functioning and structural integrity that is associated with poor neurocognitive functioning. Traumatic brain injury (TBI) is the primary cause of death and disability in children and adolescents. There is considerable heterogeneity in postinjury outcome, which is only partially explained by injury severity. Imaging biomarkers may help explain some of this variance, as diffusion weighted

  11. Integration of sparse electrophysiological measurements with preoperative MRI using 3D surface estimation in deep brain stimulation surgery

    Science.gov (United States)

    Husch, Andreas; Gemmar, Peter; Thunberg, Johan; Hertel, Frank

    2017-03-01

    Intraoperative microelectrode recordings (MER) have been used for several decades to guide neurosurgeons during the implantation of Deep Brain Stimulation (DBS) electrodes, especially when targeting the subthalamic nucleus (STN) to suppress the symptoms of Parkinson's Disease. The standard approach is to use an array of up to five MER electrodes in a fixed configuration. Interpretation of the recorded signals yields a spatially very sparse set of information about the morphology of the respective brain structures in the targeted area. However, no aid is currently available for surgeons to intraoperatively integrate this information with other data available on the patient's individual morphology (e.g. MR imaging data used for surgical planning). This integration might allow surgeons to better determine the most probable position of the electrodes within the target structure during surgery. This paper suggests a method for reconstructing a surface patch from the sparse MER dataset utilizing additional a priori knowledge about the geometrical configuration of the measurement electrodes. The conventional representation of MER measurements as intervals of target region/non-target region is therefore transformed into an equivalent boundary set representation, allowing ecient point-based calculations. Subsequently, the problem is to integrate the resulting patch with a preoperative model of the target structure, which can be formulated as registration problem minimizing a distance measure between the two surfaces. When restricting this registration procedure to translations, which is reasonable given certain geometric considerations, the problem can be solved globally by employing an exhaustive search with arbitrary precision in polynomial time. The proposed method is demonstrated using bilateral STN/Substantia Nigra segmentation data from preoperative MRIs of 17 Patients with simulated MER electrode placement. When using simulated data of heavily perturbed electrodes

  12. Neural Probes with Integrated Temperature Sensors for Monitoring Retina and Brain Implantation and Stimulation.

    Science.gov (United States)

    Wang, Jiaqi; Xie, Hui; Chung, Tsing; Chan, Leanne Lai Hang; Pang, Stella W

    2017-09-01

    Gold (Au) resistive temperature sensors were integrated on flexible polyimide-based neural probes to monitor temperature changes during neural probe implantation and stimulation. Temperature changes were measured as neural probes were implanted to infer the positions of the neural probes, and as the retina or the deep brain region was stimulated electrically. The temperature sensor consisted of a serpentine Au resistor and surrounded by four Au electrodes with 200 and [Formula: see text] diameter (dia.). The Au temperature sensors had temperature coefficient of 0.32%, and they were biocompatible and small in size. In vivo measurements of temperature changes during implantation and stimulation were carried out in the retina and deep brain region in rats. The desired implantation position was reached when temperature measured by the sensor increased to the calibrated level and became stable. There was no temperature increase when low level stimulation current of 8 and [Formula: see text] each for the two 200- and 400- [Formula: see text]-dia. electrodes, respectively, were applied. When higher level stimulation current of 100 and [Formula: see text] each were applied to the two 200- and 400- [Formula: see text]-dia. electrodes, respectively, maximum temperature increases of 1.2 °C in retina and 1 °C in deep brain region were found.

  13. Integrating Health Promotion Into Physical Therapy Practice to Improve Brain Health and Prevent Alzheimer Disease.

    Science.gov (United States)

    McGough, Ellen; Kirk-Sanchez, Neva; Liu-Ambrose, Teresa

    2017-07-01

    Alzheimer disease is the most common cause of dementia, and brain pathology appears years before symptoms are evident. Primary prevention through health promotion can incorporate lifestyle improvement across the lifespan. Risk factor assessment and identifying markers of disease might also trigger preventive measures needed for high-risk individuals and groups. Many potential risk factors are modifiable through exercise, and may be responsive to early intervention strategies to reduce the downward slope toward disability. Through the use of common clinical tests to identify cognitive and noncognitive functional markers of disease, detection and intervention can occur at earlier stages, including preclinical stages of disease. Physical activity and exercise interventions to address modifiable risk factors and impairments can play a pivotal role in the prevention and delay of functional decline, ultimately reducing the incidence of dementia. This article discusses prevention, prediction, plasticity, and participation in the context of preserving brain health and preventing Alzheimer disease and related dementias in aging adults. Rehabilitation professionals have opportunities to slow disease progression through research, practice, and education initiatives. From a clinical perspective, interventions that target brain health through lifestyle changes and exercise interventions show promise for preventing stroke and associated neurovascular diseases in addition to dementia. Physical therapists are well positioned to integrate primary health promotion into practice for the prevention of dementia and other neurological conditions in older adults.

  14. Androgen modulation of social decision making mechanisms in the brain: an integrative and embodied perspective

    Directory of Open Access Journals (Sweden)

    Rui F Oliveira

    2014-07-01

    Full Text Available Apart from their role in reproduction androgens also respond to social challenges and this response has been seen as a way to regulate the expression of behaviour according to the perceived social environment (Challenge hypothesis, Wingfield et al. 1990. This hypothesis implies that social decision-making mechanisms localized in the central nervous system (CNS are open to the influence of peripheral hormones that ultimately are under the control of the CNS through the hypothalamic-pituitary-gonadal axis. Therefore, two puzzling questions emerge at two different levels of biological analysis: (1 Why does the brain, which perceives the social environment and regulates androgen production in the gonad, need feedback information from the gonad to adjust its social decision-making processes? (2 How does the brain regulate gonadal androgen responses to social challenges and how do these feedback into the brain? In this paper, we will address these two questions using the integrative approach proposed by Niko Tinbergen, who proposed that a full understanding of behaviour requires its analysis at both proximate (physiology, ontogeny and ultimate (ecology, evolution levels.

  15. Integrating Brain, Behaviour and Phylogeny to understand the Evolution of Sensory Systems in Birds

    Directory of Open Access Journals (Sweden)

    Douglas Richard Wylie

    2015-08-01

    Full Text Available The comparative anatomy of sensory systems has played a major role in developing theories and principles central to evolutionary neuroscience. This includes the central tenet of many comparative studies, the principle of proper mass, which states that the size of a neural structure reflects its processing capacity. The size of structures within the sensory system is not, however, the only salient variable in sensory evolution. Further, the evolution of the brain and behaviour are intimately tied to phylogenetic history, requiring studies to integrate neuroanatomy with behaviour and phylogeny to gain a more holistic view of brain evolution. Birds have proven to be a useful group for these studies because of widespread interest in their phylogenetic relationships and a wealth of information on the functional organization of most of their sensory pathways. In this review, we examine the principle of proper mass in relation differences in the sensory capabilities among birds. We discuss how neuroanatomy, behaviour and phylogeny can be integrated to understand the evolution of sensory systems in birds providing evidence from visual, auditory and somatosensory systems. We also consider the concept of a trade-off, whereby one sensory system (or subpathway within a sensory system, may be expanded in size, at the expense of others, which are reduced in size.

  16. In vitro models of the blood–brain barrier: An overview of commonly used brain endothelial cell culture models and guidelines for their use

    Science.gov (United States)

    Helms, Hans C; Abbott, N Joan; Burek, Malgorzata; Cecchelli, Romeo; Couraud, Pierre-Olivier; Deli, Maria A; Förster, Carola; Galla, Hans J; Romero, Ignacio A; Shusta, Eric V; Stebbins, Matthew J; Vandenhaute, Elodie; Weksler, Babette

    2016-01-01

    The endothelial cells lining the brain capillaries separate the blood from the brain parenchyma. The endothelial monolayer of the brain capillaries serves both as a crucial interface for exchange of nutrients, gases, and metabolites between blood and brain, and as a barrier for neurotoxic components of plasma and xenobiotics. This “blood-brain barrier” function is a major hindrance for drug uptake into the brain parenchyma. Cell culture models, based on either primary cells or immortalized brain endothelial cell lines, have been developed, in order to facilitate in vitro studies of drug transport to the brain and studies of endothelial cell biology and pathophysiology. In this review, we aim to give an overview of established in vitro blood–brain barrier models with a focus on their validation regarding a set of well-established blood–brain barrier characteristics. As an ideal cell culture model of the blood–brain barrier is yet to be developed, we also aim to give an overview of the advantages and drawbacks of the different models described. PMID:26868179

  17. Integrated Environmental Modelling: human decisions, human challenges

    Science.gov (United States)

    Glynn, Pierre D.

    2015-01-01

    Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.

  18. Nanofibrous gelatine scaffolds integrated with nerve growth factor-loaded alginate microspheres for brain tissue engineering.

    Science.gov (United States)

    Büyüköz, Melda; Erdal, Esra; Alsoy Altinkaya, Sacide

    2016-11-12

    Neural regeneration research is designed in part to develop strategies for therapy after nerve damage due to injury or disease. In this study, a new gelatine-based biomimetic scaffold was fabricated for brain tissue engineering applications. A technique combining thermally induced phase separation and porogen leaching was used to create interconnected macropores and nanofibrous structure. To promote tissue regeneration processes, the scaffolds were integrated with nerve growth factor (NGF)-loaded alginate microspheres. The results showed that nanofibrous matrix could only be obtained when gelatine concentration was at least 7.5% (w/v). The scaffold with a modulus value (1.2 kPa) similar to that of brain tissue (0.5-1 kPa) was obtained by optimizing the heat treatment time, macropore size and gelatine concentration. The encapsulation efficiencies of NGF into 0.1% and 1% alginate microspheres were 85% and 100%, respectively. The release rate of NGF from the microspheres was controlled by the alginate concentration and the poly(L-lysine) coating. The immobilization of the microspheres in the scaffold reduced burst release and significantly extended the release period. The nanofibrous architecture and controlled release of NGF from the microspheres induced neurite extension of PC12 cells, demonstrating that the released NGF was in an active form. The results suggest that the scaffolds prepared in this study may have potential applications in brain tissue engineering due to topologic and mechanical properties similar to brain tissue and pore structure suitable for cell growth and differentiation. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  19. Drosophila melanogaster as a Model Organism of Brain Diseases

    Directory of Open Access Journals (Sweden)

    Werner Paulus

    2009-02-01

    Full Text Available Drosophila melanogaster has been utilized to model human brain diseases. In most of these invertebrate transgenic models, some aspects of human disease are reproduced. Although investigation of rodent models has been of significant impact, invertebrate models offer a wide variety of experimental tools that can potentially address some of the outstanding questions underlying neurological disease. This review considers what has been gleaned from invertebrate models of neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, metabolic diseases such as Leigh disease, Niemann-Pick disease and ceroid lipofuscinoses, tumor syndromes such as neurofibromatosis and tuberous sclerosis, epilepsy as well as CNS injury. It is to be expected that genetic tools in Drosophila will reveal new pathways and interactions, which hopefully will result in molecular based therapy approaches.

  20. Model-integrating software components engineering flexible software systems

    CERN Document Server

    Derakhshanmanesh, Mahdi

    2015-01-01

    In his study, Mahdi Derakhshanmanesh builds on the state of the art in modeling by proposing to integrate models into running software on the component-level without translating them to code. Such so-called model-integrating software exploits all advantages of models: models implicitly support a good separation of concerns, they are self-documenting and thus improve understandability and maintainability and in contrast to model-driven approaches there is no synchronization problem anymore between the models and the code generated from them. Using model-integrating components, software will be

  1. BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology.

    Directory of Open Access Journals (Sweden)

    Matthew Caldwell

    Full Text Available Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time.

  2. Biothermal Model of Patient for Brain Hypothermia Treatment

    Science.gov (United States)

    Wakamatsu, Hidetoshi; Gaohua, Lu

    A biothermal model of patient is proposed and verified for the brain hypothermia treatment, since the conventionally applied biothermal models are inappropriate for their unprecedented application. The model is constructed on the basis of the clinical practice of the pertinent therapy and characterized by the mathematical relation with variable ambient temperatures, in consideration of the clinical treatments such as the vital cardiopulmonary regulation. It has geometrically clear representation of multi-segmental core-shell structure, database of physiological and physical parameters with a systemic state equation setting the initial temperature of each compartment. Its step response gives the time constant about 3 hours in agreement with clinical knowledge. As for the essential property of the model, the dynamic temperature of its face-core compartment is realized, which corresponds to the tympanic membrane temperature measured under the practical anesthesia. From the various simulations consistent with the phenomena of clinical practice, it is concluded that the proposed model is appropriate for the theoretical analysis and clinical application to the brain hypothermia treatment.

  3. Integrated exposure modeling: a model using GIS and GLM.

    Science.gov (United States)

    Holford, Theodore R; Ebisu, Keita; McKay, Lisa A; Gent, Janneane F; Triche, Elizabeth W; Bracken, Michael B; Leaderer, Brian P

    2010-01-15

    Traffic exhaust is a source of air contaminants that have adverse health effects. Quantification of traffic as an exposure variable is complicated by aerosol dispersion related to variation in layout of roads, traffic density, meteorology, and topography. A statistical model is presented that uses Geographic Information Systems (GIS) technology to incorporate variables into a generalized linear model that estimates distribution of traffic-related pollution. Exposure from a source is expressed as an integral of a function proportional to average daily traffic and a nonparametric dispersion function, which takes the form of a step, polynomial, or spline model. The method may be applied using standard regression techniques for fitting generalized linear models. Modifiers of pollutant dispersion such as wind direction, meteorology, and landscape features can also be included. Two examples are given to illustrate the method. The first employs data from a study in which NO(2) (a known pollutant from automobile exhaust) was monitored outside of 138 Connecticut homes, providing a model for estimating NO(2) exposure. In the second example, estimated levels of nitrogen dioxide (NO(2)) from the model, as well as a separate spatial model, were used to analyze traffic-related health effects in a study of 761 infants.

  4. Hierarchical linear modeling (HLM) of longitudinal brain structural and cognitive changes in alcohol-dependent individuals during sobriety

    DEFF Research Database (Denmark)

    Yeh, P.H.; Gazdzinski, S.; Durazzo, T.C.

    2007-01-01

    )-derived brain volume changes and cognitive changes in abstinent alcohol-dependent individuals as a function of smoking status, smoking severity, and drinking quantities. Methods: Twenty non-smoking recovering alcoholics (nsALC) and 30 age-matched smoking recovering alcoholics (sALC) underwent quantitative MRI...... and cognitive assessments at 1 week, 1 month, and 7 months of sobriety. Eight non-smoking light drinking controls were studied at baseline and 7 months later. Brain and ventricle volumes at each time point were quantified using MRI masks, while the boundary shift integral method measured volume changes between...... time points. Using HLM, we modeled volumetric and cognitive outcome measures as a function of cigarette and alcohol use variables. Results: Different hierarchical linear models with unique model structures are presented and discussed. The results show that smaller brain volumes at baseline predict...

  5. Integrated Space Asset Management Database and Modeling

    Science.gov (United States)

    MacLeod, Todd; Gagliano, Larry; Percy, Thomas; Mason, Shane

    2015-01-01

    Effective Space Asset Management is one key to addressing the ever-growing issue of space congestion. It is imperative that agencies around the world have access to data regarding the numerous active assets and pieces of space junk currently tracked in orbit around the Earth. At the center of this issues is the effective management of data of many types related to orbiting objects. As the population of tracked objects grows, so too should the data management structure used to catalog technical specifications, orbital information, and metadata related to those populations. Marshall Space Flight Center's Space Asset Management Database (SAM-D) was implemented in order to effectively catalog a broad set of data related to known objects in space by ingesting information from a variety of database and processing that data into useful technical information. Using the universal NORAD number as a unique identifier, the SAM-D processes two-line element data into orbital characteristics and cross-references this technical data with metadata related to functional status, country of ownership, and application category. The SAM-D began as an Excel spreadsheet and was later upgraded to an Access database. While SAM-D performs its task very well, it is limited by its current platform and is not available outside of the local user base. Further, while modeling and simulation can be powerful tools to exploit the information contained in SAM-D, the current system does not allow proper integration options for combining the data with both legacy and new M&S tools. This paper provides a summary of SAM-D development efforts to date and outlines a proposed data management infrastructure that extends SAM-D to support the larger data sets to be generated. A service-oriented architecture model using an information sharing platform named SIMON will allow it to easily expand to incorporate new capabilities, including advanced analytics, M&S tools, fusion techniques and user interface for

  6. Integration of Simulink Models with Component-based Software Models

    Directory of Open Access Journals (Sweden)

    MARIAN, N.

    2008-06-01

    Full Text Available Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical constructs and process flow, then software code is generated. A Simulink model is a representation of the design or implementation of a physical system that satisfies a set of requirements. A software component-based system aims to organize system architecture and behavior as a means of computation, communication and constraints, using computational blocks and aggregates for both discrete and continuous behavior, different interconnection and execution disciplines for event-based and time-based controllers, and so on, to encompass the demands to more functionality, at even lower prices, and with opposite constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI, University of Southern Denmark. Once specified, the software model has to be analyzed. One way of doing that is to integrate in wrapper files the model back into Simulink S-functions, and use its extensive simulation features, thus allowing an early exploration of the possible design choices over multiple disciplines. The paper describes a safe translation of a restricted set of MATLAB/Simulink blocks to COMDES software components, both for continuous and discrete behavior, and the transformation of the software system into the S

  7. Internet and Social Media Use After Traumatic Brain Injury: A Traumatic Brain Injury Model Systems Study.

    Science.gov (United States)

    Baker-Sparr, Christina; Hart, Tessa; Bergquist, Thomas; Bogner, Jennifer; Dreer, Laura; Juengst, Shannon; Mellick, David; OʼNeil-Pirozzi, Therese M; Sander, Angelle M; Whiteneck, Gale G

    To characterize Internet and social media use among adults with moderate to severe traumatic brain injury (TBI) and to compare demographic and socioeconomic factors associated with Internet use between those with and without TBI. Ten Traumatic Brain Injury Model Systems centers. Persons with moderate to severe TBI (N = 337) enrolled in the TBI Model Systems National Database and eligible for follow-up from April 1, 2014, to March 31, 2015. Prospective cross-sectional observational cohort study. Internet usage survey. The proportion of Internet users with TBI was high (74%) but significantly lower than those in the general population (84%). Smartphones were the most prevalent means of Internet access for persons with TBI. The majority of Internet users with TBI had a profile account on a social networking site (79%), with more than half of the sample reporting multiplatform use of 2 or more social networking sites. Despite the prevalence of Internet use among persons with TBI, technological disparities remain in comparison with the general population. The extent of social media use among persons with TBI demonstrates the potential of these platforms for social engagement and other purposes. However, further research examining the quality of online activities and identifying potential risk factors of problematic use is recommended.

  8. Longitudinal Examination of Resilience After Traumatic Brain Injury: A Traumatic Brain Injury Model Systems Study.

    Science.gov (United States)

    Marwitz, Jennifer H; Sima, Adam P; Kreutzer, Jeffrey S; Dreer, Laura E; Bergquist, Thomas F; Zafonte, Ross; Johnson-Greene, Douglas; Felix, Elizabeth R

    2018-02-01

    To evaluate (1) the trajectory of resilience during the first year after a moderate-severe traumatic brain injury (TBI); (2) factors associated with resilience at 3, 6, and 12 months postinjury; and (3) changing relationships over time between resilience and other factors. Longitudinal analysis of an observational cohort. Five inpatient rehabilitation centers. Patients with TBI (N=195) enrolled in the resilience module of the TBI Model Systems study with data collected at 3-, 6-, and 12-month follow-up. Not applicable. Connor-Davidson Resilience Scale. Initially, resilience levels appeared to be stable during the first year postinjury. Individual growth curve models were used to examine resilience over time in relation to demographic, psychosocial, and injury characteristics. After adjusting for these characteristics, resilience actually declined over time. Higher levels of resilience were related to nonminority status, absence of preinjury substance abuse, lower anxiety and disability level, and greater life satisfaction. Resilience is a construct that is relevant to understanding brain injury outcomes and has potential value in planning clinical interventions. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  9. Cyclosporin safety in a simplified rat brain tumor implantation model

    Directory of Open Access Journals (Sweden)

    Francisco H. C. Felix

    2012-01-01

    Full Text Available Brain cancer is the second neurological cause of death. A simplified animal brain tumor model using W256 (carcinoma 256, Walker cell line was developed to permit the testing of novel treatment modalities. Wistar rats had a cell tumor solution inoculated stereotactically in the basal ganglia (right subfrontal caudate. This model yielded tumor growth in 95% of the animals, and showed absence of extracranial metastasis and systemic infection. Survival median was 10 days. Estimated tumor volume was 17.08±6.7 mm³ on the 7th day and 67.25±19.8 mm³ on 9th day post-inoculation. Doubling time was 24.25 h. Tumor growth induced cachexia, but no hematological or biochemical alterations. This model behaved as an undifferentiated tumor and can be promising for studying tumor cell migration in the central nervous system. Dexamethasone 3.0 mg/kg/day diminished significantly survival in this model. Cyclosporine 10 mg/kg/day administration was safely tolerated.

  10. IDA’s Integrated Risk Assessment and Management Model

    Science.gov (United States)

    2009-06-01

    Management Model James S. Thomason, Project Leader Approved for public release; distribution is unlimited. This work was conducted under IDA’s independent...P-4470 IDA’s Integrated Risk Assessment and Management Model James S. Thomason, Project Leader IDA’s Integrated Risk Assessment and... Management Model INSTITUTE FOR DEFENSE ANALYSES “There has been plenty of risk management talk,

  11. Blast-Associated Shock Waves Result in Increased Brain Vascular Leakage and Elevated ROS Levels in a Rat Model of Traumatic Brain Injury.

    Science.gov (United States)

    Kabu, Shushi; Jaffer, Hayder; Petro, Marianne; Dudzinski, Dave; Stewart, Desiree; Courtney, Amy; Courtney, Michael; Labhasetwar, Vinod

    2015-01-01

    Blast-associated shock wave-induced traumatic brain injury (bTBI) remains a persistent risk for armed forces worldwide, yet its detailed pathophysiology remains to be fully investigated. In this study, we have designed and characterized a laboratory-scale shock tube to develop a rodent model of bTBI. Our blast tube, driven by a mixture of oxygen and acetylene, effectively generates blast overpressures of 20-130 psi, with pressure-time profiles similar to those of free-field blast waves. We tested our shock tube for brain injury response to various blast wave conditions in rats. The results show that blast waves cause diffuse vascular brain damage, as determined using a sensitive optical imaging method based on the fluorescence signal of Evans Blue dye extravasation developed in our laboratory. Vascular leakage increased with increasing blast overpressures and mapping of the brain slices for optical signal intensity indicated nonhomogeneous damage to the cerebral vasculature. We confirmed vascular leakage due to disruption in the blood-brain barrier (BBB) integrity following blast exposure. Reactive oxygen species (ROS) levels in the brain also increased with increasing blast pressures and with time post-blast wave exposure. Immunohistochemical analysis of the brain sections analyzed at different time points post blast exposure demonstrated astrocytosis and cell apoptosis, confirming sustained neuronal injury response. The main advantages of our shock-tube design are minimal jet effect and no requirement for specialized equipment or facilities, and effectively generate blast-associated shock waves that are relevant to battle-field conditions. Overall data suggest that increased oxidative stress and BBB disruption could be the crucial factors in the propagation and spread of neuronal degeneration following blast injury. Further studies are required to determine the interplay between increased ROS activity and BBB disruption to develop effective therapeutic strategies

  12. Blast-Associated Shock Waves Result in Increased Brain Vascular Leakage and Elevated ROS Levels in a Rat Model of Traumatic Brain Injury.

    Directory of Open Access Journals (Sweden)

    Shushi Kabu

    Full Text Available Blast-associated shock wave-induced traumatic brain injury (bTBI remains a persistent risk for armed forces worldwide, yet its detailed pathophysiology remains to be fully investigated. In this study, we have designed and characterized a laboratory-scale shock tube to develop a rodent model of bTBI. Our blast tube, driven by a mixture of oxygen and acetylene, effectively generates blast overpressures of 20-130 psi, with pressure-time profiles similar to those of free-field blast waves. We tested our shock tube for brain injury response to various blast wave conditions in rats. The results show that blast waves cause diffuse vascular brain damage, as determined using a sensitive optical imaging method based on the fluorescence signal of Evans Blue dye extravasation developed in our laboratory. Vascular leakage increased with increasing blast overpressures and mapping of the brain slices for optical signal intensity indicated nonhomogeneous damage to the cerebral vasculature. We confirmed vascular leakage due to disruption in the blood-brain barrier (BBB integrity following blast exposure. Reactive oxygen species (ROS levels in the brain also increased with increasing blast pressures and with time post-blast wave exposure. Immunohistochemical analysis of the brain sections analyzed at different time points post blast exposure demonstrated astrocytosis and cell apoptosis, confirming sustained neuronal injury response. The main advantages of our shock-tube design are minimal jet effect and no requirement for specialized equipment or facilities, and effectively generate blast-associated shock waves that are relevant to battle-field conditions. Overall data suggest that increased oxidative stress and BBB disruption could be the crucial factors in the propagation and spread of neuronal degeneration following blast injury. Further studies are required to determine the interplay between increased ROS activity and BBB disruption to develop effective

  13. TU-G-210-01: Modeling for Breast and Brain HIFU Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Christensen, D. [University of Utah (United States)

    2015-06-15

    Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such as the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)

  14. Resilience Following Traumatic Brain Injury: A Traumatic Brain Injury Model Systems Study.

    Science.gov (United States)

    Kreutzer, Jeffrey S; Marwitz, Jennifer H; Sima, Adam P; Bergquist, Thomas F; Johnson-Greene, Douglas; Felix, Elizabeth R; Whiteneck, Gale G; Dreer, Laura E

    2016-05-01

    To examine resilience at 3 months after traumatic brain injury (TBI). Cross-sectional analysis of an ongoing observational cohort. Five inpatient rehabilitation centers, with 3-month follow-up conducted primarily by telephone. Persons with TBI (N=160) enrolled in the resilience module of the TBI Model System study with 3-month follow-up completed. Not applicable. Connor-Davidson Resilience Scale. Resilience scores were lower than those of the general population. A multivariable regression model, adjusting for other predictors, showed that higher education, absence of preinjury substance abuse, and less anxiety at follow-up were significantly related to greater resilience. Analysis suggests that lack of resilience may be an issue for some individuals after moderate to severe TBI. Identifying persons most likely at risk for low resilience may be useful in planning clinical interventions. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  15. Large-scale brain networks in affective and social neuroscience: towards an integrative functional architecture of the brain.

    Science.gov (United States)

    Barrett, Lisa Feldman; Satpute, Ajay Bhaskar

    2013-06-01

    Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing

    Directory of Open Access Journals (Sweden)

    Liao Chun-Chih

    2011-08-01

    Full Text Available Abstract Background In recent years, magnetic resonance imaging (MRI has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images. This paper uses an algorithm integrating fuzzy-c-mean (FCM and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain. Methods The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT on a pixel level. Overall data were then evaluated using a quantified system. Results The quantified parameters, including the "percent match" (PM and "correlation ratio" (CR, suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain. Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related. Conclusions Results indicated

  17. A monolithic integrated low-voltage deep brain stimulator with wireless power and data transmission

    Science.gov (United States)

    Zhang, Zhang; Ye, Tan; Jianmin, Zeng; Xu, Han; Xin, Cheng; Guangjun, Xie

    2016-09-01

    A monolithic integrated low-voltage deep brain stimulator with wireless power and data transmission is presented. Data and power are transmitted to the stimulator by mutual inductance coupling, while the in-vitro controller encodes the stimulation parameters. The stimulator integrates the digital control module and can generate the bipolar current with equal amplitude in four channels. In order to reduce power consumption, a novel controlled threshold voltage cancellation rectifier is proposed in this paper to provide the supply voltage of the stimulator. The monolithic stimulator was fabricated in a SMIC 0.18 μm 1-poly 6-metal mixed-signal CMOS process, occupying 0.23 mm2, and consumes 180 μW on average. Compared with previously published stimulators, this design has advantages of large stimulated current (0-0.8 mA) with the double low-voltage supply (1.8 and 3.3 V), and high-level integration. Project supported by the National Natural Science Foundation of China (Nos. 61404043, 61401137), the Key Laboratory of Infrared Imaging Materials and Detectors, Shanghai Institute of Technical Physics, Chinese Academy of Sciences (Nos. IIMDKFJJ-13-06, IIMDKFJJ-14-03), and the Fundamental Research Funds for the Central Universities (No. 2015HGZX0026).

  18. Numerical time integration for air pollution models

    NARCIS (Netherlands)

    J.G. Verwer (Jan); W. Hundsdorfer (Willem); J.G. Blom (Joke)

    1998-01-01

    textabstractDue to the large number of chemical species and the three space dimensions, off-the-shelf stiff ODE integrators are not feasible for the numerical time integration of stiff systems of advection-diffusion-reaction equations [ fracpar{c{t + nabla cdot left( vu{u c right) = nabla cdot left(

  19. Integrated modelling requires mass collaboration (Invited)

    Science.gov (United States)

    Moore, R. V.

    2009-12-01

    add, “and are the plans sustainable?” To return to the present, although, it is now possible to ask the first question and obtain an answer through linked modelling; we are still at a very early stage and the associated uncertainties are large. The process of linking and running linked systems is not yet the simple, reliable process needed for widespread uptake. At this point, it is useful to look back over the development process which has taken us from paper maps to GIS and Google Maps; it was the result of tens of thousands of PhD and MSc projects over forty years. During the development of the OpenMI, it was quickly appreciated that to transform integrated modelling from something possible in a research lab to something that had the ease of use and reliability of Google Maps would require a similar process but on a far greater scale; one far larger than any single organisation or state could support. A dramatic change to the research and development process would be needed. Using the OpenMI Association’s strategy as an example, the presentation will describe how through openness, sharing and mass collaboration made possible by inexpensive communications and computing power and adoption of a minimum set of standards, the innovation and enterprise of thousands of individuals across the world can be brought to bear upon the problems.

  20. Characterizing functional integrity: intraindividual brain signal variability predicts memory performance in patients with medial temporal lobe epilepsy.

    Science.gov (United States)

    Protzner, Andrea B; Kovacevic, Natasa; Cohn, Melanie; McAndrews, Mary Pat

    2013-06-05

    Computational modeling suggests that variability in brain signals provides important information regarding the system's capacity to adopt different network configurations that may promote optimal responding to stimuli. Although there is limited empirical work on this construct, a recent study indicates that age-related decreases in variability across the adult lifespan correlate with less efficient and less accurate performance. Here, we extend this construct to the assessment of cerebral integrity by comparing fMRI BOLD variability and fMRI BOLD amplitude in their ability to account for differences in functional capacity in patients with focal unilateral medial temporal dysfunction. We were specifically interested in whether either of these BOLD measures could identify a link between the affected medial temporal region and memory performance (as measured by a clinical test of verbal memory retention). Using partial least-squares analyses, we found that variability in a set of regions including the left hippocampus predicted verbal retention and, furthermore, this relationship was similar across a range of cognitive tasks measured during scanning (i.e., the same pattern was seen in fixation, autobiographical recall, and word generation). In contrast, signal amplitude in the hippocampus did not predict memory performance, even for a task that reliably activates the medial temporal lobes (i.e., autobiographical recall). These findings provide a powerful validation of the concept that variability in brain signals reflects functional integrity. Furthermore, this measure can be characterized as a robust biomarker in this clinical setting because it reveals the same pattern regardless of cognitive challenge or task engagement during scanning.

  1. CREATING EFFECTIVE MODELS OF VERTICAL INTEGRATED STRUCTURES IN UKRAINE

    Directory of Open Access Journals (Sweden)

    D. V. Koliesnikov

    2011-01-01

    Full Text Available The results of scientific research aimed at development of methodology-theoretical mechanisms of building the effective models of vertically-integrated structures are presented. A presence of vertically-integrated structures on natural-monopolistic markets at private and governmental sectors of economy and priority directions of integration are given.

  2. A simulation model for analysing brain structure deformations

    Science.gov (United States)

    Di Bona, Sergio; Lutzemberger, Ludovico; Salvetti, Ovidio

    2003-12-01

    Recent developments of medical software applications—from the simulation to the planning of surgical operations—have revealed the need for modelling human tissues and organs, not only from a geometric point of view but also from a physical one, i.e. soft tissues, rigid body, viscoelasticity, etc. This has given rise to the term 'deformable objects', which refers to objects with a morphology, a physical and a mechanical behaviour of their own and that reflects their natural properties. In this paper, we propose a model, based upon physical laws, suitable for the realistic manipulation of geometric reconstructions of volumetric data taken from MR and CT scans. In particular, a physically based model of the brain is presented that is able to simulate the evolution of different nature pathological intra-cranial phenomena such as haemorrhages, neoplasm, haematoma, etc and to describe the consequences that are caused by their volume expansions and the influences they have on the anatomical and neuro-functional structures of the brain.

  3. A simulation model for analysing brain structure deformations

    Energy Technology Data Exchange (ETDEWEB)

    Bona, Sergio Di [Institute for Information Science and Technologies, Italian National Research Council (ISTI-8211-CNR), Via G Moruzzi, 1-56124 Pisa (Italy); Lutzemberger, Ludovico [Department of Neuroscience, Institute of Neurosurgery, University of Pisa, Via Roma, 67-56100 Pisa (Italy); Salvetti, Ovidio [Institute for Information Science and Technologies, Italian National Research Council (ISTI-8211-CNR), Via G Moruzzi, 1-56124 Pisa (Italy)

    2003-12-21

    Recent developments of medical software applications from the simulation to the planning of surgical operations have revealed the need for modelling human tissues and organs, not only from a geometric point of view but also from a physical one, i.e. soft tissues, rigid body, viscoelasticity, etc. This has given rise to the term 'deformable objects', which refers to objects with a morphology, a physical and a mechanical behaviour of their own and that reflects their natural properties. In this paper, we propose a model, based upon physical laws, suitable for the realistic manipulation of geometric reconstructions of volumetric data taken from MR and CT scans. In particular, a physically based model of the brain is presented that is able to simulate the evolution of different nature pathological intra-cranial phenomena such as haemorrhages, neoplasm, haematoma, etc and to describe the consequences that are caused by their volume expansions and the influences they have on the anatomical and neuro-functional structures of the brain.

  4. A murine model for virotherapy of malignant brain tumors

    Directory of Open Access Journals (Sweden)

    E. Gambini

    2011-01-01

    Full Text Available Glioblastomas (GBMs are very aggressive and almost incurable brain tumors. The development of new therapeutical approaches capable of selectively killing cancer cells could represent a step forward to fight cancer. With this aim we tested the efficacy of a novel oncolytic therapy based on recombinant herpes simplex viruses (HSVs infecting exclusively cells expressing the human receptor HER-2 [1, 2], overexpressed in about 15% of GBM model based on PDGF-B embryonic transduction [4, 5]. We engineered cell cultures derived from this model to express HER-2 and we injected intracranically such cultures in NOD/SCID mice. We evaluated the efficacy of R-LM113, a recombinant HSV directed to HER-2, in this glioma model expressing HER-2. We demostrated that mice injected with engineered glioma cells infected with R-LM113 developed glioma with a statistically significant delay compared to mice injected with non-infected engineered glioma cells.

  5. A Fuzzy Integral Ensemble Method in Visual P300 Brain-Computer Interface.

    Science.gov (United States)

    Cavrini, Francesco; Bianchi, Luigi; Quitadamo, Lucia Rita; Saggio, Giovanni

    2016-01-01

    We evaluate the possibility of application of combination of classifiers using fuzzy measures and integrals to Brain-Computer Interface (BCI) based on electroencephalography. In particular, we present an ensemble method that can be applied to a variety of systems and evaluate it in the context of a visual P300-based BCI. Offline analysis of data relative to 5 subjects lets us argue that the proposed classification strategy is suitable for BCI. Indeed, the achieved performance is significantly greater than the average of the base classifiers and, broadly speaking, similar to that of the best one. Thus the proposed methodology allows realizing systems that can be used by different subjects without the need for a preliminary configuration phase in which the best classifier for each user has to be identified. Moreover, the ensemble is often capable of detecting uncertain situations and turning them from misclassifications into abstentions, thereby improving the level of safety in BCI for environmental or device control.

  6. Selectionist models of perceptual and motor systems and implications for functionalist theories of brain function

    Science.gov (United States)

    Reeke, George N.; Sporns, Olaf

    1990-06-01

    Functionalism is at present widely accepted as a working basis for cognitive science and artificial intelligence. This view holds that psychological phenomena can be adequately described in terms of functional processes carried out in the brain, and that these processes can be understood independently of the detailed structure and mode of development of the brain. In the functionalist view, the brain is analogous to a computer; both can properly be described at the level of symbolic representations and algorithms. However, an analysis of the structure, development, and evolution of the brain makes it highly unlikely that it could be a Turing machine or that brain algorithms could be either acquired by experience in the world or transmitted between generations. An alternative view is that the brain is a selective system in which two different domains of stochastic variation, the world and neural repertoires, become mapped onto each other in an individual, historical manner. Neural systems capable of such mapping can generalize and can deal with novelty in an open-ended environment. Several models have been constructed to test these ideas, including automata of a new kind that can recognize and associate patterns of sensory input by selective mechanisms. In an approach called synthetic neural modelling, the environment, the phenotype, and the nervous system of such an automaton are integrated into a single computer model. One example is Darwin III, a sessile “creature” with an eye and a multi-jointed arm having a sense of touch; its environment consists of simple shapes moving on a featureless background; its nervous system consists of some 50 000 cells of 50 different kinds connected by about 620 000 synaptic junctions. Darwin III can be trained to track moving objects with its eye, to reach out and touch objects with its arm, to categorize objects according to combinations of visual and tactile cues, and to respond in a positive or negative way to such objects

  7. Integrated Human Futures Modeling in Egypt

    Energy Technology Data Exchange (ETDEWEB)

    Passell, Howard D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Aamir, Munaf Syed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bernard, Michael Lewis [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Beyeler, Walter E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Fellner, Karen Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hayden, Nancy Kay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jeffers, Robert Fredric [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Keller, Elizabeth James Kistin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mitchell, Michael David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Silver, Emily [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tidwell, Vincent C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Villa, Daniel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vugrin, Eric D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Engelke, Peter [Atlantic Council, Washington, D.C. (United States); Burrow, Mat [Atlantic Council, Washington, D.C. (United States); Keith, Bruce [United States Military Academy, West Point, NY (United States)

    2016-01-01

    The Integrated Human Futures Project provides a set of analytical and quantitative modeling and simulation tools that help explore the links among human social, economic, and ecological conditions, human resilience, conflict, and peace, and allows users to simulate tradeoffs and consequences associated with different future development and mitigation scenarios. In the current study, we integrate five distinct modeling platforms to simulate the potential risk of social unrest in Egypt resulting from the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile in Ethiopia. The five platforms simulate hydrology, agriculture, economy, human ecology, and human psychology/behavior, and show how impacts derived from development initiatives in one sector (e.g., hydrology) might ripple through to affect other sectors and how development and security concerns may be triggered across the region. This approach evaluates potential consequences, intended and unintended, associated with strategic policy actions that span the development-security nexus at the national, regional, and international levels. Model results are not intended to provide explicit predictions, but rather to provide system-level insight for policy makers into the dynamics among these interacting sectors, and to demonstrate an approach to evaluating short- and long-term policy trade-offs across different policy domains and stakeholders. The GERD project is critical to government-planned development efforts in Ethiopia but is expected to reduce downstream freshwater availability in the Nile Basin, fueling fears of negative social and economic impacts that could threaten stability and security in Egypt. We tested these hypotheses and came to the following preliminary conclusions. First, the GERD will have an important short-term impact on water availability, food production, and hydropower production in Egypt, depending on the short- term reservoir fill rate. Second, the GERD will have a very small impact on

  8. Integration and segregation of large-scale brain networks during short-term task automatization.

    Science.gov (United States)

    Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

    2016-11-03

    The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

  9. Sixty minutes of what? A developing brain perspective for activating children with an integrative exercise approach.

    Science.gov (United States)

    Myer, Gregory D; Faigenbaum, Avery D; Edwards, Nicholas M; Clark, Joseph F; Best, Thomas M; Sallis, Robert E

    2015-12-01

    Current recommendations for physical activity in children overlook the critical importance of motor skill acquisition early in life. Instead, they focus on the quantitative aspects of physical activity (eg, accumulate 60 min of daily moderate to vigorous physical activity) and selected health-related components of physical fitness (eg, aerobic fitness, muscular strength, muscular endurance, flexibility and body composition). This focus on exercise quantity in youth may limit considerations of qualitative aspects of programme design which include (1) skill development, (2) socialisation and (3) enjoyment of exercise. The timing of brain development and associated neuroplasticity for motor skill learning makes the preadolescence period a critical time to develop and reinforce fundamental movement skills in boys and girls. Children who do not participate regularly in structured motor skill-enriched activities during physical education classes or diverse youth sports programmes may never reach their genetic potential for motor skill control which underlies sustainable physical fitness later in life. The goals of this review are twofold: (1) challenge current dogma that is currently focused on the quantitative rather than qualitative aspects of physical activity recommendations for youth and (2) synthesise the latest evidence regarding the brain and motor control that will provide the foundation for integrative exercise programming that provide a framework sustainable activity for life. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  10. Integration of Intention and Outcome for Moral Judgment in Frontotemporal Dementia: Brain Structural Signatures.

    Science.gov (United States)

    Baez, Sandra; Kanske, Philipp; Matallana, Diana; Montañes, Patricia; Reyes, Pablo; Slachevsky, Andrea; Matus, Cristian; Vigliecca, Nora Silvana; Torralva, Teresa; Manes, Facundo; Ibanez, Agustin

    2016-01-01

    Moral judgment has been proposed to rely on a distributed brain network. This function is impaired in behavioral variant frontotemporal dementia (bvFTD), a condition involving damage to some regions of this network. However, no studies have investigated moral judgment in bvFTD via structural neuroimaging. We compared the performance of 21 bvFTD patients and 19 controls on a moral judgment task involving scenarios that discriminate between the contributions of intentions and outcomes. Voxel-based morphometry was used to assess (a) the atrophy pattern in bvFTD patients, (b) associations between gray matter (GM) volume and moral judgments, and (c) structural differences between bvFTD subgroups (patients with relatively preserved moral judgment and patients with severer moral judgment impairments). Patients judged attempted harm as more permissible and accidental harm as less permissible than controls. The groups' performance on accidental harm was associated with GM volume in the precuneus. In controls, it was al- so associated with the ventromedial prefrontal cortex (VMPFC). Also, both groups' performance on attempted harm was associated with GM volume in the temporoparietal junction. Patients exhibiting worse performance displayed smaller GM volumes in the precuneus and temporal pole. Results suggest that moral judgment abnormalities in bvFTD are associated with impaired integration of intentions and outcomes, which depends on an extended brain network. In bvFTD, moral judgment seems to critically depend on areas beyond the VMPFC. © 2016 S. Karger AG, Basel.

  11. Integrated PET/MRI for planning navigated biopsies in pediatric brain tumors.

    Science.gov (United States)

    Preuss, Matthias; Werner, Peter; Barthel, Henryk; Nestler, Ulf; Christiansen, Holger; Hirsch, Franz Wolfgang; Fritzsch, Dominik; Hoffmann, Karl-Titus; Bernhard, Matthias K; Sabri, Osama

    2014-08-01

    An integrated PET/MRI scanner has been used in selected cases of pediatric brain tumor patients to obtain additional metabolic information about lesions for preoperative biopsy planning and navigation. Four patients, age 9-16 years, received PET/MRI scans employing [(11)C]methionine positron emission tomography (PET) and contrast-enhanced 3D-MR sequences for neuronavigation. PET and MR sequences have been matched for neurosurgical guidance. An infrared camera-based neuronavigation system was employed with co-registered MR and PET images fused to hybrid images for preoperative planning, stereotactic biopsy planning, and/or intraoperative guidance. All patients showed hot spots of increased amino acid transport in PET and contrast-enhancing lesions in MRI. In three of the four patients, PET hot spots were congruent with contrast-enhancing areas in MRI. In two patients, frame-based stereotactic biopsies were taken from thalamo-mesencephalic lesions. One patient underwent second-look surgery for the suspicion of recurrent malignant glioma of the posterior fossa. One incidental frontal mass lesion was subtotally resected. No complications occurred. Hybrid imaging was helpful during the procedures to obtain representative histopathologic specimens and for surgical guidance during resection. Co-registered images did match with intraoperative landmarks, tumor borders, and histopathologic specimens. The integrated PET/MRI scanner offers co-registered multimodal, high-resolution data for neuronavigation with reduced radiation exposure compared to PET/CT scans. One examination session provides all necessary data for neuronavigation and preoperative planning, avoiding additional anesthesia in the small patients. Hybrid multimodality imaging may improve safety and yield additional information when obtaining representative histopathologic specimens of brain tumors.

  12. Perinatal programming of emotional brain circuits:An integrative view from systems to molecules

    Directory of Open Access Journals (Sweden)

    Joerg eBock

    2014-02-01

    Full Text Available Environmental influences such as perinatal stress have been shown to program the developing organism to adapt brain and behavioral functions to cope with daily life challenges. Evidence is now accumulating that the specific and individual effects of early life adversity on the functional development of brain and behavior emerge as a function of the type, intensity, timing and the duration of the adverse environment, and that early life stress (ELS is a major risk factor for developing behavioral dysfunctions and mental disorders. Results from clinical as well as experimental studies in animal models support the hypothesis that ELS can induce functional ‘scars’ in prefrontal and limbic brain areas, regions that are essential for emotional control, learning and memory functions. On the other hand, the concept of stress inoculation is emerging from more recent research, which revealed positive functional adaptations in response to early life stress resulting in resilience against stress and other adversities later in life. Moreover, recent studies indicate that early life experiences and the resulting behavioral consequences can be transmitted to the next generation, leading to a transgenerational cycle of adverse or positive adaptations of brain function and behavior. In this review we propose a unifying view of stress vulnerability and resilience by connecting genetic predisposition and programming sensitivity to the context of experience-expectancy and transgenerational epigenetic traits. The adaptive maturation of stress responsive neural and endocrine systems requires environmental challenges to optimize their functions. Repeated environmental challenges can be viewed within the framework of the match/mismatch hypothesis, the outcome, psychopathology or resilience, depends on the respective predisposition and on the context later in life.

  13. Enhanced brain distribution of carboplatin in a primate model after blood-brain barrier disruption using an implantable ultrasound device.

    Science.gov (United States)

    Goldwirt, Lauriane; Canney, Michael; Horodyckid, Catherine; Poupon, Joel; Mourah, Samia; Vignot, Alexandre; Chapelon, Jean-Yves; Carpentier, Alexandre

    2016-01-01

    Glioblastoma is both the most common and aggressive primary brain tumor in adults. Carboplatin chemotherapy has shown only modest efficacy in progressive high-grade gliomas. The limited clinical efficacy of carboplatin may be due to its low concentration in tissue when the drug is delivered intravenously. The aim of this study was to assess whether the tissue concentration of intravenously administered carboplatin could be enhanced by ultrasound-induced blood-brain disruption in a primate model. Carboplatin was administered intravenously for 60 min to a single primate following blood-brain barrier opening induced by an implantable ultrasound device. Blood and brain samples were collected after animal killing, which occurred 60 min after the end of carboplatin administration. Platinum quantification in ultrafiltrate plasma and brain samples was performed using inductively coupled plasma mass spectrometry. The brain concentration of platinum was highly enhanced (5.2×) in the 3.9 cm(3) region sonicated by the US beam, with a higher concentration in more vascularized anatomical structures. At 5 and 10 mm from the US beam axis, platinum concentrations were slightly enhanced (2.2× and 1.3× respectively). This study demonstrates that BBB opening using an implantable ultrasound transducer enhances the brain distribution of carboplatin in a loco-regional manner. Such a treatment approach is of significant interest for the treatment of primary brain tumors and is under current evaluation in a phase 1 clinical trial (NCT02253212).

  14. Marketing and Languages: An Integrative Model.

    Science.gov (United States)

    McCall, Ian

    1988-01-01

    A framework is proposed for an integrated course in which knowledge of a language is consciously related to the processes of interpersonal communication and the cultural aspects of marketing and negotiation. (Editor)

  15. A Computational Model for the Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Based on Functional Brain Volume

    Directory of Open Access Journals (Sweden)

    Lirong Tan

    2017-09-01

    Full Text Available In this paper, we investigated the problem of computer-aided diagnosis of Attention Deficit Hyperactivity Disorder (ADHD using machine learning techniques. With the ADHD-200 dataset, we developed a Support Vector Machine (SVM model to classify ADHD patients from typically developing controls (TDCs, using the regional brain volumes as predictors. Conventionally, the volume of a brain region was considered to be an anatomical feature and quantified using structural magnetic resonance images. One major contribution of the present study was that we had initially proposed to measure the regional brain volumes using fMRI images. Brain volumes measured from fMRI images were denoted as functional volumes, which quantified the volumes of brain regions that were actually functioning during fMRI imaging. We compared the predictive power of functional volumes with that of regional brain volumes measured from anatomical images, which were denoted as anatomical volumes. The former demonstrated higher discriminative power than the latter for the classification of ADHD patients vs. TDCs. Combined with our two-step feature selection approach which integrated prior knowledge with the recursive feature elimination (RFE algorithm, our SVM classification model combining functional volumes and demographic characteristics achieved a balanced accuracy of 67.7%, which was 16.1% higher than that of a relevant model published previously in the work of Sato et al. Furthermore, our classifier highlighted 10 brain regions that were most discriminative in distinguishing between ADHD patients and TDCs. These 10 regions were mainly located in occipital lobe, cerebellum posterior lobe, parietal lobe, frontal lobe, and temporal lobe. Our present study using functional images will likely provide new perspectives about the brain regions affected by ADHD.

  16. Developing engineering processes through integrated modelling of product and process

    DEFF Research Database (Denmark)

    Nielsen, Jeppe Bjerrum; Hvam, Lars

    2012-01-01

    This article aims at developing an operational tool for integrated modelling of product assortments and engineering processes in companies making customer specific products. Integrating a product model in the design of engineering processes will provide a deeper understanding of the engineering...... activities as well as insight into how product features affect the engineering processes. The article suggests possible ways of integrating models of products with models of engineering processes. The models have been tested and further developed in an action research study carried out in collaboration...... with a major international engineering company....

  17. Integrating Seasonal Oscillations into Basel II Behavioural Scoring Models

    Directory of Open Access Journals (Sweden)

    Goran Klepac

    2007-09-01

    Full Text Available The article introduces a new methodology of temporal influence measurement (seasonal oscillations, temporal patterns for behavioural scoring development purposes. The paper shows how significant temporal variables can be recognised and then integrated into the behavioural scoring models in order to improve model performance. Behavioural scoring models are integral parts of the Basel II standard on Internal Ratings-Based Approaches (IRB. The IRB approach much more precisely reflects individual risk bank profile.A solution of the problem of how to analyze and integrate macroeconomic and microeconomic factors represented in time series into behavioural scorecard models will be shown in the paper by using the REF II model.

  18. Integrated modeling of ozonation for optimization of drinking water treatment

    NARCIS (Netherlands)

    van der Helm, A.W.C.

    2007-01-01

    Drinking water treatment plants automation becomes more sophisticated, more on-line monitoring systems become available and integration of modeling environments with control systems becomes easier. This gives possibilities for model-based optimization. In operation of drinking water treatment

  19. Integrated Biosphere Simulator Model (IBIS), Version 2.5

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The Integrated Biosphere Simulator (or IBIS) is designed to be a comprehensive model of the terrestrial biosphere. Tthe model represents a wide range of...

  20. Integrated Biosphere Simulator Model (IBIS), Version 2.5

    Data.gov (United States)

    National Aeronautics and Space Administration — The Integrated Biosphere Simulator (or IBIS) is designed to be a comprehensive model of the terrestrial biosphere. Tthe model represents a wide range of processes,...

  1. Wide-Field Infrared Survey Telescope (WFIRST) Integrated Modeling

    Science.gov (United States)

    Liu, Kuo-Chia; Blaurock, Carl

    2017-01-01

    Contents: introduction to WFIRST (Wide-Field Infrared Survey Telescope) and integrated modeling; WFIRST stability requirement summary; instability mitigation strategies; dynamic jitter results; STOP (structural-thermal-optical performance) (thermal distortion) results; STOP and jitter capability limitations; model validation philosophy.

  2. Integrated equilibrium in a Heckscher-Ohlin-Ricardo model

    OpenAIRE

    K T Soo

    2005-01-01

    This paper shows that, unlike in the Heckscher-Ohlin model, the integrated equilibrium in the Davis (1995) Heckscher-Ohlin-Ricardo model depends crucially on demand patterns. The area defining the integrated equilibrium is smaller, the greater is the weight placed by consumers on the good that has different technologies across countries.

  3. An overview of the model integration process: From pre ...

    Science.gov (United States)

    Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems. The paper provides a review of the literature regarding techniques and methods employed by various modeling system developers to facilitate science software interoperability. The intent of the paper is to illustrate the wide variation in methods and the limiting effect the variation has on inter-framework reuse and interoperability. A series of recommendation

  4. The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI

    DEFF Research Database (Denmark)

    Churchill, Nathan William; Madsen, Kristoffer Hougaard; Mørup, Morten

    2016-01-01

    brain regions where network expression predicts subject age in the experimental data. Thus, the FSIM is effective at summarizing functional connectivity structure in group-level fMRI, with applications in modeling the relationships between network variability and behavioral/demographic variables.......The brain consists of specialized cortical regions that exchange information between each other, reflecting a combination of segregated (local) and integrated (distributed) processes that define brain function. Functional magnetic resonance imaging (fMRI) is widely used to characterize...... these functional relationships, although it is an ongoing challenge to develop robust, interpretable models for high-dimensional fMRI data. Gaussian mixture models (GMMs) are a powerful tool for parcellating the brain, based on the similarity of voxel time series. However, conventional GMMs have limited parametric...

  5. Physical Exercise Keeps the Brain Connected: Biking Increases White Matter Integrity in Patients With Schizophrenia and Healthy Controls.

    Science.gov (United States)

    Svatkova, Alena; Mandl, René C W; Scheewe, Thomas W; Cahn, Wiepke; Kahn, René S; Hulshoff Pol, Hilleke E

    2015-07-01

    It has been shown that learning a new skill leads to structural changes in the brain. However, it is unclear whether it is the acquisition or continuous practicing of the skill that causes this effect and whether brain connectivity of patients with schizophrenia can benefit from such practice. We examined the effect of 6 months exercise on a stationary bicycle on the brain in patients with schizophrenia and healthy controls. Biking is an endemic skill in the Netherlands and thus offers an ideal situation to disentangle the effects of learning vs practice. The 33 participating patients with schizophrenia and 48 healthy individuals were assigned to either one of two conditions, ie, physical exercise or life-as-usual, balanced for diagnosis. Diffusion tensor imaging brain scans were made prior to and after intervention. We demonstrate that irrespective of diagnosis regular physical exercise of an overlearned skill, such as bicycling, significantly increases the integrity, especially of motor functioning related, white matter fiber tracts whereas life-as-usual leads to a decrease in fiber integrity. Our findings imply that exercise of an overlearned physical skill improves brain connectivity in patients and healthy individuals. This has important implications for understanding the effect of fitness programs on the brain in both healthy subjects and patients with schizophrenia. Moreover, the outcome may even apply to the nonphysical realm. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  6. Modeling Brain Responses in an Arithmetic Working Memory Task

    Science.gov (United States)

    Hamid, Aini Ismafairus Abd; Yusoff, Ahmad Nazlim; Mukari, Siti Zamratol-Mai Sarah; Mohamad, Mazlyfarina; Manan, Hanani Abdul; Hamid, Khairiah Abdul

    2010-07-01

    Functional magnetic resonance imaging (fMRI) was used to investigate brain responses due to arithmetic working memory. Nine healthy young male subjects were given simple addition and subtraction instructions in noise and in quiet. The general linear model (GLM) and random field theory (RFT) were implemented in modelling the activation. The results showed that addition and subtraction evoked bilateral activation in Heschl's gyrus (HG), superior temporal gyrus (STG), inferior frontal gyrus (IFG), supramarginal gyrus (SG) and precentral gyrus (PCG). The HG, STG, SG and PCG activate higher number of voxels in noise as compared to in quiet for addition and subtraction except for IFG that showed otherwise. The percentage of signal change (PSC) in all areas is higher in quiet as compared to in noise. Surprisingly addition (not subtraction) exhibits stronger activation.

  7. Planarian brain regeneration as a model system for developmental neurotoxicology

    Science.gov (United States)

    Hagstrom, Danielle; Cochet‐Escartin, Olivier

    2016-01-01

    Abstract Freshwater planarians, famous for their regenerative prowess, have long been recognized as a valuable in vivo animal model to study the effects of chemical exposure. In this review, we summarize the current techniques and tools used in the literature to assess toxicity in the planarian system. We focus on the planarian's particular amenability for neurotoxicology and neuroregeneration studies, owing to the planarian's unique ability to regenerate a centralized nervous system. Zooming in from the organismal to the molecular level, we show that planarians offer a repertoire of morphological and behavioral readouts while also being amenable to mechanistic studies of compound toxicity. Finally, we discuss the open challenges and opportunities for planarian brain regeneration to become an important model system for modern toxicology. PMID:27499880

  8. Integrated Space Asset Management Database and Modeling

    Science.gov (United States)

    Gagliano, L.; MacLeod, T.; Mason, S.; Percy, T.; Prescott, J.

    The Space Asset Management Database (SAM-D) was implemented in order to effectively track known objects in space by ingesting information from a variety of databases and performing calculations to determine the expected position of the object at a specified time. While SAM-D performs this task very well, it is limited by technology and is not available outside of the local user base. Modeling and simulation can be powerful tools to exploit the information contained in SAM-D. However, the current system does not allow proper integration options for combining the data with both legacy and new M&S tools. A more capable data management infrastructure would extend SAM-D to support the larger data sets to be generated by the COI. A service-oriented architecture model will allow it to easily expand to incorporate new capabilities, including advanced analytics, M&S tools, fusion techniques and user interface for visualizations. Based on a web-centric approach, the entire COI will be able to access the data and related analytics. In addition, tight control of information sharing policy will increase confidence in the system, which would encourage industry partners to provide commercial data. SIMON is a Government off the Shelf information sharing platform in use throughout DoD and DHS information sharing and situation awareness communities. SIMON providing fine grained control to data owners allowing them to determine exactly how and when their data is shared. SIMON supports a micro-service approach to system development, meaning M&S and analytic services can be easily built or adapted. It is uniquely positioned to fill this need as an information-sharing platform with a proven track record of successful situational awareness system deployments. Combined with the integration of new and legacy M&S tools, a SIMON-based architecture will provide a robust SA environment for the NASA SA COI that can be extended and expanded indefinitely. First Results of Coherent Uplink from a

  9. Language Model Applications to Spelling with Brain-Computer Interfaces

    Science.gov (United States)

    Mora-Cortes, Anderson; Manyakov, Nikolay V.; Chumerin, Nikolay; Van Hulle, Marc M.

    2014-01-01

    Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies. PMID:24675760

  10. Language Model Applications to Spelling with Brain-Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Anderson Mora-Cortes

    2014-03-01

    Full Text Available Within the Ambient Assisted Living (AAL community, Brain-Computer Interfaces (BCIs have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies.

  11. Language model applications to spelling with Brain-Computer Interfaces.

    Science.gov (United States)

    Mora-Cortes, Anderson; Manyakov, Nikolay V; Chumerin, Nikolay; Van Hulle, Marc M

    2014-03-26

    Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies.

  12. White matter integrity and cognition in mild traumatic brain injury following motor vehicle accident.

    Science.gov (United States)

    Xiong, Kunlin; Zhu, Yongshan; Zhang, Yulong; Yin, Zhiyong; Zhang, Jingna; Qiu, Mingguo; Zhang, Weiguo

    2014-12-03

    The aim of this study is to explore the white matter structure integrity in patients with mild traumatic brain injury (mTBI) using diffusion tensor imaging (DTI), and to analyze the relationship between the white matter structure integrity and cognitive impairment of patients with mTBI. Twenty-five patients with mTBI and 25 healthy control subjects were studied with conventional MR imaging and diffusion tensor imaging. Fractional anisotropy (FA) and mean diffusivity (MD) maps of patients with mTBI were calculated and compared, with these control maps using tract-based spatial statistics (TBSS). Significantly lower fractional anisotropy was found in patients in the uncinate fasciculus, superior longitudinal fasciculus, inferior longitudinal fasciculus, and internal capsule. Mean diffusivity was significantly elevated in the body of corpus callosum, uncinate fasciculus, superior longitudinal fasciculus, and internal capsule in the mTBI group compared with the control group (PMental State Examination (MMSE) in the mTBI patient group (R(2)=0.36, P<0.05). TBSS analysis of DTI suggests that patients with mTBI have focal axonal injury, and the pathophysiology is significantly related to the MMSE and IQ of mTBI patients. Diffusion tensor imaging can be a powerful technique for in vivo detection of mTBI, and can help in the diagnosis of patients with mTBI. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Generation of iPSC-derived Human Brain Organoids to Model Early Neurodevelopmental Disorders.

    Science.gov (United States)

    Gabriel, Elke; Gopalakrishnan, Jay

    2017-04-14

    The restricted availability of suitable in vitro models that can reliably represent complex human brain development is a significant bottleneck that limits the translation of basic brain research into clinical application. While induced pluripotent stem cells (iPSCs) have replaced the ethically questionable human embryonic stem cells, iPSC-based neuronal differentiation studies remain descriptive at the cellular level but fail to adequately provide the details that could be derived from a complex, 3D human brain tissue. This gap is now filled through the application of iPSC-derived, 3D brain organoids, "Brains in a dish," that model many features of complex human brain development. Here, a method for generating iPSC-derived, 3D brain organoids is described. The organoids can help with modeling autosomal recessive primary microcephaly (MCPH), a rare human neurodevelopmental disorder. A widely accepted explanation for the brain malformation in MCPH is a depletion of the neural stem cell pool during the early stages of human brain development, a developmental defect that is difficult to recreate or prove in vitro. To study MCPH, we generated iPSCs from patient-derived fibroblasts carrying a mutation in the centrosomal protein CPAP. By analyzing the ventricular zone of microcephaly 3D brain organoids, we showed the premature differentiation of neural progenitors. These 3D brain organoids are a powerful in vitro system that will be instrumental in modeling congenital brain disorders induced by neurotoxic chemicals, neurotrophic viral infections, or inherited genetic mutations.

  14. In vitro models of the blood-brain barrier

    DEFF Research Database (Denmark)

    Helms, Hans Christian Cederberg; Abbott, N Joan; Burek, Malgorzata

    2016-01-01

    components of plasma and xenobiotics. This "blood-brain barrier" function is a major hindrance for drug uptake into the brain parenchyma. Cell culture models, based on either primary cells or immortalized brain endothelial cell lines, have been developed, in order to facilitate in vitro studies of drug...

  15. Cluster imaging of multi-brain networks (CIMBN: a general framework for hyperscanning and modeling a group of interacting brains

    Directory of Open Access Journals (Sweden)

    Lian eDuan

    2015-07-01

    Full Text Available Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called Cluster Imaging of Multi-brain Networks (CIMBN. CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network’s properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology.

  16. The Bee as a Model to Investigate Brain and Behavioural Asymmetries

    Directory of Open Access Journals (Sweden)

    Elisa Frasnelli

    2014-01-01

    Full Text Available The honeybee Apis mellifera, with a brain of only 960,000 neurons and the ability to perform sophisticated cognitive tasks, has become an excellent model in life sciences and in particular in cognitive neurosciences. It has been used in our laboratories to investigate brain and behavioural asymmetries, i.e., the different functional specializations of the right and the left sides of the brain. It is well known that bees can learn to associate an odour stimulus with a sugar reward, as demonstrated by extension of the proboscis when presented with the trained odour in the so-called Proboscis Extension Reflex (PER paradigm. Bees recall this association better when trained using their right antenna than they do when using their left antenna. They also retrieve short-term memory of this task better when using the right antenna. On the other hand, when tested for long-term memory recall, bees respond better when using their left antenna. Here we review a series of behavioural studies investigating bees’ lateralization, integrated with electrophysiological measurements to study asymmetries of olfactory sensitivity, and discuss the possible evolutionary origins of these asymmetries. We also present morphological data obtained by scanning electron microscopy and two-photon microscopy. Finally, a behavioural study conducted in a social context is summarised, showing that honeybees control context-appropriate social interactions using their right antenna, rather than the left, thus suggesting that lateral biases in behaviour might be associated with requirements of social life.

  17. A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.

    Science.gov (United States)

    Yao, Zizhen; Mich, John K; Ku, Sherman; Menon, Vilas; Krostag, Anne-Rachel; Martinez, Refugio A; Furchtgott, Leon; Mulholland, Heather; Bort, Susan; Fuqua, Margaret A; Gregor, Ben W; Hodge, Rebecca D; Jayabalu, Anu; May, Ryan C; Melton, Samuel; Nelson, Angelique M; Ngo, N Kiet; Shapovalova, Nadiya V; Shehata, Soraya I; Smith, Michael W; Tait, Leah J; Thompson, Carol L; Thomsen, Elliot R; Ye, Chaoyang; Glass, Ian A; Kaykas, Ajamete; Yao, Shuyuan; Phillips, John W; Grimley, Joshua S; Levi, Boaz P; Wang, Yanling; Ramanathan, Sharad

    2017-01-05

    During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/β-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Disruption of White Matter Integrity in Adult Survivors of Childhood Brain Tumors: Correlates with Long-Term Intellectual Outcomes.

    Science.gov (United States)

    King, Tricia Z; Wang, Liya; Mao, Hui

    2015-01-01

    Although chemotherapy and radiation treatment have contributed to increased survivorship, treatment-induced brain injury has been a concern when examining long-term intellectual outcomes of survivors. Specifically, disruption of brain white matter integrity and its relationship to intellectual outcomes in adult survivors of childhood brain tumors needs to be better understood. Fifty-four participants underwent diffusion tensor imaging in addition to structural MRI and an intelligence test (IQ). Voxel-wise group comparisons of fractional anisotropy calculated from DTI data were performed using Tract Based Spatial Statistics (TBSS) on 27 survivors (14 treated with radiation with and without chemotherapy and 13 treated without radiation treatment on average over 13 years since diagnosis) and 27 healthy comparison participants. Whole brain white matter fractional anisotropy (FA) differences were explored between each group. The relationships between IQ and FA in the regions where statistically lower FA values were found in survivors were examined, as well as the role of cumulative neurological factors. The group of survivors treated with radiation with and without chemotherapy had lower IQ relative to the group of survivors without radiation treatment and the healthy comparison group. TBSS identified white matter regions with significantly different mean fractional anisotropy between the three different groups. A lower level of white matter integrity was found in the radiation with or without chemotherapy treated group compared to the group without radiation treatment and also the healthy control group. The group without radiation treatment had a lower mean FA relative to healthy controls. The white matter disruption of the radiation with or without chemotherapy treated survivors was positively correlated with IQ and cumulative neurological factors. Lower long-term intellectual outcomes of childhood brain tumor survivors are associated with lower white matter integrity

  19. Disruption of White Matter Integrity in Adult Survivors of Childhood Brain Tumors: Correlates with Long-Term Intellectual Outcomes.

    Directory of Open Access Journals (Sweden)

    Tricia Z King

    Full Text Available Although chemotherapy and radiation treatment have contributed to increased survivorship, treatment-induced brain injury has been a concern when examining long-term intellectual outcomes of survivors. Specifically, disruption of brain white matter integrity and its relationship to intellectual outcomes in adult survivors of childhood brain tumors needs to be better understood.Fifty-four participants underwent diffusion tensor imaging in addition to structural MRI and an intelligence test (IQ. Voxel-wise group comparisons of fractional anisotropy calculated from DTI data were performed using Tract Based Spatial Statistics (TBSS on 27 survivors (14 treated with radiation with and without chemotherapy and 13 treated without radiation treatment on average over 13 years since diagnosis and 27 healthy comparison participants. Whole brain white matter fractional anisotropy (FA differences were explored between each group. The relationships between IQ and FA in the regions where statistically lower FA values were found in survivors were examined, as well as the role of cumulative neurological factors.The group of survivors treated with radiation with and without chemotherapy had lower IQ relative to the group of survivors without radiation treatment and the healthy comparison group. TBSS identified white matter regions with significantly different mean fractional anisotropy between the three different groups. A lower level of white matter integrity was found in the radiation with or without chemotherapy treated group compared to the group without radiation treatment and also the healthy control group. The group without radiation treatment had a lower mean FA relative to healthy controls. The white matter disruption of the radiation with or without chemotherapy treated survivors was positively correlated with IQ and cumulative neurological factors.Lower long-term intellectual outcomes of childhood brain tumor survivors are associated with lower white

  20. Multi-Modal Integration of EEG-fNIRS for Brain-Computer Interfaces - Current Limitations and Future Directions.

    Science.gov (United States)

    Ahn, Sangtae; Jun, Sung C

    2017-01-01

    Multi-modal integration, which combines multiple neurophysiological signals, is gaining more attention for its potential to supplement single modality's drawbacks and yield reliable results by extracting complementary features. In particular, integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) is cost-effective and portable, and therefore is a fascinating approach to brain-computer interface (BCI). However, outcomes from the integration of these two modalities have yielded only modest improvement in BCI performance because of the lack of approaches to integrate the two different features. In addition, mismatch of recording locations may hinder further improvement. In this literature review, we surveyed studies of the integration of EEG/fNIRS in BCI thoroughly and discussed its current limitations. We also suggested future directions for efficient and successful multi-modal integration of EEG/fNIRS in BCI systems.

  1. Multi-Modal Integration of EEG-fNIRS for Brain-Computer Interfaces – Current Limitations and Future Directions

    Science.gov (United States)

    Ahn, Sangtae; Jun, Sung C.

    2017-01-01

    Multi-modal integration, which combines multiple neurophysiological signals, is gaining more attention for its potential to supplement single modality’s drawbacks and yield reliable results by extracting complementary features. In particular, integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) is cost-effective and portable, and therefore is a fascinating approach to brain-computer interface (BCI). However, outcomes from the integration of these two modalities have yielded only modest improvement in BCI performance because of the lack of approaches to integrate the two different features. In addition, mismatch of recording locations may hinder further improvement. In this literature review, we surveyed studies of the integration of EEG/fNIRS in BCI thoroughly and discussed its current limitations. We also suggested future directions for efficient and successful multi-modal integration of EEG/fNIRS in BCI systems. PMID:29093673

  2. Multi-Modal Integration of EEG-fNIRS for Brain-Computer Interfaces – Current Limitations and Future Directions

    Directory of Open Access Journals (Sweden)

    Sangtae Ahn

    2017-10-01

    Full Text Available Multi-modal integration, which combines multiple neurophysiological signals, is gaining more attention for its potential to supplement single modality’s drawbacks and yield reliable results by extracting complementary features. In particular, integration of electroencephalography (EEG and functional near-infrared spectroscopy (fNIRS is cost-effective and portable, and therefore is a fascinating approach to brain-computer interface (BCI. However, outcomes from the integration of these two modalities have yielded only modest improvement in BCI performance because of the lack of approaches to integrate the two different features. In addition, mismatch of recording locations may hinder further improvement. In this literature review, we surveyed studies of the integration of EEG/fNIRS in BCI thoroughly and discussed its current limitations. We also suggested future directions for efficient and successful multi-modal integration of EEG/fNIRS in BCI systems.

  3. Integration of inmigrants in Spain: the patchwork model

    Directory of Open Access Journals (Sweden)

    Antidio Martínez de Lizarrondo Artola

    2014-10-01

    Full Text Available The main hypothesis of this article is that differences in autonomous communities immigrant integration policies, are due to politic and socio-structural factors. Although, this autonomic diversity doesn’t generate different models, it can be considered as the source of the Spanish integration model, which could be assimilated to the patchwork model. We have demonstrated that the autonomic heterogeneity in the application of the integration policies, influences the fact that the Spanish migratory system is becoming a unique model in the EU. Additional explanatory variables for these differences are the features of the Mediterranean Welfare State and the system of temporary migration

  4. Learning dynamics by theoretical tools of game theory. Comment on "Move me, astonish me...delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by M. Pelowski et al.

    Science.gov (United States)

    Burini, Diletta; De Lillo, Silvana

    2017-07-01

    The VIMAP model presented in the survey [5] aims at analyzing the processes that can occur in the human perception in the front of an artwork. Such a model combines the bottom-up (artwork derived) processes with the top-down mechanisms which describe how individuals adapt or change their own art processing experience. The cognitive flow consists of seven stages connected to five outcomes, which account for all the main ways of responding to art. Moreover this model can also identify the specific regions of the brain that are posited to be main centers of the processes that may coincide with the proposed cognitive checks.

  5. Modeling of a segmented electrode for desynchronizing deep brain stimulation

    Directory of Open Access Journals (Sweden)

    Julia eBuhlmann

    2011-12-01

    Full Text Available Deep brain stimulation (DBS is an effective therapy for medically refrac- tory movement disorders like Parkinson’s disease. The electrodes, implanted in the target area within the human brain, generate an electric field which activates nerve fibers and cell bodies in the proximate vicinity. Even though the different target nuclei display considerable differences in their anatomical structure, only few types of electrodes are currently commercially available. It is desirable to adjust the electric field and in particular the volume of tissue activated around the electrode with respect to the corresponding target nucleus in a such way that side effects can be reduced. Furthermore, a more selective and partial activation of the target structure is desirable for an optimal application of novel stimulation strate- gies, e.g. coordinated reset neuromodulation. Hence we designed a DBS electrode with a segmented design allowing a more selective activation of the target struc- ture. We created a finite element model (FEM of the electrode and analyzed the volume of tissue activated for this electrode design. The segmented electrode ac- tivated an area in a targeted manner, of which the dimension and position relative to the electrode could be controlled by adjusting the stimulation parameters for each contact. According to our computational analysis, this directed stimulation might be superior with respect to the occurrence of side effects and it enables the application of coordinated reset neuromodulation under optimal conditions.

  6. Integration Models for Indigenous Public Health Curricula

    Science.gov (United States)

    Coombe, Leanne; Lee, Vanessa; Robinson, Priscilla

    2017-01-01

    All graduates of Master of Public Health (MPH) programmes in Australia are expected to achieve a core set of Indigenous public health competencies designed to train "judgement safe practitioners". A curriculum framework document was developed alongside the competencies to assist programme providers to integrate appropriate Indigenous…

  7. Human Systems Integration (HSI) Tradeoff Model

    Science.gov (United States)

    2014-03-01

    distribution is unlimited. Release # 88ABW-2014- 1475, dated 7 Apr 2014. on grammatical and software errors and the recommendation to add a screen (Figure 17...SIGNATURE// MATTHEW T. TARANTO, Major, USAF Chief, Human Systems Analysis Division Human Systems Integration Directorate...enhancing the understanding of HSI tradeoffs. At the direction of 711 HPW/HP, the Survivability/ Vulnerability Information Analysis Center (SURVIAC

  8. The Kurzweil integral in financial market modeling

    Czech Academy of Sciences Publication Activity Database

    Krejčí, Pavel; Lamba, H.; Monteiro, Giselle Antunes; Rachinskii, D.

    2016-01-01

    Roč. 141, č. 2 (2016), s. 261-286 ISSN 0862-7959 R&D Projects: GA ČR(CZ) GA15-12227S Institutional support: RVO:67985840 Keywords : hysteresis * Prandtl-Ishlinskii operator * Kurzweil integral Subject RIV: BA - General Mathematics http://hdl.handle.net/10338.dmlcz/145715

  9. Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability.

    Science.gov (United States)

    Heye, Anna K; Thrippleton, Michael J; Armitage, Paul A; Valdés Hernández, Maria Del C; Makin, Stephen D; Glatz, Andreas; Sakka, Eleni; Wardlaw, Joanna M

    2016-01-15

    There is evidence that subtle breakdown of the blood-brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n=201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a "sham" DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and K(Trans) estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low

  10. Knowledge Modeling for the Outcome of Brain Stereotactic Radiosurgery

    Science.gov (United States)

    Hauck, Jillian E.

    Purpose: To build a model that will predict the survival time for patients that were treated with stereotactic radiosurgery for brain metastases using support vector machine (SVM) regression. Methods and Materials: This study utilized data from 481 patients, which were equally divided into training and validation datasets randomly. The SVM model used a Gaussian RBF function, along with various parameters, such as the size of the epsilon insensitive region and the cost parameter (C) that are used to control the amount of error tolerated by the model. The predictor variables for the SVM model consisted of the actual survival time of the patient, the number of brain metastases, the graded prognostic assessment (GPA) and Karnofsky Performance Scale (KPS) scores, prescription dose, and the largest planning target volume (PTV). The response of the model is the survival time of the patient. The resulting survival time predictions were analyzed against the actual survival times by single parameter classification and two-parameter classification. The predicted mean survival times within each classification were compared with the actual values to obtain the confidence interval associated with the model's predictions. In addition to visualizing the data on plots using the means and error bars, the correlation coefficients between the actual and predicted means of the survival times were calculated during each step of the classification. Results: The number of metastases and KPS scores, were consistently shown to be the strongest predictors in the single parameter classification, and were subsequently used as first classifiers in the two-parameter classification. When the survival times were analyzed with the number of metastases as the first classifier, the best correlation was obtained for patients with 3 metastases, while patients with 4 or 5 metastases had significantly worse results. When the KPS score was used as the first classifier, patients with a KPS score of 60 and

  11. A dynamic in vivo-like organotypic blood-brain barrier model to probe metastatic brain tumors

    Science.gov (United States)

    Xu, Hui; Li, Zhongyu; Yu, Yue; Sizdahkhani, Saman; Ho, Winson S.; Yin, Fangchao; Wang, Li; Zhu, Guoli; Zhang, Min; Jiang, Lei; Zhuang, Zhengping; Qin, Jianhua

    2016-11-01

    The blood-brain barrier (BBB) restricts the uptake of many neuro-therapeutic molecules, presenting a formidable hurdle to drug development in brain diseases. We proposed a new and dynamic in vivo-like three-dimensional microfluidic system that replicates the key structural, functional and mechanical properties of the blood-brain barrier in vivo. Multiple factors in this system work synergistically to accentuate BBB-specific attributes-permitting the analysis of complex organ-level responses in both normal and pathological microenvironments in brain tumors. The complex BBB microenvironment is reproduced in this system via physical cell-cell interaction, vascular mechanical cues and cell migration. This model possesses the unique capability to examine brain metastasis of human lung, breast and melanoma cells and their therapeutic responses to chemotherapy. The results suggest that the interactions between cancer cells and astrocytes in BBB microenvironment might affect the ability of malignant brain tumors to traverse between brain and vascular compartments. Furthermore, quantification of spatially resolved barrier functions exists within a single assay, providing a versatile and valuable platform for pharmaceutical development, drug testing and neuroscientific research.

  12. Resuscitation speed affects brain injury in a large animal model of traumatic brain injury and shock

    DEFF Research Database (Denmark)

    Sillesen, Martin; Jin, Guang; Johansson, Pär I

    2014-01-01

    infusion speed increment NS (n¿=¿7). Hemodynamic variables over a 6-hour observation phase were recorded. Following euthanasia, brains were harvested and lesion size as well as brain swelling was measured.ResultsBolus FFP resuscitation resulted in greater brain swelling (22.36¿±¿1.03% vs. 15.58¿±¿2.52%, p...

  13. Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

    Science.gov (United States)

    Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

    2017-10-01

    Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. A Computational Cognitive Model Integrating Different Emotion Regulation Strategies

    NARCIS (Netherlands)

    Abro, A.H.; Manzoor Rajper, A.; Tabatabaei, S.; Treur, J.; Georgeon, Olivier L.

    2015-01-01

    In this paper a cognitive model is introduced which integrates a model for emotion generation with models for three different emotion regulation strategies. Given a stressful situation, humans often apply multiple emotion regulation strategies. The presented computational model has been designed

  15. Integrating decision management with UML modeling concepts and tools

    DEFF Research Database (Denmark)

    Könemann, Patrick

    2009-01-01

    . In this paper, we propose an integration of a decision management and a UML-based modeling tool, based on use cases we distill from an example: the UML modeling tool shall show all decisions related to a model and allow extending or updating them; the decision management tool shall trigger the modeling tool...

  16. Integration of ultra-high field MRI and histology for connectome based research of brain disorders

    Directory of Open Access Journals (Sweden)

    Shan eYang

    2013-09-01

    Full Text Available Ultra-high field magnetic resonance imaging (MRI became increasingly relevant for in vivo neuroscientific research because of improved spatial resolutions. However, this is still the unchallenged domain of histological studies, which long played an important role in the investigation of neuropsychiatric disorders. While the field of biological psychiatry strongly advanced on macroscopic levels, current developments are rediscovering the richness of immunohistological information when attempting a multi-level systematic approach to brain function and dysfunction. For most studies, histology sections lost information on three-dimensional reconstructions. Translating histological sections to 3D-volumes would thus not only allow for multi-stain and multi-subject alignment in post mortem data, but also provide a crucial step in big data initiatives involving the network analyses currently performed with in vivo MRI. We therefore investigated potential pitfalls during integration of MR and histological information where no additional blockface information is available. We demonstrated that strengths and requirements from both methods seem to be ideally merged at a spatial resolution of 200 μm. However, the success of this approach is heavily dependent on choices of hardware, sequence and reconstruction. We provide a fully automated pipeline that optimizes histological 3D reconstructions, providing a potentially powerful solution not only for primary human post mortem research institutions in neuropsychiatric research, but also to help alleviate the massive workloads in neuroanatomical atlas initiatives. We further demonstrate (for the first time the feasibility and quality of ultra-high spatial resolution (150 µm isotopic imaging of the entire human brain MRI at 7T, offering new opportunities for analyses on MR-derived information.

  17. Monoaminergic integration of diet and social signals in the brains of juvenile spadefoot toads.

    Science.gov (United States)

    Burmeister, Sabrina S; Rodriguez Moncalvo, Verónica G; Pfennig, Karin S

    2017-09-01

    Social behavior often includes the production of species-specific signals (e.g. mating calls or visual displays) that evoke context-dependent behavioral responses from conspecifics. Monoamines are important neuromodulators that have been implicated in context-dependent social behavior, yet we know little about the development of monoaminergic systems and whether they mediate the effects of early life experiences on adult behavior. We examined the effects of diet and social signals on monoamines early in development in the plains spadefoot toad (Spea bombifrons), a species in which diet affects the developmental emergence of species recognition and body condition affects the expression of adult mating preferences. To do so, we manipulated the diet of juveniles for 6 weeks following metamorphosis and collected their brains 40 min following the presentation of either a conspecific or a heterospecific call. We measured levels of monoamines and their metabolites using high pressure liquid chromatography from tissue punches of the auditory midbrain (i.e. torus semicircularis), hypothalamus and preoptic area. We found that call type affected dopamine and noradrenaline signaling in the auditory midbrain and that diet affected dopamine and serotonin in the hypothalamus. In the preoptic area, we detected an interaction between diet and call type, indicating that diet modulates how the preoptic area integrates social information. Our results suggest that the responsiveness of monoamine systems varies across the brain and highlight preoptic dopamine and noradrenaline as candidates for mediating effects of early diet experience on later expression of social preferences. © 2017. Published by The Company of Biologists Ltd.

  18. The dynamics of multimodal integration: The averaging diffusion model.

    Science.gov (United States)

    Turner, Brandon M; Gao, Juan; Koenig, Scott; Palfy, Dylan; L McClelland, James

    2017-12-01

    We combine extant theories of evidence accumulation and multi-modal integration to develop an integrated framework for modeling multimodal integration as a process that unfolds in real time. Many studies have formulated sensory processing as a dynamic process where noisy samples of evidence are accumulated until a decision is made. However, these studies are often limited to a single sensory modality. Studies of multimodal stimulus integration have focused on how best to combine different sources of information to elicit a judgment. These studies are often limited to a single time point, typically after the integration process has occurred. We address these limitations by combining the two approaches. Experimentally, we present data that allow us to study the time course of evidence accumulation within each of the visual and auditory domains as well as in a bimodal condition. Theoretically, we develop a new Averaging Diffusion Model in which the decision variable is the mean rather than the sum of evidence samples and use it as a base for comparing three alternative models of multimodal integration, allowing us to assess the optimality of this integration. The outcome reveals rich individual differences in multimodal integration: while some subjects' data are consistent with adaptive optimal integration, reweighting sources of evidence as their relative reliability changes during evidence integration, others exhibit patterns inconsistent with optimality.

  19. Modeling the dynamics of human brain activity with recurrent neural networks

    NARCIS (Netherlands)

    Güçlü, U.; Gerven, M.A.J. van

    2017-01-01

    Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of stimuli to features (feature model) and a linear convolution

  20. Chronic traumatic encephalopathy-integration of canonical traumatic brain injury secondary injury mechanisms with tau pathology.

    Science.gov (United States)

    Kulbe, Jacqueline R; Hall, Edward D

    2017-11-01

    In recent years, a new neurodegenerative tauopathy labeled Chronic Traumatic Encephalopathy (CTE), has been identified that is believed to be primarily a sequela of repeated mild traumatic brain injury (TBI), often referred to as concussion, that occurs in athletes participating in contact sports (e.g. boxing, American football, Australian football, rugby, soccer, ice hockey) or in military combatants, especially after blast-induced injuries. Since the identification of CTE, and its neuropathological finding of deposits of hyperphosphorylated tau protein, mechanistic attention has been on lumping the disorder together with various other non-traumatic neurodegenerative tauopathies. Indeed, brains from suspected CTE cases that have come to autopsy have been confirmed to have deposits of hyperphosphorylated tau in locations that make its anatomical distribution distinct for other tauopathies. The fact that these individuals experienced repetitive TBI episodes during their athletic or military careers suggests that the secondary injury mechanisms that have been extensively characterized in acute TBI preclinical models, and in TBI patients, including glutamate excitotoxicity, intracellular calcium overload, mitochondrial dysfunction, free radical-induced oxidative damage and neuroinflammation, may contribute to the brain damage associated with CTE. Thus, the current review begins with an in depth analysis of what is known about the tau protein and its functions and dysfunctions followed by a discussion of the major TBI secondary injury mechanisms, and how the latter have been shown to contribute to tau pathology. The value of this review is that it might lead to improved neuroprotective strategies for either prophylactically attenuating the development of CTE or slowing its progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Mechanical Model of Traditional Thai Massage for Integrated Healthcare

    OpenAIRE

    Salinee Rattanaphan; Panya Srichandr

    2015-01-01

    In this study, a mechanical model was developed, aiming to provide standardized and programmable traditional Thai massage (TTM) therapy to patients. The TTM was modeled and integrated into a mechanical hand (MH) system, and a prototype massage chair was built and tested for user satisfaction. Three fundamental principles of Thai massage were integrated: pull, press, and pin. Based on these principles, the mechanics of Thai massage was studied and a mathematical model was developed to describe...

  2. Monotonic non-linear transformations as a tool to investigate age-related effects on brain white matter integrity: A Box-Cox investigation.

    Science.gov (United States)

    Morozova, Maria; Koschutnig, Karl; Klein, Elise; Wood, Guilherme

    2016-01-15

    Non-linear effects of age on white matter integrity are ubiquitous in the brain and indicate that these effects are more pronounced in certain brain regions at specific ages. Box-Cox analysis is a technique to increase the log-likelihood of linear relationships between variables by means of monotonic non-linear transformations. Here we employ Box-Cox transformations to flexibly and parsimoniously determine the degree of non-linearity of age-related effects on white matter integrity by means of model comparisons using a voxel-wise approach. Analysis of white matter integrity in a sample of adults between 20 and 89years of age (n=88) revealed that considerable portions of the white matter in the corpus callosum, cerebellum, pallidum, brainstem, superior occipito-frontal fascicle and optic radiation show non-linear effects of age. Global analyses revealed an increase in the average non-linearity from fractional anisotropy to radial diffusivity, axial diffusivity, and mean diffusivity. These results suggest that Box-Cox transformations are a useful and flexible tool to investigate more complex non-linear effects of age on white matter integrity and extend the functionality of the Box-Cox analysis in neuroimaging. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Theory, modeling, and integrated studies in the Arase (ERG) project

    Science.gov (United States)

    Seki, Kanako; Miyoshi, Yoshizumi; Ebihara, Yusuke; Katoh, Yuto; Amano, Takanobu; Saito, Shinji; Shoji, Masafumi; Nakamizo, Aoi; Keika, Kunihiro; Hori, Tomoaki; Nakano, Shin'ya; Watanabe, Shigeto; Kamiya, Kei; Takahashi, Naoko; Omura, Yoshiharu; Nose, Masahito; Fok, Mei-Ching; Tanaka, Takashi; Ieda, Akimasa; Yoshikawa, Akimasa

    2018-02-01

    Understanding of underlying mechanisms of drastic variations of the near-Earth space (geospace) is one of the current focuses of the magnetospheric physics. The science target of the geospace research project Exploration of energization and Radiation in Geospace (ERG) is to understand the geospace variations with a focus on the relativistic electron acceleration and loss processes. In order to achieve the goal, the ERG project consists of the three parts: the Arase (ERG) satellite, ground-based observations, and theory/modeling/integrated studies. The role of theory/modeling/integrated studies part is to promote relevant theoretical and simulation studies as well as integrated data analysis to combine different kinds of observations and modeling. Here we provide technical reports on simulation and empirical models related to the ERG project together with their roles in the integrated studies of dynamic geospace variations. The simulation and empirical models covered include the radial diffusion model of the radiation belt electrons, GEMSIS-RB and RBW models, CIMI model with global MHD simulation REPPU, GEMSIS-RC model, plasmasphere thermosphere model, self-consistent wave-particle interaction simulations (electron hybrid code and ion hybrid code), the ionospheric electric potential (GEMSIS-POT) model, and SuperDARN electric field models with data assimilation. ERG (Arase) science center tools to support integrated studies with various kinds of data are also briefly introduced.[Figure not available: see fulltext.

  4. QMU in Integrated Spacecraft System Models Project

    Data.gov (United States)

    National Aeronautics and Space Administration — ACTA and Sandia National Laboratories propose to quantify and propagate substructure modeling uncertainty for reduced-order substructure models to higher levels of...

  5. Informing pedagogy through the brain-targeted teaching model.

    Science.gov (United States)

    Hardiman, Mariale

    2012-01-01

    Improving teaching to foster creative thinking and problem-solving for students of all ages will require two essential changes in current educational practice. First, to allow more time for deeper engagement with material, it is critical to reduce the vast number of topics often required in many courses. Second, and perhaps more challenging, is the alignment of pedagogy with recent research on cognition and learning. With a growing focus on the use of research to inform teaching practices, educators need a pedagogical framework that helps them interpret and apply research findings. This article describes the Brain-Targeted Teaching Model, a scheme that relates six distinct aspects of instruction to research from the neuro- and cognitive sciences.

  6. Integration models: multicultural and liberal approaches confronted

    Science.gov (United States)

    Janicki, Wojciech

    2012-01-01

    European societies have been shaped by their Christian past, upsurge of international migration, democratic rule and liberal tradition rooted in religious tolerance. Boosting globalization processes impose new challenges on European societies, striving to protect their diversity. This struggle is especially clearly visible in case of minorities trying to resist melting into mainstream culture. European countries' legal systems and cultural policies respond to these efforts in many ways. Respecting identity politics-driven group rights seems to be the most common approach, resulting in creation of a multicultural society. However, the outcome of respecting group rights may be remarkably contradictory to both individual rights growing out from liberal tradition, and to reinforced concept of integration of immigrants into host societies. The hereby paper discusses identity politics upturn in the context of both individual rights and integration of European societies.

  7. Modeling unified interaction for communication service integration

    OpenAIRE

    Rana, Juwel; Kristiansson, Johan; Synnes, Kåre

    2010-01-01

      Social network inspired communication services has made a huge success, allowing users to communicate and share information in new fashion. At the same time, telecom operator's services are becoming more open, which makes it possible to develop improved social networking services and integrate them with mobile platforms. One problem that needs to be addressed when developing such services how to fetch useful social information and make it available for the services running in the cloud o...

  8. Understanding Gulf War Illness: An Integrative Modeling Approach

    Science.gov (United States)

    2016-10-01

    most efficacious. KEYWORDS Autonomic Dysfunction Computational Biology Cytokines Deregulated Balance Diisopropyl Phosphorofluoridate...students in conduct of model Begin 3 and continue 100% Test cholinergic toxins in mice with examination of immune markers in brain and periphery 4-15 50...50% Search for novel treatment courses. Launch repeated searches for optimal treatments using the set of candidate cytokine , hormone/autonomic and

  9. Toward an autonomous brain machine interface: integrating sensorimotor reward modulation and reinforcement learning.

    Science.gov (United States)

    Marsh, Brandi T; Tarigoppula, Venkata S Aditya; Chen, Chen; Francis, Joseph T

    2015-05-13

    For decades, neurophysiologists have worked on elucidating the function of the cortical sensorimotor control system from the standpoint of kinematics or dynamics. Recently, computational neuroscientists have developed models that can emulate changes seen in the primary motor cortex during learning. However, these simulations rely on the existence of a reward-like signal in the primary sensorimotor cortex. Reward modulation of the primary sensorimotor cortex has yet to be characterized at the level of neural units. Here we demonstrate that single units/multiunits and local field potentials in the primary motor (M1) cortex of nonhuman primates (Macaca radiata) are modulated by reward expectation during reaching movements and that this modulation is present even while subjects passively view cursor motions that are predictive of either reward or nonreward. After establishing this reward modulation, we set out to determine whether we could correctly classify rewarding versus nonrewarding trials, on a moment-to-moment basis. This reward information could then be used in collaboration with reinforcement learning principles toward an autonomous brain-machine interface. The autonomous brain-machine interface would use M1 for both decoding movement intention and extraction of reward expectation information as evaluative feedback, which would then update the decoding algorithm as necessary. In the work presented here, we show that this, in theory, is possible. Copyright © 2015 the authors 0270-6474/15/357374-14$15.00/0.

  10. Building an Integrative Model for Managing Exploratory Innovation

    DEFF Research Database (Denmark)

    Zarmeen, Parisha; Turri, Vanessa Gina; Sanchez, Ron

    2014-01-01

    ’ (2008) framework for strategically assessing the benefits of segregation versus integration of innovation processes. We develop and apply our model working with managers in two company contexts to assure the ability of our Integrated Model to identify key organizational and strategic variables that need......Purpose: In this paper we develop an integrated model identifying the key factors involved in managing exploratory innovation processes while also maintaining current business models and processes. Methodology/approach: We first characterize the problem of innovation as consisting of “the four...... central problems” organizations face when trying to manage innovation processes (Van de Ven, 1986). We develop an enhanced version of O’Connor’s (2008) Discovery, Incubation and Acceleration (DIA) model by integrating elements of Sanchez’ (2012) theory of architectural isomorphism as well as Markides...

  11. Model-Based Integration and Interpretation of Data

    DEFF Research Database (Denmark)

    Petersen, Johannes

    2004-01-01

    Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...

  12. Increased Stability and Breakdown of Brain Effective Connectivity During Slow-Wave Sleep: Mechanistic Insights from Whole-Brain Computational Modelling

    OpenAIRE

    Jobst, Beatrice M; Hindriks, Rikkert; Laufs, Helmut; Tagliazucchi, E; Hahn, Gerald; Ponce-Alvarez, Adrián; Stevner, Angus B. A.; Kringelbach, Morten L.; Deco, Gustavo

    2017-01-01

    Recent research has found that the human sleep cycle is characterised by changes in spatiotemporal patterns of brain activity. Yet, we are still missing a mechanistic explanation of the local neuronal dynamics underlying these changes. We used whole-brain computational modelling to study the differences in global brain functional connectivity and synchrony of fMRI activity in healthy humans during wakefulness and slow-wave sleep. We applied a whole-brain model based on the normal form of a su...

  13. The development of integrated health care models in Scotland

    Directory of Open Access Journals (Sweden)

    Kevin J. Woods

    2001-06-01

    Full Text Available Integrated health care is a key policy aim of Scotland's newly devolved government. ‘Partnership working’ is the mechanism that has been selected to achieve this goal. Three illustrative examples of health care integration models developed in Scotland are considered; system organisation and structure; Local Health Care Co-operatives (LHCCs; and Managed Clinical Networks. Using these examples the paper explores the nature of ‘partnership’ and asks if it can deliver integrated care.

  14. Prenatal Exposure of Guinea Pigs to the Organophosphorus Pesticide Chlorpyrifos Disrupts the Structural and Functional Integrity of the Brain

    Science.gov (United States)

    Mullins, Roger J.; Xu, Su; Pereira, Edna F.R.; Pescrille, Joseph D.; Todd, Spencer W.; Mamczarz, Jacek; Albuquerque, Edson X.; Gullapalli, Rao P.

    2015-01-01

    This study was designed to test the hypothesis that prenatal exposure of guinea pigs to the organophosphorus (OP) pesticide chlorpyrifos (CPF) disrupts the structural and functional integrity of the brain. Pregnant guinea pigs were injected with chlorpyrifos (20 mg/kg, s.c.) or vehicle (peanut oil) once per day for ten consecutive days, starting approximately on the 50th day of gestation. Cognitive behavior of female offspring was examined starting at 40–45 post-natal days (PND) using the Morris Water Maze (MWM), and brain structural integrity was analyzed at PND 70 using magnetic resonance imaging (MRI) methods, including T2-weighted anatomical scans and Diffusion Kurtosis Imaging (DKI). The offspring of exposed mothers had significantly decreased body weight and brain volume, particularly in the frontal regions of the brain including the striatum. Furthermore, the offspring demonstrated significant spatial learning deficits in MWM recall compared to the vehicle group. Diffusion measures revealed reduced white matter integrity within the striatum and amygdala that correlated with spatial learning performance. These findings reveal the lasting effect of pre-natal exposure to CPF as well as the danger of mother to child transmission of CPF in the environment. PMID:25704171

  15. Semi-autonomous image-guided brain tumour resection using an integrated robotic system: A bench-top study.

    Science.gov (United States)

    Hu, Danying; Gong, Yuanzheng; Seibel, Eric J; Sekhar, Laligam N; Hannaford, Blake

    2018-02-01

    Complete brain tumour resection is an extremely critical factor for patients' survival rate and long-term quality of life. This paper introduces a prototype medical robotic system that aims to automatically detect and clean up brain tumour residues after the removal of tumour bulk through conventional surgery. We focus on the development of an integrated surgical robotic system for image-guided robotic brain surgery. The Behavior Tree framework is explored to coordinate cross-platform medical subtasks. The integrated system was tested on a simulated laboratory platform. Results and performance indicate the feasibility of supervised semi-automation for residual brain tumour ablation in a simulated surgical cavity with sub-millimetre accuracy. The modularity in the control architecture allows straightforward integration of further medical devices. This work presents a semi-automated laboratory setup, simulating an intraoperative robotic neurosurgical procedure with real-time endoscopic image guidance and provides a foundation for the future transition from engineering approaches to clinical application. Copyright © 2017 John Wiley & Sons, Ltd.

  16. A reproducible brain tumour model established from human glioblastoma biopsies

    Directory of Open Access Journals (Sweden)

    Li Xingang

    2009-12-01

    Full Text Available Abstract Background Establishing clinically relevant animal models of glioblastoma multiforme (GBM remains a challenge, and many commonly used cell line-based models do not recapitulate the invasive growth patterns of patient GBMs. Previously, we have reported the formation of highly invasive tumour xenografts in nude rats from human GBMs. However, implementing tumour models based on primary tissue requires that these models can be sufficiently standardised with consistently high take rates. Methods In this work, we collected data on growth kinetics from a material of 29 biopsies xenografted in nude rats, and characterised this model with an emphasis on neuropathological and radiological features. Results The tumour take rate for xenografted GBM biopsies were 96% and remained close to 100% at subsequent passages in vivo, whereas only one of four lower grade tumours engrafted. Average time from transplantation to the onset of symptoms was 125 days ± 11.5 SEM. Histologically, the primary xenografts recapitulated the invasive features of the parent tumours while endothelial cell proliferations and necrosis were mostly absent. After 4-5 in vivo passages, the tumours became more vascular with necrotic areas, but also appeared more circumscribed. MRI typically revealed changes related to tumour growth, several months prior to the onset of symptoms. Conclusions In vivo passaging of patient GBM biopsies produced tumours representative of the patient tumours, with high take rates and a reproducible disease course. The model provides combinations of angiogenic and invasive phenotypes and represents a good alternative to in vitro propagated cell lines for dissecting mechanisms of brain tumour progression.

  17. Training in Brain Retraction Using a Self-Made Three-Dimensional Model.

    Science.gov (United States)

    Mashiko, Toshihiro; Konno, Takehiko; Kaneko, Naoki; Watanabe, Eiju

    2015-08-01

    A hollow brain model was created using soft urethane. A tube passing through the hollow was attached for use as a water inlet and manometer. Water sufficient in quantity to realize the intended initial pressure was infused through the tube. The brain model was retracted with a brain spatula and the surgical corridor was opened. By measuring local force with a sensor set on the brain spatula, the model could be used for training in brain retraction. At the same time, the water column of the manometer was measured and the relationship with the force of the brain spatula was investigated. A positive correlation between the water column and local force was confirmed. This indicated that it was possible to use this model without a force sensor for the same training using water column measurements. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. INTEGRATION OF HETEROGENOUS DIGITAL SURFACE MODELS

    OpenAIRE

    R. Boesch; C. Ginzler

    2012-01-01

    The application of extended digital surface models often reveals, that despite an acceptable global accuracy for a given dataset, the local accuracy of the model can vary in a wide range. For high resolution applications which cover the spatial extent of a whole country, this can be a major drawback. Within the Swiss National Forest Inventory (NFI), two digital surface models are available, one derived from LiDAR point data and the other from aerial images. Automatic photogram...

  19. Traumatic brain injury–Modeling neuropsychiatric symptoms in rodents

    Directory of Open Access Journals (Sweden)

    Oz eMalkesman

    2013-10-01

    Full Text Available Each year in the United States, approximately 1.5 million people sustain a traumatic brain injury (TBI. Victims of TBI can suffer from chronic post-TBI symptoms, such as sensory and motor deficits, cognitive impairments including problems with memory, learning, and attention, and neuropsychiatric symptoms such as depression, anxiety, irritability, aggression, and suicidal rumination. Although partially associated with the site and severity of injury, the biological mechanisms associated with many of these symptoms—and why some patients experience differing assortments of persistent maladies—are largely unknown. The use of animal models is a promising strategy for elucidation of the mechanisms of impairment and treatment, and learning, memory, sensory and motor tests have widespread utility in rodent models of TBI and psychopharmacology. Comparatively, behavioral tests for the evaluation of neuropsychiatric symptomatology are rarely employed in animal models of TBI and, as determined in this review, the results have been inconsistent. Animal behavioral studies contribute to the understanding of the biological mechanisms by which TBI is associated with neurobehavioral symptoms and offer a powerful means for pre-clinical treatment validation. Therefore, further exploration of the utility of animal behavioral tests for the study of injury mechanisms and therapeutic strategies for the alleviation of emotional symptoms are relevant and essential.

  20. The Intersystem Model of Psychotherapy: An Integrated Systems Treatment Approach

    Science.gov (United States)

    Weeks, Gerald R.; Cross, Chad L.

    2004-01-01

    This article introduces the intersystem model of psychotherapy and discusses its utility as a truly integrative and comprehensive approach. The foundation of this conceptually complex approach comes from dialectic metatheory; hence, its derivation requires an understanding of both foundational and integrational constructs. The article provides a…

  1. Integrated Climate Change Modelling and Policy Linkages for ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    This knowledge is typically based on future climate scenarios developed using integrated modelling techniques for both short- and long-term change. Applying this ... Improving approaches, integrating tools This project seeks to build on the collective strengths and experience of those CCW projects. It will maximize the ...

  2. Thermalization in integrable models and conformal field theories

    Indian Academy of Sciences (India)

    Gautam Mandal TIFR, Mumbai

    Introduction. Critical quench: model building. Quantum Ergodicity and integrability. Relaxation rates. Holography. Reduced density matrix- contd. Functional integral representation of the density matrix element. 〈φ, A|ρA|ψ, A〉 = ∑n〈n, Ac ; φ, A|ρ|ψ, A; n, Ac 〉. In the picture ρ ∼ exp[−βH].

  3. Height-integrated conductivity in auroral substorms - 2. Modeling

    DEFF Research Database (Denmark)

    Gjerløv, Jesper Wittendorff; Hoffman, R.A.

    2000-01-01

    Calculations of height-integrated conductivity from 31 individual Dynamics Explorer (DE 2) substorm crossings presented by Gjerloev and Hoffman [this issue] are used to compile empirical models of the height-integrated Pedersen and Hall conductivities (conductances) in a bulge-type auroral substorm...

  4. Modelling studies of fish production in integrated agriculture - aquaculture systems

    NARCIS (Netherlands)

    Dam, van A.A.

    1995-01-01


    The general objective of this thesis is to formulate a general model for fish production in integrated ponds and ricefields as a means of obtaining a better understanding of these production systems. Integrated culture systems produce fish without large industrial energy inputs and have

  5. Characterization of a novel brain barrier ex vivo insect-based P-glycoprotein screening model

    DEFF Research Database (Denmark)

    Andersson, O.; Badisco, L.; Hansen, A. H.

    2014-01-01

    In earlier studies insects were proposed as suitable models for vertebrate blood–brain barrier (BBB) permeability prediction and useful in early drug discovery. Here we provide transcriptome and functional data demonstrating the presence of a P-glycoprotein (Pgp) efflux transporter in the brain....... As in vertebrates, the locust brain–barrier function is morphologically confined to one specific cell layer and by using a whole-brain ex vivo drug exposure technique our locust model may retain the major cues that maintain and modulate the physiological function of the brain barrier. We show that the locust model...

  6. Know to restore: an integrated model

    Directory of Open Access Journals (Sweden)

    Cristiana Bartolomei

    2012-11-01

    Full Text Available Renovation and conservation interventions on historical buildings are generally accomplished based on wide and heterogeneous documents. The possibility of using this information is important for the design of appropriate strategies of intervention. The use of a Multimedia Information Archive (A.I.M allows in-depth knowledge of the buildings preservation status and can generate new data for further processing through dedicated procedures leading the user to highlight significant conceptual links. This paper presents an overview of some basic methodologies developed in integrated digital environments.

  7. The Exercising Brain: Changes in Functional Connectivity Induced by an Integrated Multimodal Cognitive and Whole-Body Coordination Training.

    Science.gov (United States)

    Demirakca, Traute; Cardinale, Vita; Dehn, Sven; Ruf, Matthias; Ende, Gabriele

    2016-01-01

    This study investigated the impact of "life kinetik" training on brain plasticity in terms of an increased functional connectivity during resting-state functional magnetic resonance imaging (rs-fMRI). The training is an integrated multimodal training that combines motor and cognitive aspects and challenges the brain by introducing new and unfamiliar coordinative tasks. Twenty-one subjects completed at least 11 one-hour-per-week "life kinetik" training sessions in 13 weeks as well as before and after rs-fMRI scans. Additionally, 11 control subjects with 2 rs-fMRI scans were included. The CONN toolbox was used to conduct several seed-to-voxel analyses. We searched for functional connectivity increases between brain regions expected to be involved in the exercises. Connections to brain regions representing parts of the default mode network, such as medial frontal cortex and posterior cingulate cortex, did not change. Significant connectivity alterations occurred between the visual cortex and parts of the superior parietal area (BA7). Premotor area and cingulate gyrus were also affected. We can conclude that the constant challenge of unfamiliar combinations of coordination tasks, combined with visual perception and working memory demands, seems to induce brain plasticity expressed in enhanced connectivity strength of brain regions due to coactivation.

  8. White Matter MS-Lesion Segmentation Using a Geometric Brain Model.

    OpenAIRE

    Strumia Maddalena; Schmidt Frank; Anastasopoulos Constantin; Granziera Cristina; Krueger Gunnar; Brox Thomas

    2016-01-01

    Brain magnetic resonance imaging (MRI) in patients with Multiple Sclerosis (MS) shows regions of signal abnormalities named plaques or lesions. The spatial lesion distribution plays a major role for MS diagnosis. In this paper we present a 3D MS lesion segmentation method based on an adaptive geometric brain model. We model the topological properties of the lesions and brain tissues in order to constrain the lesion segmentation to the white matter. As a result the method is independent of an ...

  9. A Nonparametric model for Brain Tumor Segmentation and Volumetry in Longitudinal MR Sequences

    OpenAIRE

    Alberts, Esther; Charpiat, Guillaume; Tarabalka, Yuliya; Huber, Thomas; Weber, Marc-André; Bauer, Jan; Zimmer, Claus; Menze, Bjoern H.

    2015-01-01

    International audience; Brain tumor image segmentation and brain tumor growth assessment are inter-dependent and benet from a joint evaluation. Starting from a generative model for multimodal brain tumor segmentation, we make use of a nonparametric growth model that is implemented as a conditional random field (CRF) including directed links with infinite weight in order to incorporate growth and inclusion constraints, reflecting our prior belief on tumor occurrence in the dierent image modali...

  10. Development of the Integrated Communication Model

    Science.gov (United States)

    Ho, Hua-Kuo

    2008-01-01

    Human communication is a critical issue in personal life. It also should be the indispensable core element of general education curriculum in universities and colleges. Based on literature analysis and the author's clinical observation, the importance of human communication, functions of model, and often seen human communication models were…

  11. A Fuzzy Integral Ensemble Method in Visual P300 Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Francesco Cavrini

    2016-01-01

    Full Text Available We evaluate the possibility of application of combination of classifiers using fuzzy measures and integrals to Brain-Computer Interface (BCI based on electroencephalography. In particular, we present an ensemble method that can be applied to a variety of systems and evaluate it in the context of a visual P300-based BCI. Offline analysis of data relative to 5 subjects lets us argue that the proposed classification strategy is suitable for BCI. Indeed, the achieved performance is significantly greater than the average of the base classifiers and, broadly speaking, similar to that of the best one. Thus the proposed methodology allows realizing systems that can be used by different subjects without the need for a preliminary configuration phase in which the best classifier for each user has to be identified. Moreover, the ensemble is often capable of detecting uncertain situations and turning them from misclassifications into abstentions, thereby improving the level of safety in BCI for environmental or device control.

  12. Candesartan attenuates ischemic brain edema and protects the blood-brain barrier integrity from ischemia/reperfusion injury in rats.

    Science.gov (United States)

    Panahpour, Hamdollah; Nekooeian, Ali Akbar; Dehghani, Gholam Abbas

    2014-01-01

    Angiotensin II (Ang II) has an important role on cerebral microcirculation; however, its direct roles in terms of ischemic brain edema need to be clarified. This study evaluated the role of central Ang II by using candesartan, as an AT1 receptor blocker, in the brain edema formation and blood-brain barrier (BBB) disruption caused by ischemia/reperfusion (I/R) injuries in rat. Rats were exposed to 60-min middle cerebral artery (MCA) occlusion. Vehicle and non-hypotensive doses of candesartan (0.1 mg/kg) were administered one hour before ischemia. Neurological dysfunction scoring was evaluated following 24 h of reperfusion. Animals were then decapitated under deep anesthesia for the assessments of cerebral infarct size, edema formation, and BBB permeability. The outcomes of 24 h reperfusion after 60-min MCA occlusion were severe neurological disability, massive BBB disruption (Evans blue extravasation = 12.5 ± 1.94 µg/g tissue), 4.02% edema, and cerebral infarction (317 ± 21 mm3). Candesartan at a dose of 0.1 mg/kg, without changing arterial blood pressure, improved neurological dysfunction scoring together with significant reductions in BBB disruption (54.9%), edema (59.2%), and cerebral infarction (54.9%). Inactivation of central AT1 receptors, if not accompanied with arterial hypotension, protected cerebral micro-vasculatures from damaging effects of acute stroke.

  13. Candesartan Attenuates Ischemic Brain Edema and Protects the Blood–Brain Barrier Integrity from Ischemia/Reperfusion Injury in Rats

    Science.gov (United States)

    Panahpour, Hamdollah; Nekooeian, Ali Akbar; Dehghani, Gholam Abbas

    2014-01-01

    Background: Angiotensin II (Ang II) has an important role on cerebral microcirculation; however, its direct roles in terms of ischemic brain edema need to be clarified. This study evaluated the role of central Ang II by using candesartan, as an AT1 receptor blocker, in the brain edema formation and blood-brain barrier (BBB) disruption caused by ischemia/reperfusion (I/R) injuries in rat. Methods: Rats were exposed to 60-min middle cerebral artery (MCA) occlusion. Vehicle and non-hypotensive doses of candesartan (0.1 mg/kg) were administered one hour before ischemia. Neurological dysfunction scoring was evaluated following 24 h of reperfusion. Animals were then decapitated under deep anesthesia for the assessments of cerebral infarct size, edema formation, and BBB permeability. Results: The outcomes of 24 h reperfusion after 60-min MCA occlusion were severe neurological disability, massive BBB disruption (Evans blue extravasation = 12.5 ± 1.94 µg/g tissue), 4.02% edema, and cerebral infarction (317 ± 21 mm3). Candesartan at a dose of 0.1 mg/kg, without changing arterial blood pressure, improved neurological dysfunction scoring together with significant reductions in BBB disruption (54.9%), edema (59.2%), and cerebral infarction (54.9%). Conclusions: Inactivation of central AT1 receptors, if not accompanied with arterial hypotension, protected cerebral micro-vasculatures from damaging effects of acute stroke. PMID:25326022

  14. Integrated Age-based Krill Model Fish Res 2015

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An integrated, age-structured model was fitted to different combinations of survey data using two forms of selectivity (logistic or double-logistic) with...

  15. Integrative systems modeling and multi-objective optimization

    Science.gov (United States)

    This presentation presents a number of algorithms, tools, and methods for utilizing multi-objective optimization within integrated systems modeling frameworks. We first present innovative methods using a genetic algorithm to optimally calibrate the VELMA and SWAT ecohydrological ...

  16. Integrated Krill Model WG-SAM-14/20

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The integrated modeling framework for Antarctic krill (Euphausia superba) has been extended to include estimates of krill growth consistent with survey data and to...

  17. INNOVATIVE MODEL OF INTEGRATED ENERGY MANAGEMENT IN COMPANIES

    National Research Council Canada - National Science Library

    Milan Majernik; Martin Bosak; Lenka Stofova; Petra Szaryszova

    2015-01-01

    Purpose: To propose and verify an innovative concept model of integrating standardized energy management system according to ISO 50001 management system of enterprises in the network of automobile suppliers...

  18. Logistic Regression Modeling of Diminishing Manufacturing Sources for Integrated Circuits

    National Research Council Canada - National Science Library

    Gravier, Michael

    1999-01-01

    .... This thesis draws on available data from the electronics integrated circuit industry to attempt to assess whether statistical modeling offers a viable method for predicting the presence of DMSMS...

  19. Integrated Main Propulsion System Performance Reconstruction Process/Models

    Science.gov (United States)

    Lopez, Eduardo; Elliott, Katie; Snell, Steven; Evans, Michael

    2013-01-01

    The Integrated Main Propulsion System (MPS) Performance Reconstruction process provides the MPS post-flight data files needed for postflight reporting to the project integration management and key customers to verify flight performance. This process/model was used as the baseline for the currently ongoing Space Launch System (SLS) work. The process utilizes several methodologies, including multiple software programs, to model integrated propulsion system performance through space shuttle ascent. It is used to evaluate integrated propulsion systems, including propellant tanks, feed systems, rocket engine, and pressurization systems performance throughout ascent based on flight pressure and temperature data. The latest revision incorporates new methods based on main engine power balance model updates to model higher mixture ratio operation at lower engine power levels.

  20. Integrated Visualization Environment for Science Mission Modeling Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA is emphasizing the use of larger, more integrated models in conjunction with systems engineering tools and decision support systems. These tools place a...

  1. Integrating Theoretical Models with Functional Neuroimaging.

    Science.gov (United States)

    Pratte, Michael S; Tong, Frank

    2017-02-01

    The development of mathematical models to characterize perceptual and cognitive processes dates back almost to the inception of the field of psychology. Since the 1990s, human functional neuroimaging has provided for rapid empirical and theoretical advances across a variety of domains in cognitive neuroscience. In more recent work, formal modeling and neuroimaging approaches are being successfully combined, often producing models with a level of specificity and rigor that would not have been possible by studying behavior alone. In this review, we highlight examples of recent studies that utilize this combined approach to provide novel insights into the mechanisms underlying human cognition. The studies described here span domains of perception, attention, memory, categorization, and cognitive control, employing a variety of analytic and model-inspired approaches. Across these diverse studies, a common theme is that individually tailored, creative solutions are often needed to establish compelling links between multi-parameter models and complex sets of neural data. We conclude that future developments in model-based cognitive neuroscience will have great potential to advance our theoretical understanding and ability to model both low-level and high-level cognitive processes.

  2. An Integrated Model of Information Literacy, Based upon Domain Learning

    Science.gov (United States)

    Thompson, Gary B.; Lathey, Johnathan W.

    2013-01-01

    Introduction. Grounded in Alexander's model of domain learning, this study presents an integrated micro-model of information literacy. It is predicated upon the central importance of domain learning for the development of the requisite research skills by students. Method. The authors reviewed previous models of information literacy and…

  3. Integrating a Decision Management Tool with UML Modeling Tools

    DEFF Research Database (Denmark)

    Könemann, Patrick

    the development process. In this report, we propose an integration of a decision management and a UML-based modeling tool, based on use cases we distill from a case study: the modeling tool shall show all decisions related to a model and allow its users to extend or update them; the decision management tool shall...

  4. Integrating public transort networks in the axial model

    NARCIS (Netherlands)

    Gil, J.

    2012-01-01

    This study presents a first step in the development of a model that integrates public transport networks with the space syntax axial model, towards a network model that can describe the multi?modal movement structure of a city and study its patterns and flows. It describes the method for building an

  5. EnergyPlus Air Source Integrated Heat Pump Model

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Bo [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Energy and Transportation Science Division; Adams, Mark B. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Energy and Transportation Science Division; New, Joshua Ryan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Energy and Transportation Science Division

    2016-03-30

    This report summarizes the development of the EnergyPlus air-source integrated heat pump model. It introduces its physics, sub-models, working modes, and control logic. In addition, inputs and outputs of the new model are described, and input data file (IDF) examples are given.

  6. Integrable double deformation of the principal chiral model

    Energy Technology Data Exchange (ETDEWEB)

    Delduc, F., E-mail: Francois.Delduc@ens-lyon.fr [Laboratoire de Physique, ENS Lyon and CNRS UMR 5672, Université de Lyon, 46, allée d' Italie, 69364 Lyon Cedex 07 (France); Magro, M., E-mail: Marc.Magro@ens-lyon.fr [Laboratoire de Physique, ENS Lyon and CNRS UMR 5672, Université de Lyon, 46, allée d' Italie, 69364 Lyon Cedex 07 (France); Vicedo, B., E-mail: Benoit.Vicedo@gmail.com [School of Physics, Astronomy and Mathematics, University of Hertfordshire, College Lane, Hatfield AL10 9AB (United Kingdom)

    2015-02-15

    We define a two-parameter family of integrable deformations of the principal chiral model on an arbitrary compact group. The Yang–Baxter σ-model and the principal chiral model with a Wess–Zumino term both correspond to limits in which one of the two parameters vanishes.

  7. Advancing population ecology with integral projection models: a practical guide

    DEFF Research Database (Denmark)

    Merow, Cory; Dahlgren, Johan; Metcall, C. Jessica E.

    2014-01-01

    Integral Projection Models (IPMs) use information on how an individual's state influences its vital rates - survival, growth and reproduction - to make population projections. IPMs are constructed from regression models predicting vital rates from state variables (e.g., size or age) and covariates...... Projection Models....

  8. Towards an integrated formal model of fundamental frequency in ...

    African Journals Online (AJOL)

    The approach is applied to two current models of decay in intonation curves. The models and then the conflicts between them are described. These latter were used to construct the integrated model. Our short term objective is to validate the application of our approach by testing and implementing empirical instrumental ...

  9. Integrating affective responses into game theory: A dual selves model

    OpenAIRE

    Greiff, Matthias

    2015-01-01

    This paper develops a method to integrate affective reponses into game theoretical models. We illustrate our method in a team production framework. The model analyzes how concave and convex status preferences for esteem solve the problem of team production under complete and incomplete information about workers’ abilities. Using a dual selves model, we model the choice of effort as a deliberative decision and the expression of esteem as an affective response. Modeling an individual’s affectiv...

  10. Using chaotic artificial neural networks to model memory in the brain

    Science.gov (United States)

    Aram, Zainab; Jafari, Sajad; Ma, Jun; Sprott, Julien C.; Zendehrouh, Sareh; Pham, Viet-Thanh

    2017-03-01

    In the current study, a novel model for human memory is proposed based on the chaotic dynamics of artificial neural networks. This new model explains a biological fact about memory which is not yet explained by any other model: There are theories that the brain normally works in a chaotic mode, while during attention it shows ordered behavior. This model uses the periodic windows observed in a previously proposed model for the brain to store and then recollect the information.

  11. Data Assimilation in Integrated and Distributed Hydrological Models

    DEFF Research Database (Denmark)

    Zhang, Donghua

    Integrated hydrological models are frequently used in water-related environmental resource management. With our better understanding of the hydrological processes and the improved computational power, hydrological models are becoming increasingly more complex as they integrate multiple hydrological...... processes and provide simulations in refined temporal and spatial resolutions. Recent developments in measurement and sensor technologies have significantly improved the coverage, quality, frequency and diversity of hydrological observations. Data assimilation provides a great potential in relation...

  12. Integrated thermodynamic model for ignition target performance

    Directory of Open Access Journals (Sweden)

    Springer P.T.

    2013-11-01

    Full Text Available We have derived a 3-dimensional synthetic model for NIF implosion conditions, by predicting and optimizing fits to a broad set of x-ray and nuclear diagnostics obtained on each shot. By matching x-ray images, burn width, neutron time-of-flight ion temperature, yield, and fuel ρr, we obtain nearly unique constraints on conditions in the hotspot and fuel in a model that is entirely consistent with the observables. This model allows us to determine hotspot density, pressure, areal density (ρr, total energy, and other ignition-relevant parameters not available from any single diagnostic. This article describes the model and its application to National Ignition Facility (NIF tritium–hydrogen–deuterium (THD and DT implosion data, and provides an explanation for the large yield and ρr degradation compared to numerical code predictions.

  13. An Integrated Approach to Modeling Evacuation Behavior

    Science.gov (United States)

    2011-02-01

    A spate of recent hurricanes and other natural disasters have drawn a lot of attention to the evacuation decision of individuals. Here we focus on evacuation models that incorporate two economic phenomena that seem to be increasingly important in exp...

  14. Quantitative consensus of bioaccumulation models for integrated testing strategies.

    Science.gov (United States)

    Fernández, Alberto; Lombardo, Anna; Rallo, Robert; Roncaglioni, Alessandra; Giralt, Francesc; Benfenati, Emilio

    2012-09-15

    A quantitative consensus model based on bioconcentration factor (BCF) predictions obtained from five quantitative structure-activity relationship models was developed for bioaccumulation assessment as an integrated testing approach for waiving. Three categories were considered: non-bioaccumulative, bioaccumulative and very bioaccumulative. Five in silico BCF models were selected and included into a quantitative consensus model by means of the continuous formulation of Bayes' theorem. The discrete likelihoods commonly used in the qualitative Bayesian model were substituted by probability density functions to reduce the loss of information that occurred when continuous BCF values were distributed across the three bioaccumulation categories. Results showed that the continuous Bayesian model yielded the best classification predictions compared not only to the discrete Bayesian model, but also to the individual BCF models. The proposed quantitative consensus model proved to be a suitable approach for integrated testing strategies for continuous endpoints of environmental interest. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. Broad integration of expression maps and co-expression networks compassing novel gene functions in the brain.

    Science.gov (United States)

    Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

    2014-11-10

    Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas.

  16. Multiscale modeling of integrated CCS systems

    Science.gov (United States)

    Alhajaj, Ahmed; Shah, Nilay

    2015-01-01

    The world will continue consuming fossil fuel within the coming decades to meet its growing energy demand; however, this source must be cleaner through implementation of carbon capture, transport and storage (CCTS). This process is complex and involves multiple phases, owned by different operational companies and stakeholders with different business models and regulatory framework. The objective of this work is to develop a multiscale modeling approach to link process models, post-combustion capture plant model and network design models under an optimization framework in order to design and analyse the cost optimal CO2 infrastructure that match CO2 sources and sinks in capacity and time. The network comprises a number of CO2 sources at fixed locations and a number of potential CO2 storage sites. The decisions to be determined include from which sources it is appropriate to capture CO2 and the cost-optimal degree-of-capture (DOC) for a given source and the infrastructural layout of the CO2 transmission network.

  17. Development of an Integrated Global Energy Model

    Energy Technology Data Exchange (ETDEWEB)

    Krakowski, R.A.

    1999-07-08

    The primary objective of this research was to develop a forefront analysis tool for application to enhance understanding of long-term, global, nuclear-energy and nuclear-material futures. To this end, an existing economics-energy-environmental (E{sup 3}) model was adopted, modified, and elaborated to examine this problem in a multi-regional (13), long-term ({approximately}2,100) context. The E{sup 3} model so developed was applied to create a Los Alamos presence in this E{sup 3} area through ''niche analyses'' that provide input to the formulation of policies dealing with and shaping of nuclear-energy and nuclear-materials futures. Results from analyses using the E{sup 3} model have been presented at a variety of national and international conferences and workshops. Through use of the E{sup 3} model Los Alamos was afforded the opportunity to participate in a multi-national E{sup 3} study team that is examining a range of global, long-term nuclear issues under the auspices of the IAEA during the 1998-99 period . Finally, the E{sup 3} model developed under this LDRD project is being used as an important component in more recent Nuclear Material Management Systems (NMMS) project.

  18. Integration of Design and Control through Model Analysis

    DEFF Research Database (Denmark)

    Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay

    2002-01-01

    and design (manipulative) variables that may be employed with different objectives in design and control for the integrated problem. The computer aided model analysis is highlighted through illustrative examples, involving processes with mass and/or energy recycle, where the important design and control......A systematic computer aided analysis of the process model is proposed as a pre-solution step for integration of design and control problems. The process model equations are classified in terms of balance equations, constitutive equations and conditional equations. Analysis of the phenomena models...

  19. Integrability in three dimensions: Algebraic Bethe ansatz for anyonic models

    Directory of Open Access Journals (Sweden)

    Sh. Khachatryan

    2015-10-01

    Full Text Available We extend basic properties of two dimensional integrable models within the Algebraic Bethe Ansatz approach to 2+1 dimensions and formulate the sufficient conditions for the commutativity of transfer matrices of different spectral parameters, in analogy with Yang–Baxter or tetrahedron equations. The basic ingredient of our models is the R-matrix, which describes the scattering of a pair of particles over another pair of particles, the quark-anti-quark (meson scattering on another quark-anti-quark state. We show that the Kitaev model belongs to this class of models and its R-matrix fulfills well-defined equations for integrability.

  20. Arbitrary modeling of TSVs for 3D integrated circuits

    CERN Document Server

    Salah, Khaled; El-Rouby, Alaa

    2014-01-01

    This book presents a wide-band and technology independent, SPICE-compatible RLC model for through-silicon vias (TSVs) in 3D integrated circuits. This model accounts for a variety of effects, including skin effect, depletion capacitance and nearby contact effects. Readers will benefit from in-depth coverage of concepts and technology such as 3D integration, Macro modeling, dimensional analysis and compact modeling, as well as closed form equations for the through silicon via parasitics. Concepts covered are demonstrated by using TSVs in applications such as a spiral inductor?and inductive-based

  1. Integration of Design and Control Through Model Analysis

    DEFF Research Database (Denmark)

    Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay

    2000-01-01

    A systematic analysis of the process model is proposed as a pre-solution step for integration of design and control problems. It is shown that the same set of process (control) variables and design (manipulative) variables is employed with different objectives in design and control. Analysis...... of the phenomena models representing the process model identify the relationships between the important process and design variables, which help to understand, define and address some of the issues related to integration of design and control issues. The model analysis is highlighted through examples involving...

  2. Models for efficient integration of solar energy

    DEFF Research Database (Denmark)

    Bacher, Peder

    the available flexibility in the system. In the present thesis methods related to operation of solar energy systems and for optimal energy use in buildings are presented. Two approaches for forecasting of solar power based on numerical weather predictions (NWPs) are presented, they are applied to forecast...... the power output from PV and solar thermal collector systems. The first approach is based on a developed statistical clear-sky model, which is used for estimating the clear-sky output solely based on observations of the output. This enables local effects such as shading from trees to be taken into account....... The second approach to solar power forecasting is based on conditional parametric modelling. It is well suited for forecasting of solar thermal power, since is it can be make non-linear in the inputs. The approach is also extended to a probabilistic solar power forecasting model. The statistical clear...

  3. Integrated model of a composite propellant rocket

    Science.gov (United States)

    Miccio, Francesco

    2016-12-01

    The combustion of composite solid propellants was investigated and an available numerical model was improved for taking into account the change of pressure, when the process occurs in a confined environment, as inside a rocket. The pressure increase upon ignition is correctly described by the improved model for both sandwich and dispersed particles propellants. In the latter case, self-induced fluctuations in the pressure and in all other computed variables occur, as consequence of the periodic rise and depletion of oxidizer particles from the binder matrix. The comparison with the results of the constant pressure model shows a different fluctuating profile of gas velocity, with a possible second order effect induced by the pressure fluctuations.

  4. Fractional Diffusion Based Modelling and Prediction of Human Brain Response to External Stimuli

    Directory of Open Access Journals (Sweden)

    Hamidreza Namazi

    2015-01-01

    Full Text Available Human brain response is the result of the overall ability of the brain in analyzing different internal and external stimuli and thus making the proper decisions. During the last decades scientists have discovered more about this phenomenon and proposed some models based on computational, biological, or neuropsychological methods. Despite some advances in studies related to this area of the brain research, there were fewer efforts which have been done on the mathematical modeling of the human brain response to external stimuli. This research is devoted to the modeling and prediction of the human EEG signal, as an alert state of overall human brain activity monitoring, upon receiving external stimuli, based on fractional diffusion equations. The results of this modeling show very good agreement with the real human EEG signal and thus this model can be used for many types of applications such as prediction of seizure onset in patient with epilepsy.

  5. Integrating interactive computational modeling in biology curricula.

    Directory of Open Access Journals (Sweden)

    Tomáš Helikar

    2015-03-01

    Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  6. Integrating Interactive Computational Modeling in Biology Curricula

    Science.gov (United States)

    Helikar, Tomáš; Cutucache, Christine E.; Dahlquist, Lauren M.; Herek, Tyler A.; Larson, Joshua J.; Rogers, Jim A.

    2015-01-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by “building and breaking it” via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the “Vision and Change” call to action in undergraduate biology education by providing a hands-on approach to biology. PMID:25790483

  7. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

    Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

    2015-03-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  8. Fresh Frozen Plasma Modulates Brain Gene Expression in a Swine Model of Traumatic Brain Injury and Shock

    DEFF Research Database (Denmark)

    Sillesen, Martin; Bambakidis, Ted; Dekker, Simone E

    2017-01-01

    analysis revealed an upregulation of genes involved in metabolic and platelet signaling, as well as collagen formation and downregulation of inflammation. CONCLUSIONS: Fresh frozen plasma resuscitation in this model was associated with downregulation of inflammatory pathway genes and expression of gene...... clusters mapping to increased metabolic and platelet signaling, which, in turn, was reversely associated with brain swelling....

  9. WASICA: An effective wavelet-shrinkage based ICA model for brain fMRI data analysis.

    Science.gov (United States)

    Wang, Nizhuan; Zeng, Weiming; Shi, Yingchao; Ren, Tianlong; Jing, Yanshan; Yin, Jun; Yang, Jiajun

    2015-05-15

    Researches declared that the super-Gaussian property contributed to the success of some spatial independent component analysis (ICA) algorithms in brain fMRI source separation (e.g., Infomax and FastICA), which implied that sparse approximation transforming the sources (super-Gaussian or Gaussian-like) with stronger super-Gaussian feature would possibly improve the separation performance of these algorithms. This paper presented a novel wavelet-shrinkage based ICA (WASICA) model, an extension of our previous SACICA, for single-subject analysis. In contrast, two main aspects had been effectively enhanced: (1) sparse approximation coefficients set formation, made up of two sub-procedures: the wavelet-shrinkage of wavelet packet (WP) tree nodes, and the automatic nodes selection and integration based on the relative WP energy; (2) ICA-based decomposition and reconstruction, composed of temporal dynamics extraction using ICA, WP reconstruction based on the sparse approximation coefficients set and least-square-based functional networks reconstruction. The wavelet-shrinkage and the automatic nodes selection and integration simultaneously transformed both the mixtures and underlying sources into effective sparse approximation coefficients sets, exhibiting stronger super-Gaussian distribution; WP projected-back approximation with nuisance-exclusion contributed to networks reconstruction. Simulation 1 revealed WASICA successfully recovered super-Gaussian and some Gaussian-like sources. Simulation 2 and hybrid data experiments showed that WASICA with good temporal performance had stronger source recovery ability and signal detection sensitivity spatially than FastICA, Infomax and SACICA did; the higher intra-consistency in task-related experiments denoted WASICA occupied stronger spatial robustness against smooth kernels. WASICA was a promising brain signal separation model with charming spatial-temporal performance. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Model sparsity and brain pattern interpretation of classification models in neuroimaging

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Churchill, Nathan W

    2012-01-01

    Interest is increasing in applying discriminative multivariate analysis techniques to the analysis of functional neuroimaging data. Model interpretation is of great importance in the neuroimaging context, and is conventionally based on a ‘brain map’ derived from the classification model. In this ......Interest is increasing in applying discriminative multivariate analysis techniques to the analysis of functional neuroimaging data. Model interpretation is of great importance in the neuroimaging context, and is conventionally based on a ‘brain map’ derived from the classification model...... encoding of the experiment. For a support vector machine, logistic regression and Fisher's discriminant analysis we demonstrate that selection of model regularization parameters has a strong but consistent impact on the generalizability and both the reproducibility and interpretable sparsity of the models....... This supports the view that the quality of spatial patterns extracted from models cannot be assessed purely by focusing on prediction accuracy. Our results instead suggest that model regularization parameters must be carefully selected, so that the model and its visualization enhance our ability to interpret...

  11. Imaging of Glial Cell Activation and White Matter Integrity in Brains of Active and Recently Retired National Football League Players.

    Science.gov (United States)

    Coughlin, Jennifer M; Wang, Yuchuan; Minn, Il; Bienko, Nicholas; Ambinder, Emily B; Xu, Xin; Peters, Matthew E; Dougherty, John W; Vranesic, Melin; Koo, Soo Min; Ahn, Hye-Hyun; Lee, Merton; Cottrell, Chris; Sair, Haris I; Sawa, Akira; Munro, Cynthia A; Nowinski, Christopher J; Dannals, Robert F; Lyketsos, Constantine G; Kassiou, Michael; Smith, Gwenn; Caffo, Brian; Mori, Susumu; Guilarte, Tomas R; Pomper, Martin G

    2017-01-01

    Microglia, the resident immune cells of the central nervous system, play an important role in the brain's response to injury and neurodegenerative processes. It has been proposed that prolonged microglial activation occurs after single and repeated traumatic brain injury, possibly through sports-related concussive and subconcussive injuries. Limited in vivo brain imaging studies months to years after individuals experience a single moderate to severe traumatic brain injury suggest widespread persistent microglial activation, but there has been little study of persistent glial cell activity in brains of athletes with sports-related traumatic brain injury. To measure translocator protein 18 kDa (TSPO), a marker of activated glial cell response, in a cohort of National Football League (NFL) players and control participants, and to report measures of white matter integrity. This cross-sectional, case-control study included young active (n = 4) or former (n = 10) NFL players recruited from across the United States, and 16 age-, sex-, highest educational level-, and body mass index-matched control participants. This study was conducted at an academic research institution in Baltimore, Maryland, from January 29, 2015, to February 18, 2016. Positron emission tomography-based regional measures of TSPO using [11C]DPA-713, diffusion tensor imaging measures of regional white matter integrity, regional volumes on structural magnetic resonance imaging, and neuropsychological performance. The mean (SD) ages of the 14 NFL participants and 16 control participants were 31.3 (6.1) years and 27.6 (4.9) years, respectively. Players reported a mean (SD) of 7.0 (6.4) years (range, 1-21 years) since the last self-reported concussion. Using [11C]DPA-713 positron emission tomographic data from 12 active or former NFL players and 11 matched control participants, the NFL players showed higher total distribution volume in 8 of the 12 brain regions examined (P players compared with 15

  12. Exploring RNA structure by integrative molecular modelling

    DEFF Research Database (Denmark)

    Masquida, Benoît; Beckert, Bertrand; Jossinet, Fabrice

    2010-01-01

    in three dimensions (3D) and used as building blocks assembled manually during a bioinformatic interactive process. Comparing the models to the corresponding crystal structures has validated the method as being powerful to predict the RNA topology and architecture while being less accurate regarding...... the prediction of base-base interactions. These aspects as well as the necessary steps towards automation will be discussed....

  13. Exploring RNA structure by integrative molecular modelling.

    Science.gov (United States)

    Masquida, Benoît; Beckert, Bertrand; Jossinet, Fabrice

    2010-07-31

    RNA molecular modelling is adequate to rapidly tackle the structure of RNA molecules. With new structured RNAs constituting a central class of cellular regulators discovered every year, the need for swift and reliable modelling methods is more crucial than ever. The pragmatic method based on interactive all-atom molecular modelling relies on the observation that specific structural motifs are recurrently found in RNA sequences. Once identified by a combination of comparative sequence analysis and biochemical data, the motifs composing the secondary structure of a given RNA can be extruded in three dimensions (3D) and used as building blocks assembled manually during a bioinformatic interactive process. Comparing the models to the corresponding crystal structures has validated the method as being powerful to predict the RNA topology and architecture while being less accurate regarding the prediction of base-base interactions. These aspects as well as the necessary steps towards automation will be discussed. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  14. A depth integrated model for suspended transport

    NARCIS (Netherlands)

    Galappatti, R.

    1983-01-01

    A new depth averaged model for suspended sediment transport in open channels has been developed based on an asymptotic solution to the two dimensional convection-diffusion equation in the vertical plane. The solution for the depth averaged concentration is derived from the bed boundary condition and

  15. Integrated Biogeomorphological Modeling Using Delft3D

    Science.gov (United States)

    Ye, Q.; Jagers, B.

    2011-12-01

    The skill of numerical morphological models has improved significantly from the early 2D uniform, total load sediment models (with steady state or infrequent wave updates) to recent 3D hydrodynamic models with multiple suspended and bed load sediment fractions and bed stratigraphy (online coupled with waves). Although there remain many open questions within this combined field of hydro- and morphodynamics, we observe an increasing need to include biological processes in the overall dynamics. In riverine and inter-tidal environments, there is often an important influence by riparian vegetation and macrobenthos. Over the past decade more and more researchers have started to extend the simulation environment with wrapper scripts and other quick code hacks to estimate their influence on morphological development in coastal, estuarine and riverine environments. Although one can in this way quickly analyze different approaches, these research tools have generally not been designed with reuse, performance and portability in mind. We have now implemented a reusable, flexible, and efficient two-way link between the Delft3D open source framework for hydrodynamics, waves and morphology, and the water quality and ecology modules. The same link will be used for 1D, 2D and 3D modeling on networks and both structured and unstructured grids. We will describe the concepts of the overall system, and illustrate it with some first results.

  16. Stroke and Drug Delivery--In Vitro Models of the Ischemic Blood-Brain Barrier

    DEFF Research Database (Denmark)

    Tornabene, Erica; Brodin, Birger

    2016-01-01

    and Drug Administration-approved tissue plasminogen activator for treatment of acute ischemic stroke being the most prominent example. A large number of potential drug candidates for treatment of ischemic brain tissue have been developed and subsequently failed in clinical trials. A deeper understanding......Stroke is a major cause of death and disability worldwide. Both cerebral hypoperfusion and focal cerebral infarcts are caused by a reduction of blood flow to the brain, leading to stroke and subsequent brain damage. At present, only few medical treatments of stroke are available, with the Food...... of permeation pathways across the barrier in ischemic and postischemic brain endothelium is important for development of new medical treatments. The blood-brain barrier, that is, the endothelial monolayer lining the brain capillaries, changes properties during an ischemic event. In vitro models of the blood-brain...

  17. INTEGRATION OF HETEROGENOUS DIGITAL SURFACE MODELS

    Directory of Open Access Journals (Sweden)

    R. Boesch

    2012-08-01

    Full Text Available The application of extended digital surface models often reveals, that despite an acceptable global accuracy for a given dataset, the local accuracy of the model can vary in a wide range. For high resolution applications which cover the spatial extent of a whole country, this can be a major drawback. Within the Swiss National Forest Inventory (NFI, two digital surface models are available, one derived from LiDAR point data and the other from aerial images. Automatic photogrammetric image matching with ADS80 aerial infrared images with 25cm and 50cm resolution is used to generate a surface model (ADS-DSM with 1m resolution covering whole switzerland (approx. 41000 km2. The spatially corresponding LiDAR dataset has a global point density of 0.5 points per m2 and is mainly used in applications as interpolated grid with 2m resolution (LiDAR-DSM. Although both surface models seem to offer a comparable accuracy from a global view, local analysis shows significant differences. Both datasets have been acquired over several years. Concerning LiDAR-DSM, different flight patterns and inconsistent quality control result in a significantly varying point density. The image acquisition of the ADS-DSM is also stretched over several years and the model generation is hampered by clouds, varying illumination and shadow effects. Nevertheless many classification and feature extraction applications requiring high resolution data depend on the local accuracy of the used surface model, therefore precise knowledge of the local data quality is essential. The commercial photogrammetric software NGATE (part of SOCET SET generates the image based surface model (ADS-DSM and delivers also a map with figures of merit (FOM of the matching process for each calculated height pixel. The FOM-map contains matching codes like high slope, excessive shift or low correlation. For the generation of the LiDAR-DSM only first- and last-pulse data was available. Therefore only the point

  18. Integration of Heterogenous Digital Surface Models

    Science.gov (United States)

    Boesch, R.; Ginzler, C.

    2011-08-01

    The application of extended digital surface models often reveals, that despite an acceptable global accuracy for a given dataset, the local accuracy of the model can vary in a wide range. For high resolution applications which cover the spatial extent of a whole country, this can be a major drawback. Within the Swiss National Forest Inventory (NFI), two digital surface models are available, one derived from LiDAR point data and the other from aerial images. Automatic photogrammetric image matching with ADS80 aerial infrared images with 25cm and 50cm resolution is used to generate a surface model (ADS-DSM) with 1m resolution covering whole switzerland (approx. 41000 km2). The spatially corresponding LiDAR dataset has a global point density of 0.5 points per m2 and is mainly used in applications as interpolated grid with 2m resolution (LiDAR-DSM). Although both surface models seem to offer a comparable accuracy from a global view, local analysis shows significant differences. Both datasets have been acquired over several years. Concerning LiDAR-DSM, different flight patterns and inconsistent quality control result in a significantly varying point density. The image acquisition of the ADS-DSM is also stretched over several years and the model generation is hampered by clouds, varying illumination and shadow effects. Nevertheless many classification and feature extraction applications requiring high resolution data depend on the local accuracy of the used surface model, therefore precise knowledge of the local data quality is essential. The commercial photogrammetric software NGATE (part of SOCET SET) generates the image based surface model (ADS-DSM) and delivers also a map with figures of merit (FOM) of the matching process for each calculated height pixel. The FOM-map contains matching codes like high slope, excessive shift