Science.gov

Sample records for brain integrating models

  1. The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

    PubMed Central

    Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.

    2013-01-01

    Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172

  2. Efficient multilevel brain tumor segmentation with integrated bayesian model classification.

    PubMed

    Corso, J J; Sharon, E; Dube, S; El-Saden, S; Sinha, U; Yuille, A

    2008-05-01

    We present a new method for automatic segmentation of heterogeneous image data that takes a step toward bridging the gap between bottom-up affinity-based segmentation methods and top-down generative model based approaches. The main contribution of the paper is a Bayesian formulation for incorporating soft model assignments into the calculation of affinities, which are conventionally model free. We integrate the resulting model-aware affinities into the multilevel segmentation by weighted aggregation algorithm, and apply the technique to the task of detecting and segmenting brain tumor and edema in multichannel magnetic resonance (MR) volumes. The computationally efficient method runs orders of magnitude faster than current state-of-the-art techniques giving comparable or improved results. Our quantitative results indicate the benefit of incorporating model-aware affinities into the segmentation process for the difficult case of glioblastoma multiforme brain tumor. PMID:18450536

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

    ERIC Educational Resources Information Center

    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…

  4. Neurocomputational approaches to modelling multisensory integration in the brain: a review.

    PubMed

    Ursino, Mauro; Cuppini, Cristiano; Magosso, Elisa

    2014-12-01

    The Brain's ability to integrate information from different modalities (multisensory integration) is fundamental for accurate sensory experience and efficient interaction with the environment: it enhances detection of external stimuli, disambiguates conflict situations, speeds up responsiveness, facilitates processes of memory retrieval and object recognition. Multisensory integration operates at several brain levels: in subcortical structures (especially the Superior Colliculus), in higher-level associative cortices (e.g., posterior parietal regions), and even in early cortical areas (such as primary cortices) traditionally considered to be purely unisensory. Because of complex non-linear mechanisms of brain integrative phenomena, a key tool for their understanding is represented by neurocomputational models. This review examines different modelling principles and architectures, distinguishing the models on the basis of their aims: (i) Bayesian models based on probabilities and realizing optimal estimator of external cues; (ii) biologically inspired models of multisensory integration in the Superior Colliculus and in the Cortex, both at level of single neuron and network of neurons, with emphasis on physiological mechanisms and architectural schemes; among the latter, some models exhibit synaptic plasticity and reproduce development of integrative capabilities via Hebbian-learning rules or self-organizing maps; (iii) models of semantic memory that implement object meaning as a fusion between sensory-motor features (embodied cognition). This overview paves the way to future challenges, such as reconciling neurophysiological and Bayesian models into a unifying theory, and stimulates upcoming research in both theoretical and applicative domains. PMID:25218929

  5. Insights From an Integrated Physiologically Based Pharmacokinetic Model for Brain Penetration.

    PubMed

    Trapa, Patrick E; Belova, Elena; Liras, Jenny L; Scott, Dennis O; Steyn, Stefan J

    2016-02-01

    Central-nervous-system, physiologically based pharmacokinetic (PBPK) models predict exposure profiles in the brain, that is, the rate and extent of distribution. The current work develops one such model and presents improved methods for determining key input parameters. A simple linear regression statistical model estimates the passive permeability at the blood-brain barrier from brain uptake index data and descriptors, and a novel analysis extracts the relative active transport parameter from in vitro assays taking into consideration both paracellular transport and unstirred water layers. The integrated PBPK model captures the concentration profiles of both rate-restricted and effluxed compounds with high passive permeability. In many cases, compounds distribute rapidly into the brain and are, therefore, not rate limited. The PBPK model is then simplified to a straightforward equation to describe brain-to-plasma ratios at steady state. The equation can estimate brain penetration either from in vitro efflux data or from in vivo results from another species and, therefore, is a valuable tool in the discovery setting. PMID:26869440

  6. Allostasis and the human brain: Integrating models of stress from the social and life sciences

    PubMed Central

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

    2009-01-01

    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 between stress and health, as well as the neural focus of “wear and tear” due to ongoing adaptation. This mediation, in turn, allows us to model the interplay over time between context, current stressor exposure, internal regulation of bodily processes, and health outcomes. We illustrate how this approach facilitates the integration of current findings in human neuroscience and genetics with key constructs from stress models from the social and life sciences, with implications for future research and the design of interventions targeting individuals at risk. PMID:20063966

  7. Integrated modeling of PET and DTI information based on conformal brain mapping

    NASA Astrophysics Data System (ADS)

    Zou, Guangyu; Xi, Yongjian; Heckenburg, Greg; Duan, Ye; Hua, Jing; Gu, Xiangfeng

    2006-03-01

    Recent advances in imaging technologies, such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) and Diffusion Tensor Imaging (DTI) have accelerated brain research in many aspects. In order to better understand the synergy of the many processes involved in normal brain function, integrated modeling and analysis of MRI, PET, and DTI is highly desirable. Unfortunately, the current state-of-art computational tools fall short in offering a comprehensive computational framework that is accurate and mathematically rigorous. In this paper we present a framework which is based on conformal parameterization of a brain from high-resolution structural MRI data to a canonical spherical domain. This model allows natural integration of information from co-registered PET as well as DTI data and lays the foundation for a quantitative analysis of the relationship between diverse data sets. Consequently, the system can be designed to provide a software environment able to facilitate statistical detection of abnormal functional brain patterns in patients with a large number of neurological disorders.

  8. Using Drosophila as an integrated model to study mild repetitive traumatic brain injury

    PubMed Central

    Barekat, Ayeh; Gonzalez, Arysa; Mauntz, Ruth E.; Kotzebue, Roxanne W.; Molina, Brandon; El-Mecharrafie, Nadja; Conner, Catherine J.; Garza, Shannon; Melkani, Girish C.; Joiner, William J.; Lipinski, Marta M.; Finley, Kim D.; Ratliff, Eric P.

    2016-01-01

    Traumatic brain injury (TBI) is a major cause of morbidity and mortality worldwide. In addition, there has been a growing appreciation that even repetitive, milder forms of TBI (mTBI) can have long-term deleterious consequences to neural tissues. Hampering our understanding of genetic and environmental factors that influence the cellular and molecular responses to injury has been the limited availability of effective genetic model systems that could be used to identify the key genes and pathways that modulate both the acute and long-term responses to TBI. Here we report the development of a severe and mild-repetitive TBI model using Drosophila. Using this system, key features that are typically found in mammalian TBI models were also identified in flies, including the activation of inflammatory and autophagy responses, increased Tau phosphorylation and neuronal defects that impair sleep-related behaviors. This novel injury paradigm demonstrates the utility of Drosophila as an effective tool to validate genetic and environmental factors that influence the whole animal response to trauma and to identify prospective therapies needed for the treatment of TBI. PMID:27143646

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

    PubMed

    Morimoto, Jun; Kawato, Mitsuo

    2015-03-01

    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

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

    PubMed Central

    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

  11. C5a alters blood–brain barrier integrity in a human in vitro model of systemic lupus erythematosus

    PubMed Central

    Mahajan, Supriya D; Parikh, Neil U; Woodruff, Trent M; Jarvis, James N; Lopez, Molly; Hennon, Teresa; Cunningham, Patrick; Quigg, Richard J; Schwartz, Stanley A; Alexander, Jessy J

    2015-01-01

    The blood–brain barrier (BBB) plays a crucial role in brain homeostasis, thereby maintaining the brain environment precise for optimal neuronal function. Its dysfunction is an intriguing complication of systemic lupus erythematosus (SLE). SLE is a systemic autoimmune disorder where neurological complications occur in 5–50% of cases and is associated with impaired BBB integrity. Complement activation occurs in SLE and is an important part of the clinical profile. Our earlier studies demonstrated that C5a generated by complement activation caused the loss of brain endothelial layer integrity in rodents. The goal of the current study was to determine the translational potential of these studies to a human system. To assess this, we used a two dimensional in vitro BBB model constructed using primary human brain microvascular endothelial cells and astroglial cells, which closely emulates the in vivo BBB allowing the assessment of BBB integrity. Increased permeability monitored by changes in transendothelial electrical resistance and cytoskeletal remodelling caused by actin fiber rearrangement were observed when the cells were exposed to lupus serum and C5a, similar to the observations in mice. In addition, our data show that C5a/C5aR1 signalling alters nuclear factor-κB translocation into nucleus and regulates the expression of the tight junction proteins, claudin-5 and zonula occludens 1 in this setting. Our results demonstrate for the first time that C5a regulates BBB integrity in a neuroinflammatory setting where it affects both endothelial and astroglial cells. In addition, we also demonstrate that our previous findings in a mouse model, were emulated in human cells in vitro, bringing the studies one step closer to understanding the translational potential of C5a/C5aR1 blockade as a promising therapeutic strategy in SLE and other neurodegenerative diseases. PMID:26059553

  12. Chronic rapamycin restores brain vascular integrity and function through NO synthase activation and improves memory in symptomatic mice modeling Alzheimer's disease

    PubMed Central

    Lin, Ai-Ling; Zheng, Wei; Halloran, Jonathan J; Burbank, Raquel R; Hussong, Stacy A; Hart, Matthew J; Javors, Martin; Shih, Yen-Yu Ian; Muir, Eric; Solano Fonseca, Rene; Strong, Randy; Richardson, Arlan G; Lechleiter, James D; Fox, Peter T; Galvan, Veronica

    2013-01-01

    Vascular pathology is a major feature of Alzheimer's disease (AD) and other dementias. We recently showed that chronic administration of the target-of-rapamycin (TOR) inhibitor rapamycin, which extends lifespan and delays aging, halts the progression of AD-like disease in transgenic human (h)APP mice modeling AD when administered before disease onset. Here we demonstrate that chronic reduction of TOR activity by rapamycin treatment started after disease onset restored cerebral blood flow (CBF) and brain vascular density, reduced cerebral amyloid angiopathy and microhemorrhages, decreased amyloid burden, and improved cognitive function in symptomatic hAPP (AD) mice. Like acetylcholine (ACh), a potent vasodilator, acute rapamycin treatment induced the phosphorylation of endothelial nitric oxide (NO) synthase (eNOS) and NO release in brain endothelium. Administration of the NOS inhibitor L-NG-Nitroarginine methyl ester reversed vasodilation as well as the protective effects of rapamycin on CBF and vasculature integrity, indicating that rapamycin preserves vascular density and CBF in AD mouse brains through NOS activation. Taken together, our data suggest that chronic reduction of TOR activity by rapamycin blocked the progression of AD-like cognitive and histopathological deficits by preserving brain vascular integrity and function. Drugs that inhibit the TOR pathway may have promise as a therapy for AD and possibly for vascular dementias. PMID:23801246

  13. Integration of jugular venous return and circle of Willis in a theoretical human model of selective brain cooling.

    PubMed

    Neimark, Matthew A; Konstas, Angelos-Aristeidis; Laine, Andrew F; Pile-Spellman, John

    2007-11-01

    A three-dimensional mathematical model was developed to examine the induction of selective brain cooling (SBC) in the human brain by intracarotid cold (2.8 degrees C) saline infusion (ICSI) at 30 ml/min. The Pennes bioheat equation was used to propagate brain temperature. The effect of cooled jugular venous return was investigated, along with the effect of the circle of Willis (CoW) on the intracerebral temperature distribution. The complete CoW, missing A1 variant (mA1), and fetal P1 variant (fP1) were simulated. ICSI induced moderate hypothermia (defined as 32-34 degrees C) in the internal carotid artery (ICA) territory within 5 min. Incorporation of the complete CoW resulted in a similar level of hypothermia in the ICA territory. In addition, the anterior communicating artery and ipsilateral posterior communicating artery distributed cool blood to the contralateral anterior and ipsilateral posterior territories, respectively, imparting mild hypothermia (35 and 35.5 degrees C respectively). The mA1 and fP1 variants allowed for sufficient cooling of the middle cerebral territory (30-32 degrees C). The simulations suggest that ICSI is feasible and may be the fastest method of inducing hypothermia. Moreover, the effect of convective heat transfer via the complete CoW and its variants underlies the important role of CoW anatomy in intracerebral temperature distributions during SBC. PMID:17761787

  14. A framework for integrating the songbird brain

    PubMed Central

    Smith, V.A.; Wada, K.; Rivas, M.V.; McElroy, M.; Smulders, T.V.; Carninci, P.; Hayashizaki, Y.; Dietrich, F.; Wu, X.; McConnell, P.; Yu, J.; Wang, P.P.; Hartemink, A.J.; Lin, S.

    2008-01-01

    Biological systems by default involve complex components with complex relationships. To decipher how biological systems work, we assume that one needs to integrate information over multiple levels of complexity. The songbird vocal communication system is ideal for such integration due to many years of ethological investigation and a discreet dedicated brain network. Here we announce the beginnings of a songbird brain integrative project that involves high-throughput, molecular, anatomical, electrophysiological and behavioral levels of analysis. We first formed a rationale for inclusion of specific biological levels of analysis, then developed high-throughput molecular technologies on songbird brains, developed technologies for combined analysis of electrophysiological activity and gene regulation in awake behaving animals, and developed bioinformatic tools that predict causal interactions within and between biological levels of organization. This integrative brain project is fitting for the interdisciplinary approaches taken in the current songbird issue of the Journal of Comparative Physiology A and is expected to be conducive to deciphering how brains generate and perceive complex behaviors. PMID:12471494

  15. The integration of large-scale neural network modeling and functional brain imaging in speech motor control

    PubMed Central

    Golfinopoulos, E.; Tourville, J.A.; Guenther, F.H.

    2009-01-01

    Speech production demands a number of integrated processing stages. The system must encode the speech motor programs that command movement trajectories of the articulators and monitor transient spatiotemporal variations in auditory and somatosensory feedback. Early models of this system proposed that independent neural regions perform specialized speech processes. As technology advanced, neuroimaging data revealed that the dynamic sensorimotor processes of speech require a distributed set of interacting neural regions. The DIVA (Directions into Velocities of Articulators) neurocomputational model elaborates on early theories, integrating existing data and contemporary ideologies, to provide a mechanistic account of acoustic, kinematic, and functional magnetic resonance imaging (fMRI) data on speech acquisition and production. This large-scale neural network model is composed of several interconnected components whose cell activities and synaptic weight strengths are governed by differential equations. Cells in the model are associated with neuroanatomical substrates and have been mapped to locations in Montreal Neurological Institute stereotactic space, providing a means to compare simulated and empirical fMRI data. The DIVA model also provides a computational and neurophysiological framework within which to interpret and organize research on speech acquisition and production in fluent and dysfluent child and adult speakers. The purpose of this review article is to demonstrate how the DIVA model is used to motivate and guide functional imaging studies. We describe how model predictions are evaluated using voxel-based, region-of-interest-based parametric analyses and inter-regional effective connectivity modeling of fMRI data. PMID:19837177

  16. Integrating Retinoic Acid Signaling with Brain Function

    ERIC Educational Resources Information Center

    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…

  17. From Neurodegeneration to Brain Health: An Integrated Approach.

    PubMed

    Petersen, Robert B; Lissemore, Frances M; Appleby, Brian; Aggarwal, Neelum; Boyatzis, Richard; Casadesus, Gemma; Cummings, Jeff; Jack, Anthony; Perry, George; Safar, Jiri; Sajatovic, Martha; Surewicz, Witold K; Wang, Yanming; Whitehouse, Peter; Lerner, Alan

    2015-01-01

    The term "brain health" integrates general health and well-being with cognitive fitness, in the context of an environment that includes the spectrum of positive and negative factors affecting the individual. Brain health incorporates the effects of neurodegeneration in an ecological sense and the effects of environment and health practices on brain function. It also provides a framework for understanding and maximizing cognitive function across the lifespan. Despite decades of research into the pathogenesis of neurodegenerative disorders, our understanding of how to treat them is relatively rudimentary. Unidimensional approaches, such as medication monotherapies, have generally produced negative results in treatment trials. New integrative paradigms that cut across the molecular and cellular level to the individual and societal level may provide new approaches to understand and treat these disorders. This report on proceedings of a multi-disciplinary conference held in Cleveland, Ohio, in October 2013 summarizes research progress in understanding neurodegenerative disorders in a brain health context. A new "brain health" paradigm is essential to finally understand neurodegenerative disorders such as Alzheimer's disease and overcome the relative stand-still in therapeutics research that has characterized the last decade. The authors summarize progress in these emerging areas with the aim of producing new integrated scientific models for understanding brain health, potentially modifying disease course and advancing care for individuals and families affected by neurodegenerative conditions. PMID:25720413

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

    PubMed

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

    2015-12-01

    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. PMID:26598686

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

    PubMed Central

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

    2015-01-01

    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. PMID:26598686

  20. Multimodal, multidimensional models of mouse brain.

    PubMed

    Mackenzie-Graham, Allan J; Lee, Erh-Fang; Dinov, Ivo D; Yuan, Heng; Jacobs, Russell E; Toga, Arthur W

    2007-01-01

    Naturally occurring mutants and genetically manipulated strains of mice are widely used to model a variety of human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison and to facilitate the integration of anatomic, genetic, and physiologic observations from multiple subjects and experiments. We have developed digital atlases of the C57BL/6J mouse brain (adult and neonate) as comprehensive frameworks for storing and accessing the myriad types of information about the mouse brain. Along with raw and annotated images, these contain database management systems and a set of tools for comparing information from different techniques and different animals. Each atlas establishes a canonical representation of the mouse brain and provides the tools for the manipulation and analysis of new data. We describe both these atlases and discuss how they may be put to use in organizing and analyzing data from mouse models of epilepsy. PMID:17767578

  1. A model for lupus brain disease

    PubMed Central

    Diamond, Betty; Volpe, Bruce T.

    2015-01-01

    Summary Systemic lupus erythematosus is an autoimmune disease characterized by antibodies that bind target autoantigens in multiple organs in the body. In peripheral organs, immune complexes engage the complement cascade, recruiting blood-borne inflammatory cells and initiating tissue inflammation. Immune complex-mediated activation of Fc receptors on infiltrating blood-borne cells and tissue resident cells amplifies an inflammatory cascade with resulting damage to tissue function, ultimately leading to tissue destruction. This pathophysiology appears to explain tissue injury throughout the body, except in the central nervous system. This review addresses a paradigm we have developed for autoantibody-mediated brain damage. This paradigm suggests that antibody-mediated brain disease does not depend on immune complex formation but rather on antibody-mediated alterations in neuronal activation and survival. Moreover, antibodies only access brain tissue when blood-brain barrier integrity is impaired, leading to a lack of concurrence of brain disease and tissue injury in other organs. We discuss the implications of this model for lupus and for identifying other antibodies that may contribute to brain disease. PMID:22725954

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

    PubMed Central

    Zaslavsky, Ilya; Baldock, Richard A.; Boline, Jyl

    2014-01-01

    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 (POI)s, 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 (SRSs) 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 Project. PMID

  3. The LISA Integrated Model

    NASA Technical Reports Server (NTRS)

    Merkowitz, Stephen M.

    2002-01-01

    The Laser Interferometer Space Antenna (LISA) space mission has unique needs that argue for an aggressive modeling effort. These models ultimately need to forecast and interrelate the behavior of the science input, structure, optics, control systems, and many other factors that affect the performance of the flight hardware. In addition, many components of these integrated models will also be used separately for the evaluation and investigation of design choices, technology development and integration and test. This article presents an overview of the LISA integrated modeling effort.

  4. The Integrated Medical Model

    NASA Technical Reports Server (NTRS)

    Kerstman, Eric; Minard, Charles; Saile, Lynn; Freiere deCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

    2010-01-01

    The goals of the Integrated Medical Model (IMM) are to develop an integrated, quantified, evidence-based decision support tool useful to crew health and mission planners and to help align science, technology, and operational activities intended to optimize crew health, safety, and mission success. Presentation slides address scope and approach, beneficiaries of IMM capabilities, history, risk components, conceptual models, development steps, and the evidence base. Space adaptation syndrome is used to demonstrate the model's capabilities.

  5. Searching for the one and many emotional brains. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

    NASA Astrophysics Data System (ADS)

    Armony, Jorge L.

    2015-06-01

    Over the past hundred years or so, several neurally-based, or at least neurally-inspired, models of emotion have been proposed, with varying degrees of acceptance and success. Early ones were mostly based on data obtained from experiments conducted in non-human animals using classical conditioning paradigms, thus focusing on defensive (threat) and appetitive (reward) behaviors. Some features of the models were sometimes confirmed as being also applicable to humans, usually in experiments with patients suffering from focal brain lesions - although inconsistent, or even contradictory findings were often reported.

  6. Left Brain, Right Brain, Super Brain: The Holistic Model.

    ERIC Educational Resources Information Center

    Yellin, David

    Recent discoveries about the whole brain seem to call for a holistic approach to learning, one in which educators would teach the whole person, including physical and emotional states as well as cognitive abilities. Three holistic techniques are particularly relevant to education: (1) biofeedback; (2) yoga; and (3) the Lozanov method. Biofeedback…

  7. What Brain Sciences Reveal about Integrating Theory and Practice

    ERIC Educational Resources Information Center

    Patton, Michael Quinn

    2014-01-01

    Theory and practice are integrated in the human brain. Situation recognition and response are key to this integration. Scholars of decision making and expertise have found that people with great expertise are more adept at situational recognition and intentional about their decision-making processes. Several interdisciplinary fields of inquiry…

  8. Epigenetic Integration of the Developing Brain and Face

    PubMed Central

    Parsons, Trish E.; Schmidt, Eric J.; Boughner, Julia C.; Jamniczky, Heather A.; Marcucio, Ralph S.; Hallgrímsson, Benedikt

    2011-01-01

    The integration of the brain and face and to what extent this relationship constrains or enables evolutionary change in the craniofacial complex is an issue of long-standing interest in vertebrate evolution. To investigate brain-face integration, we studied the covariation between the forebrain and midface at gestational days 10-10.5 in four strains of laboratory mice. We found that phenotypic variation in the forebrain is highly correlated with that of the face during face formation such that variation in the size of the forebrain correlates with the degree of prognathism and orientation of the facial prominences. This suggests strongly that the integration of the brain and face is relevant to the etiology of midfacial malformations such as orofacial clefts. This axis of integration also has important implications for the evolutionary developmental biology of the mammalian craniofacial complex. PMID:21901785

  9. Cilostazol strengthens barrier integrity in brain endothelial cells.

    PubMed

    Horai, Shoji; Nakagawa, Shinsuke; Tanaka, Kunihiko; Morofuji, Yoichi; Couraud, Pierre-Oliver; Deli, Maria A; Ozawa, Masaki; Niwa, Masami

    2013-03-01

    We studied the effect of cilostazol, a selective inhibitor of phosphodiesterase 3, on barrier functions of blood-brain barrier (BBB)-related endothelial cells, primary rat brain capillary endothelial cells (RBEC), and the immortalized human brain endothelial cell line hCMEC/D3. The pharmacological potency of cilostazol was also evaluated on ischemia-related BBB dysfunction using a triple co-culture BBB model (BBB Kit™) subjected to 6-h oxygen glucose deprivation (OGD) and 3-h reoxygenation. There was expression of phosphodiesterase 3B mRNA in RBEC, and a significant increase in intracellular cyclic AMP (cAMP) content was detected in RBEC treated with both 1 and 10 μM cilostazol. Cilostazol increased the transendothelial electrical resistance (TEER), an index of barrier tightness of interendothelial tight junctions (TJs), and decreased the endothelial permeability of sodium fluorescein through the RBEC monolayer. The effects on these barrier functions were significantly reduced in the presence of protein kinase A (PKA) inhibitor H-89. Microscopic observation revealed smooth and even localization of occludin immunostaining at TJs and F-actin fibers at the cell borders in cilostazol-treated RBEC. In hCMEC/D3 cells treated with 1 and 10 μM cilostazol for 24 and 96 h, P-glycoprotein transporter activity was increased, as assessed by rhodamine 123 accumulation. Cilostazol improved the TEER in our triple co-culture BBB model with 6-h OGD and 3-h reoxygenation. As cilostazol stabilized barrier integrity in BBB-related endothelial cells, probably via cAMP/PKA signaling, the possibility that cilostazol acts as a BBB-protective drug against cerebral ischemic insults to neurons has to be considered. PMID:23224787

  10. The Integrated Medical Model

    NASA Technical Reports Server (NTRS)

    Butler, Douglas J.; Kerstman, Eric

    2010-01-01

    This slide presentation reviews the goals and approach for the Integrated Medical Model (IMM). The IMM is a software decision support tool that forecasts medical events during spaceflight and optimizes medical systems during simulations. It includes information on the software capabilities, program stakeholders, use history, and the software logic.

  11. An Integrated Model Recontextualized

    ERIC Educational Resources Information Center

    O'Meara, KerryAnn; Saltmarsh, John

    2016-01-01

    In this commentary, authors KerryAnn O'Meara and John Saltmarsh reflect on their 2008 "Journal of Higher Education Outreach and Engagement" article "An Integrated Model for Advancing the Scholarship of Engagement: Creating Academic Homes for the Engaged Scholar," reprinted in this 20th anniversary issue of "Journal of…

  12. Optical systems integrated modeling

    NASA Technical Reports Server (NTRS)

    Shannon, Robert R.; Laskin, Robert A.; Brewer, SI; Burrows, Chris; Epps, Harlan; Illingworth, Garth; Korsch, Dietrich; Levine, B. Martin; Mahajan, Vini; Rimmer, Chuck

    1992-01-01

    An integrated modeling capability that provides the tools by which entire optical systems and instruments can be simulated and optimized is a key technology development, applicable to all mission classes, especially astrophysics. Many of the future missions require optical systems that are physically much larger than anything flown before and yet must retain the characteristic sub-micron diffraction limited wavefront accuracy of their smaller precursors. It is no longer feasible to follow the path of 'cut and test' development; the sheer scale of these systems precludes many of the older techniques that rely upon ground evaluation of full size engineering units. The ability to accurately model (by computer) and optimize the entire flight system's integrated structural, thermal, and dynamic characteristics is essential. Two distinct integrated modeling capabilities are required. These are an initial design capability and a detailed design and optimization system. The content of an initial design package is shown. It would be a modular, workstation based code which allows preliminary integrated system analysis and trade studies to be carried out quickly by a single engineer or a small design team. A simple concept for a detailed design and optimization system is shown. This is a linkage of interface architecture that allows efficient interchange of information between existing large specialized optical, control, thermal, and structural design codes. The computing environment would be a network of large mainframe machines and its users would be project level design teams. More advanced concepts for detailed design systems would support interaction between modules and automated optimization of the entire system. Technology assessment and development plans for integrated package for initial design, interface development for detailed optimization, validation, and modeling research are presented.

  13. Cardiorespiratory fitness and brain volume and white matter integrity

    PubMed Central

    Zhu, Na; Schreiner, Pamela J.; Launer, Lenore J.; Whitmer, Rachel A.; Sidney, Stephen; Demerath, Ellen; Thomas, William; Bouchard, Claude; He, Ka; Erus, Guray; Battapady, Harsha; Bryan, R. Nick

    2015-01-01

    Objective: We hypothesized that greater cardiorespiratory fitness is associated with lower odds of having unfavorable brain MRI findings. Methods: We studied 565 healthy, middle-aged, black and white men and women in the CARDIA (Coronary Artery Risk Development in Young Adults) Study. The fitness measure was symptom-limited maximal treadmill test duration (Maxdur); brain MRI was measured 5 years later. Brain MRI measures were analyzed as means and as proportions below the 15th percentile (above the 85th percentile for white matter abnormal tissue volume). Results: Per 1-minute-higher Maxdur, the odds ratio for having less whole brain volume was 0.85 (p = 0.04) and for having low white matter integrity was 0.80 (p = 0.02), adjusted for age, race, sex, clinic, body mass index, smoking, alcohol, diet, physical activity, education, blood pressure, diabetes, total cholesterol, and lung function (plus intracranial volume for white matter integrity). No significant associations were observed between Maxdur and abnormal tissue volume or blood flow in white matter. Findings were similar for associations with continuous brain MRI measures. Conclusions: Greater physical fitness was associated with more brain volume and greater white matter integrity measured 5 years later in middle-aged adults. PMID:25957331

  14. Integrated Environmental Control Model

    Energy Science and Technology Software Center (ESTSC)

    1999-09-03

    IECM is a powerful multimedia engineering software program for simulating an integrated coal-fired power plant. It 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 integratedmore » 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 dofferent costs and performance results. A Graphical Use Interface (GUI) facilitates the configuration of the technologies, entry of data, and retrieval of results.« less

  15. Integrated Watershed Modeling

    NASA Astrophysics Data System (ADS)

    Bagulho Galvão, P.; Neves, R.; Silva, A.; Chambel Leitão, P.; Braunchweig, F.

    2004-05-01

    Integrated systems that bring together EO data, local measurements and modeling tools, are a fundamental instrument to help decision making in watershed and land use management. The BASINS system (EPA http://www.epa.gov/OST/BASINS/) follows this philosophy, merging data from local measurement with modeling tools (HSPF, SWAT, PLOAD, QUAL2E). However, remote sensed data is still used in a very static way (usually to define land cover, see corine land cover project). This approach is being replaced with operational methods that use EO data (such as land surface temperature, vegetation state, soil moisture, surface roughness) for both inputs and validation. The development of integrated watershed models that dynamically interact with remote sensed data opens interesting prospective to the validation and improvement of such models. This paper describes the possible data contribution of remote sensing to the needs associated with state of the art watershed models, including well know systems (such as SWAT or HSPF) and a system still under development (MOHID LAND). Application of such models is shown at two pilot sites, which were selected under EU projects, TempQsim and Interreg II B - ICRW.

  16. Realistic modeling of neurons and networks: towards brain simulation

    PubMed Central

    D’Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

    Summary Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field. PMID:24139652

  17. An Embodied Brain Model of the Human Foetus.

    PubMed

    Yamada, Yasunori; Kanazawa, Hoshinori; Iwasaki, Sho; Tsukahara, Yuki; Iwata, Osuke; Yamada, Shigehito; Kuniyoshi, Yasuo

    2016-01-01

    Cortical learning via sensorimotor experiences evoked by bodily movements begins as early as the foetal period. However, the learning mechanisms by which sensorimotor experiences guide cortical learning remain unknown owing to technical and ethical difficulties. To bridge this gap, we present an embodied brain model of a human foetus as a coupled brain-body-environment system by integrating anatomical/physiological data. Using this model, we show how intrauterine sensorimotor experiences related to bodily movements induce specific statistical regularities in somatosensory feedback that facilitate cortical learning of body representations and subsequent visual-somatosensory integration. We also show how extrauterine sensorimotor experiences affect these processes. Our embodied brain model can provide a novel computational approach to the mechanistic understanding of cortical learning based on sensorimotor experiences mediated by complex interactions between the body, environment and nervous system. PMID:27302194

  18. An Embodied Brain Model of the Human Foetus

    PubMed Central

    Yamada, Yasunori; Kanazawa, Hoshinori; Iwasaki, Sho; Tsukahara, Yuki; Iwata, Osuke; Yamada, Shigehito; Kuniyoshi, Yasuo

    2016-01-01

    Cortical learning via sensorimotor experiences evoked by bodily movements begins as early as the foetal period. However, the learning mechanisms by which sensorimotor experiences guide cortical learning remain unknown owing to technical and ethical difficulties. To bridge this gap, we present an embodied brain model of a human foetus as a coupled brain-body-environment system by integrating anatomical/physiological data. Using this model, we show how intrauterine sensorimotor experiences related to bodily movements induce specific statistical regularities in somatosensory feedback that facilitate cortical learning of body representations and subsequent visual-somatosensory integration. We also show how extrauterine sensorimotor experiences affect these processes. Our embodied brain model can provide a novel computational approach to the mechanistic understanding of cortical learning based on sensorimotor experiences mediated by complex interactions between the body, environment and nervous system. PMID:27302194

  19. Integrable models and combinatorics

    NASA Astrophysics Data System (ADS)

    Bogolyubov, N. M.; Malyshev, C. L.

    2015-10-01

    Relations between quantum integrable models solvable by the quantum inverse scattering method and some aspects of enumerative combinatorics and partition theory are discussed. The main example is the Heisenberg XXZ spin chain in the limit cases of zero or infinite anisotropy. Form factors and some thermal correlation functions are calculated, and it is shown that the resulting form factors in a special q-parametrization are the generating functions for plane partitions and self-avoiding lattice paths. The asymptotic behaviour of the correlation functions is studied in the case of a large number of sites and a moderately large number of spin excitations. For sufficiently low temperature a relation is established between the correlation functions and the theory of matrix integrals. Bibliography: 125 titles.

  20. Integrated Assessment Model Evaluation

    NASA Astrophysics Data System (ADS)

    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. Integrated Assessment Modeling

    SciTech Connect

    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.

  2. Modelling convection-enhanced delivery in normal and oedematous brain.

    PubMed

    Haar, P J; Chen, Z-J; Fatouros, P P; Gillies, G T; Corwin, F D; Broaddus, W C

    2014-03-01

    Convection-enhanced delivery (CED) could have clinical applications in the delivery of neuroprotective agents in brain injury states, such as ischaemic stroke. For CED to be safe and effective, a physician must have accurate knowledge of how concentration distributions will be affected by catheter location, flow rate and other similar parameters. In most clinical applications of CED, brain microstructures will be altered by pathological injury processes. Ischaemic stroke and other acute brain injury states are complicated by formation of cytotoxic oedema, in which cellular swelling decreases the fractional volume of the extracellular space (ECS). Such changes would be expected to significantly alter the distribution of neuroprotective agents delivered by CED. Quantitative characterization of these changes will help confirm this prediction and assist in efforts to model the distribution of therapeutic agents. Three-dimensional computational models based on a Nodal Point Integration (NPI) scheme were developed to model infusions in normal brain and brain with cytotoxic oedema. These models were compared to experimental data in which CED was studied in normal brain and in a middle cerebral artery (MCA) occlusion model of cytotoxic oedema. The computational models predicted concentration distributions with reasonable accuracy. PMID:24446800

  3. Chronic systemic IL-1β exacerbates central neuroinflammation independently of the blood-brain barrier integrity.

    PubMed

    Murta, Verónica; Farías, María Isabel; Pitossi, Fernando Juan; Ferrari, Carina Cintia

    2015-01-15

    Peripheral circulating cytokines are involved in immune to brain communication and systemic inflammation is considered a risk factor for flaring up the symptoms in most neurodegenerative diseases. We induced both central inflammatory demyelinating lesion, and systemic inflammation with an interleukin-1β expressing adenovector. The peripheral pro-inflammatory stimulus aggravated the ongoing central lesion independently of the blood-brain barrier (BBB) integrity. This model allows studying the role of specific molecules and cells (neutrophils) from the innate immune system, in the relationship between central and peripheral communication, and on relapsing episodes of demyelinating lesions, along with the role of BBB integrity. PMID:25595250

  4. Physical Activity Affects Brain Integrity in HIV + Individuals

    PubMed Central

    Ortega, Mario; Baker, Laurie M.; Vaida, Florin; Paul, Robert; Basco, Brian; Ances, Beau M.

    2015-01-01

    Prior research has suggested benefits of aerobic physical activity (PA) on cognition and brain volumes in HIV uninfected (HIV−) individuals, however, few studies have explored the relationships between PA and brain integrity (cognition and structural brain volumes) in HIV-infected (HIV +) individuals. Seventy HIV + individuals underwent neuropsychological testing, structural neuroimaging, laboratory tests, and completed a PA questionnaire, recalling participation in walking, running, and jogging activities over the last year. A PA engagement score of weekly metabolic equivalent (MET) hr of activity was calculated using a compendium of PAs. HIV + individuals were classified as physically active (any energy expended above resting expenditure, n = 22) or sedentary (n = 48). Comparisons of neuropsychological performance, grouped by executive and motor domains, and brain volumes were completed between groups. Physically active and sedentary HIV + individuals had similar demographic and laboratory values, but the active group had higher education (14.0 vs. 12.6 years, p = .034). Physically active HIV + individuals performed better on executive (p = .040, unadjusted; p = .043, adjusted) but not motor function (p = .17). In addition, among the physically active group the amount of physical activity (METs) positively correlated with executive (Pearson’s r = 0.45, p = 0.035) but not motor (r = 0.21; p = .35) performance. In adjusted analyses the physically active HIV + individuals had larger putamen volumes (p = .019). A positive relationship exists between PA and brain integrity in HIV + individuals. Results from the present study emphasize the importance to conduct longitudinal interventional investigation to determine if PA improves brain integrity in HIV + individuals. PMID:26581799

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

    PubMed Central

    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

  6. Human midsagittal brain shape variation: patterns, allometry and integration

    PubMed Central

    Bruner, Emiliano; Martin-Loeches, Manuel; Colom, Roberto

    2010-01-01

    Midsagittal cerebral morphology provides a homologous geometrical reference for brain shape and cortical vs. subcortical spatial relationships. In this study, midsagittal brain shape variation is investigated in a sample of 102 humans, in order to describe and quantify the major patterns of correlation between morphological features, the effect of size and sex on general anatomy, and the degree of integration between different cortical and subcortical areas. The only evident pattern of covariation was associated with fronto-parietal cortical bulging. The allometric component was weak for the cortical profile, but more robust for the posterior subcortical areas. Apparent sex differences were evidenced in size but not in brain shape. Cortical and subcortical elements displayed scarcely integrated changes, suggesting a modular separation between these two areas. However, a certain correlation was found between posterior subcortical and parietal cortical variations. These results should be directly integrated with information ranging from functional craniology to wiring organization, and with hypotheses linking brain shape and the mechanical properties of neurons during morphogenesis. PMID:20345859

  7. Human midsagittal brain shape variation: patterns, allometry and integration.

    PubMed

    Bruner, Emiliano; Martin-Loeches, Manuel; Colom, Roberto

    2010-05-01

    Midsagittal cerebral morphology provides a homologous geometrical reference for brain shape and cortical vs. subcortical spatial relationships. In this study, midsagittal brain shape variation is investigated in a sample of 102 humans, in order to describe and quantify the major patterns of correlation between morphological features, the effect of size and sex on general anatomy, and the degree of integration between different cortical and subcortical areas. The only evident pattern of covariation was associated with fronto-parietal cortical bulging. The allometric component was weak for the cortical profile, but more robust for the posterior subcortical areas. Apparent sex differences were evidenced in size but not in brain shape. Cortical and subcortical elements displayed scarcely integrated changes, suggesting a modular separation between these two areas. However, a certain correlation was found between posterior subcortical and parietal cortical variations. These results should be directly integrated with information ranging from functional craniology to wiring organization, and with hypotheses linking brain shape and the mechanical properties of neurons during morphogenesis. PMID:20345859

  8. Reentry: a key mechanism for integration of brain function

    PubMed Central

    Edelman, Gerald M.; Gally, Joseph A.

    2013-01-01

    Reentry in nervous systems is the ongoing bidirectional exchange of signals along reciprocal axonal fibers linking two or more brain areas. The hypothesis that reentrant signaling serves as a general mechanism to couple the functioning of multiple areas of the cerebral cortex and thalamus was first proposed in 1977 and 1978 (Edelman, 1978). A review of the amount and diversity of supporting experimental evidence accumulated since then suggests that reentry is among the most important integrative mechanisms in vertebrate brains (Edelman, 1993). Moreover, these data prompt testable hypotheses regarding mechanisms that favor the development and evolution of reentrant neural architectures. PMID:23986665

  9. Glacial integrative modelling.

    PubMed

    Ganopolski, Andrey

    2003-09-15

    Understanding the mechanisms of past climate changes requires modelling of the complex interaction between all major components of the Earth system: atmosphere, ocean, cryosphere, lithosphere and biosphere. This paper reviews attempts at such an integrative approach to modelling climate changes during the glacial age. In particular, the roles of different factors in shaping glacial climate are compared based on the results of simulations with an Earth-system model of intermediate complexity, CLIMBER-2. It is shown that ice sheets, changes in atmospheric compositions, vegetation cover, and reorganization of the ocean thermohaline circulation play important roles in glacial climate changes. Another example of this approach is the modelling of two major types of abrupt glacial climate changes: Dansgaard-Oeschger and Heinrich events. Our results corroborate some of the early proposed mechanisms, which relate abrupt climate changes to the internal instability of the ocean thermohaline circulation and ice sheets. At the same time, it is shown that realistic representation of the temporal evolution of the palaeoclimatic background is crucial to simulate observed features of the glacial abrupt climate changes. PMID:14558899

  10. An Adaptive Complex Network Model for Brain Functional Networks

    PubMed Central

    Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

    2009-01-01

    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. PMID:19738902

  11. The theory of multistage integration in the visual brain.

    PubMed Central

    Bartels, A; Zeki, S

    1998-01-01

    The theory of multistage integration is based on evidence that the visual brain consists of several parallel multistage processing systems, each specialized for a given attribute such as colour or motion. Each stage of a given system processes information at a distinct level of complexity. Our theory supposes that activity at any stage of a given multistage processing system is perceptually explicit--that is to say, it requires no further processing to generate a conscious experience. This activity can be integrated, or bound, with the perceptually explicit activity at any given stage of another or the same multistage processing system. Such binding is therefore not a process that generates a conscious experience, but rather one that brings different conscious experiences together. Many perceptual advantages result from such a flexible and dynamic integrative system. Conversely, there would be disadvantages to limiting perception and binding to hypothetical 'terminal' stages of such processing systems or to hypothetical 'integrator' areas. Although we formulate our hypothesis in terms of the visual brain, we believe it might form a general principle of brain functioning. PMID:9881478

  12. Integrated Medical Model Overview

    NASA Technical Reports Server (NTRS)

    Myers, J.; Boley, L.; Foy, M.; Goodenow, D.; Griffin, D.; Keenan, A.; Kerstman, E.; Melton, S.; McGuire, K.; Saile, L.; Shah, R.; Garcia, Y.; Sirmons. B.; Walton, M.; Reyes, D.

    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.

  13. Development of a permeability-limited model of the human brain and cerebrospinal fluid (CSF) to integrate known physiological and biological knowledge: Estimating time varying CSF drug concentrations and their variability using in vitro data.

    PubMed

    Gaohua, Lu; Neuhoff, Sibylle; Johnson, Trevor N; Rostami-Hodjegan, Amin; Jamei, Masoud

    2016-06-01

    A 4-compartment permeability-limited brain (4Brain) model consisting of brain blood, brain mass, cranial and spinal cerebrospinal fluid (CSF) compartments has been developed and incorporated into a whole body physiologically-based pharmacokinetic (PBPK) model within the Simcyp Simulator. The model assumptions, structure, governing equations and system parameters are described. The model in particular considers the anatomy and physiology of the brain and CSF, including CSF secretion, circulation and absorption, as well as the function of various efflux and uptake transporters existing on the blood-brain barrier (BBB) and blood-CSF barrier (BCSFB), together with the known parameter variability. The model performance was verified using in vitro data and clinical observations for paracetamol and phenytoin. The simulated paracetamol spinal CSF concentration is comparable with clinical lumbar CSF data for both intravenous and oral doses. Phenytoin CSF concentration-time profiles in epileptic patients were simulated after accounting for disease-induced over-expression of efflux transporters within the BBB. Various 'what-if' scenarios, involving variation of specific drug and system parameters of the model, demonstrated that the 4Brain model is able to simulate the possible impact of transporter-mediated drug-drug interactions, the lumbar puncture process and the age-dependent change in the CSF turnover rate on the local PK within the brain. PMID:27236639

  14. Pediatric Rodent Models of Traumatic Brain Injury.

    PubMed

    Semple, Bridgette D; Carlson, Jaclyn; Noble-Haeusslein, Linda J

    2016-01-01

    Due to a high incidence of traumatic brain injury (TBI) in children and adolescents, age-specific studies are necessary to fully understand the long-term consequences of injuries to the immature brain. Preclinical and translational research can help elucidate the vulnerabilities of the developing brain to insult, and provide model systems to formulate and evaluate potential treatments aimed at minimizing the adverse effects of TBI. Several experimental TBI models have therefore been scaled down from adult rodents for use in juvenile animals. The following chapter discusses these adapted models for pediatric TBI, and the importance of age equivalence across species during model development and interpretation. Many neurodevelopmental processes are ongoing throughout childhood and adolescence, such that neuropathological mechanisms secondary to a brain insult, including oxidative stress, metabolic dysfunction and inflammation, may be influenced by the age at the time of insult. The long-term evaluation of clinically relevant functional outcomes is imperative to better understand the persistence and evolution of behavioral deficits over time after injury to the developing brain. Strategies to modify or protect against the chronic consequences of pediatric TBI, by supporting the trajectory of normal brain development, have the potential to improve quality of life for brain-injured children. PMID:27604726

  15. Quantitative genetic analysis of brain size variation in sticklebacks: support for the mosaic model of brain evolution

    PubMed Central

    Noreikiene, Kristina; Herczeg, Gábor; Gonda, Abigél; Balázs, Gergely; Husby, Arild; Merilä, Juha

    2015-01-01

    The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback (Gasterosteus aculeatus). We found that heritabilities were low (average h2 = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average rG = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high (rG = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks. PMID:26108633

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

    PubMed

    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

  17. Altered Cerebellar White Matter Integrity in Patients with Mild Traumatic Brain Injury in the Acute Stage

    PubMed Central

    Wang, Zhongqiu; Wu, Wenzhong; Liu, Yongkang; Wang, Tianyao; Chen, Xiao; Zhang, Jianhua; Zhou, Guoxing; Chen, Rong

    2016-01-01

    Background and Purpose Imaging studies of traumatic brain injury demonstrate that the cerebellum is often affected. We aim to examine fractional anisotropy alteration in acute-phase mild traumatic brain injury patients in cerebellum-related white matter tracts. Materials and Methods This prospective study included 47 mild traumatic brain injury patients in the acute stage and 37 controls. MR imaging and neurocognitive tests were performed in patients within 7 days of injury. White matter integrity was examined by using diffusion tensor imaging. We used three approaches, tract-based spatial statistics, graphical-model-based multivariate analysis, and region-of-interest analysis, to detect altered cerebellar white matter integrity in mild traumatic brain injury patients. Results Results from three analysis methods were in accordance with each other, and suggested fractional anisotropy in the middle cerebellar peduncle and the pontine crossing tract was changed in the acute-phase mild traumatic brain injury patients, relative to controls (adjusted p-value < 0.05). Higher fractional anisotropy in the middle cerebellar peduncle was associated with worse performance in the fluid cognition composite (r = -0.289, p-value = 0.037). Conclusion Altered cerebellar fractional anisotropy in acute-phase mild traumatic brain injury patients is localized in specific regions and statistically associated with cognitive deficits detectable on neurocognitive testing. PMID:26967320

  18. Functional brain networks underlying detection and integration of disconfirmatory evidence.

    PubMed

    Lavigne, Katie M; Metzak, Paul D; Woodward, Todd S

    2015-05-15

    Processing evidence that disconfirms a prior interpretation is a fundamental aspect of belief revision, and has clear social and clinical relevance. This complex cognitive process requires (at minimum) an alerting stage and an integration stage, and in the current functional magnetic resonance imaging (fMRI) study, we used multivariate analysis methodology on two datasets in an attempt to separate these sequentially-activated cognitive stages and link them to distinct functional brain networks. Thirty-nine healthy participants completed one of two versions of an evidence integration experiment involving rating two consecutive animal images, both of which consisted of two intact images of animal faces morphed together at different ratios (e.g., 70/30 bird/dolphin followed by 10/90 bird/dolphin). The two versions of the experiment differed primarily in terms of stimulus presentation and timing, which facilitated functional interpretation of brain networks based on differences in the hemodynamic response shapes between versions. The data were analyzed using constrained principal component analysis for fMRI (fMRI-CPCA), which allows distinct, simultaneously active task-based networks to be separated, and these were interpreted using both temporal (task-based hemodynamic response shapes) and spatial (dominant brain regions) information. Three networks showed increased activity during integration of disconfirmatory relative to confirmatory evidence: (1) a network involved in alerting to the requirement to revise an interpretation, identified as the salience network (dorsal anterior cingulate cortex and bilateral insula); (2) a sensorimotor response-related network (pre- and post-central gyri, supplementary motor area, and thalamus); and (3) an integration network involving rostral prefrontal, orbitofrontal and posterior parietal cortex. These three networks were staggered in their peak activity (alerting, responding, then integrating), but at certain time points (e

  19. Modeling of functional brain imaging data

    NASA Astrophysics Data System (ADS)

    Horwitz, Barry

    1999-03-01

    The richness and complexity of data sets obtained from functional neuroimaging studies of human cognitive behavior, using techniques such as positron emission tomography and functional magnetic resonance imaging, have until recently not been exploited by computational neural modeling methods. In this article, following a brief introduction to functional neuroimaging methodology, two neural modeling approaches for use with functional brain imaging data are described. One, which uses structural equation modeling, examines the effective functional connections between various brain regions during specific cognitive tasks. The second employs large-scale neural modeling to relate functional neuroimaging signals in multiple, interconnected brain regions to the underlying neurobiological time-varying activities in each region. These two modeling procedures are illustrated using a visual processing paradigm.

  20. Vascular Integrity in the Pathogenesis of Brain Arteriovenous Malformation

    PubMed Central

    Zhang, Rui; Zhu, Wan

    2015-01-01

    Brain arteriovenous malformation (bAVM) is an important cause of intracranial hemorrhage (ICH), particularly in the young population. ICH is the first clinical symptom in about 50 % of bAVM patients. The vessels in bAVM are fragile and prone to rupture, causing bleeding into the brain. About 30 % of unruptured and non-hemorrhagic bAVMs demonstrate microscopic evidence of hemosiderin in the vascular wall. In bAVM mouse models, vascular mural cell coverage is reduced in the AVM lesion, accompanied by vascular leakage and microhemorrhage. In this review, we discuss possible signaling pathways involved in abnormal vascular development in bAVM. PMID:26463919

  1. An integrated network model of psychotic symptoms.

    PubMed

    Looijestijn, Jasper; Blom, Jan Dirk; Aleman, André; Hoek, Hans W; Goekoop, Rutger

    2015-12-01

    The full body of research on the nature of psychosis and its determinants indicates that a considerable number of factors are relevant to the development of hallucinations, delusions, and other positive symptoms, ranging from neurodevelopmental parameters and altered connectivity of brain regions to impaired cognitive functioning and social factors. We aimed to integrate these factors in a single mathematical model based on network theory. At the microscopic level this model explains positive symptoms of psychosis in terms of experiential equivalents of robust, high-frequency attractor states of neural networks. At the mesoscopic level it explains them in relation to global brain states, and at the macroscopic level in relation to social-network structures and dynamics. Due to the scale-free nature of biological networks, all three levels are governed by the same general laws, thereby allowing for an integrated model of biological, psychological, and social phenomena involved in the mediation of positive symptoms of psychosis. This integrated network model of psychotic symptoms (INMOPS) is described together with various possibilities for application in clinical practice. PMID:26432501

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

    PubMed

    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. PMID:27604727

  3. 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.

    NASA Astrophysics Data System (ADS)

    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.

  4. Weight Drop Models in Traumatic Brain Injury.

    PubMed

    Kalish, Brian T; Whalen, Michael J

    2016-01-01

    Weight drop models in rodents have been used for several decades to advance our understanding of the pathophysiology of traumatic brain injury. Weight drop models have been used to replicate focal cerebral contusion as well as diffuse brain injury characterized by axonal damage. More recently, closed head injury models with free head rotation have been developed to model sports concussions, which feature functional disturbances in the absence of overt brain damage assessed by conventional imaging techniques. Here, we describe the history of development of closed head injury models in the first part of the chapter. In the second part, we describe the development of our own weight drop closed head injury model that features impact plus rapid downward head rotation, no structural brain injury, and long-term cognitive deficits in the case of multiple injuries. This rodent model was developed to reproduce key aspects of sports concussion so that a mechanistic understanding of how long-term cognitive deficits might develop will eventually follow. Such knowledge is hoped to impact athletes and war fighters and others who suffer concussive head injuries by leading to targeted therapies aimed at preventing cognitive and other neurological sequelae in these high-risk groups. PMID:27604720

  5. Integrated modeling for the VLTI

    NASA Astrophysics Data System (ADS)

    Mueller, Michael; Wilhelm, Rainer; Baier, Horst; Koehler, Bertrand

    2003-02-01

    Within the scope of the Very Large Telescope Interferometer (VLTI) project, a set of software tools for integrated modeling of ground- and space-based stellar interferometers has been developed. Integrated modeling aims at time-dependent system analysis combining different technical disciplines (optics, mechanical structure, control system with sensors and actuators, environmental disturbances). The main components of the software are BeamWarrior, a tool for creation of dynamic optical models, and SMI (Structural Modeling Interface), which generates linear state-space models from finite element models of a mechanical structure. Based on these tools, models of the various subsystems (e.g. telescope, delay line, beam combiner) can be created in the relevant technical disciplines (e.g. optics, structure). All subsystem models are integrated into the Matlab/Simulink environment for dynamic control system simulations. The output of the dynamic model is a complete description of the time-dependent electromagnetic field in each interferometer arm. This output serves as input to an instrument model simulating the creation of interference fringes. This paper shows the application of the integrated modeling concept to the VLTI. The architecture of a Simulink-based integrated model with its main components, telescope structures, optics and control loops, is presented. Disturbance models for wind load, seismic ground excitation and atmospheric turbulence are included. Beam combination is performed using a simplified model of the VINCI instrument. Results of closed-loop dynamic simulations are presented.

  6. Integrability of the Rabi Model

    SciTech Connect

    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.

  7. Mathematical Model of Evolution of Brain Parcellation.

    PubMed

    Ferrante, Daniel D; Wei, Yi; Koulakov, Alexei A

    2016-01-01

    We study the distribution of brain and cortical area sizes [parcellation units (PUs)] obtained for three species: mouse, macaque, and human. We find that the distribution of PU sizes is close to lognormal. We propose the mathematical model of evolution of brain parcellation based on iterative fragmentation and specialization. In this model, each existing PU has a probability to be split that depends on PU size only. This model suggests that the same evolutionary process may have led to brain parcellation in these three species. Within our model, region-to-region (macro) connectivity is given by the outer product form. We show that most experimental data on non-zero macaque cortex macroscopic-level connections can be explained by the outer product power-law form suggested by our model (62% for area V1). We propose a multiplicative Hebbian learning rule for the macroconnectome that could yield the correct scaling of connection strengths between areas. We thus propose an evolutionary model that may have contributed to both brain parcellation and mesoscopic level connectivity in mammals. PMID:27378859

  8. Mathematical Model of Evolution of Brain Parcellation

    PubMed Central

    Ferrante, Daniel D.; Wei, Yi; Koulakov, Alexei A.

    2016-01-01

    We study the distribution of brain and cortical area sizes [parcellation units (PUs)] obtained for three species: mouse, macaque, and human. We find that the distribution of PU sizes is close to lognormal. We propose the mathematical model of evolution of brain parcellation based on iterative fragmentation and specialization. In this model, each existing PU has a probability to be split that depends on PU size only. This model suggests that the same evolutionary process may have led to brain parcellation in these three species. Within our model, region-to-region (macro) connectivity is given by the outer product form. We show that most experimental data on non-zero macaque cortex macroscopic-level connections can be explained by the outer product power-law form suggested by our model (62% for area V1). We propose a multiplicative Hebbian learning rule for the macroconnectome that could yield the correct scaling of connection strengths between areas. We thus propose an evolutionary model that may have contributed to both brain parcellation and mesoscopic level connectivity in mammals. PMID:27378859

  9. Compact continuum brain model for human electroencephalogram

    NASA Astrophysics Data System (ADS)

    Kim, J. W.; Shin, H.-B.; Robinson, P. A.

    2007-12-01

    A low-dimensional, compact brain model has recently been developed based on physiologically based mean-field continuum formulation of electric activity of the brain. The essential feature of the new compact model is a second order time-delayed differential equation that has physiologically plausible terms, such as rapid corticocortical feedback and delayed feedback via extracortical pathways. Due to its compact form, the model facilitates insight into complex brain dynamics via standard linear and nonlinear techniques. The model successfully reproduces many features of previous models and experiments. For example, experimentally observed typical rhythms of electroencephalogram (EEG) signals are reproduced in a physiologically plausible parameter region. In the nonlinear regime, onsets of seizures, which often develop into limit cycles, are illustrated by modulating model parameters. It is also shown that a hysteresis can occur when the system has multiple attractors. As a further illustration of this approach, power spectra of the model are fitted to those of sleep EEGs of two subjects (one with apnea, the other with narcolepsy). The model parameters obtained from the fittings show good matches with previous literature. Our results suggest that the compact model can provide a theoretical basis for analyzing complex EEG signals.

  10. Integrated Workforce Modeling System

    NASA Technical Reports Server (NTRS)

    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.

  11. The brain and somatic integration: insights into the standard biological rationale for equating "brain death" with death.

    PubMed

    Shewmon, A D

    2001-10-01

    The mainstream rationale for equating "brain death" (BD) with death is that the brain confers integrative unity upon the body, transforming it from a mere collection of organs and tissues to an "organism as a whole." In support of this conclusion, the impressive list of the brain's myriad integrative functions is often cited. Upon closer examination, and after operational definition of terms, however, one discovers that most integrative functions of the brain are actually not somatically integrating, and, conversely, most integrative functions of the body are not brain-mediated. With respect to organism-level vitality, the brain's role is more modulatory than constitutive, enhancing the quality and survival potential of a presupposedly living organism. Integrative unity of a complex organism is an inherently nonlocalizable, holistic feature involving the mutual interaction among all the parts, not a top-down coordination imposed by one part upon a passive multiplicity of other parts. Loss of somatic integrative unity is not a physiologically tenable rationale for equating BD with death of the organism as a whole. PMID:11588655

  12. Direct integration transmittance model

    NASA Technical Reports Server (NTRS)

    Kunde, V. G.; Maguire, W. C.

    1973-01-01

    A transmittance model was developed for the 200-2000/cm region for interpretation of high spectral resolution measurements of laboratory absorption and of planetary thermal emission. The high spectral resolution requires transmittances to be computed monochromatically by summing the contribution of individual molecular absorption lines. A magnetic tape atlas of H2O,O3, and CO2 molecular line parameters serves as input to the transmittance model with simple empirical representations used for continuum regions wherever suitable laboratory data exist. The theoretical formulation of the transmittance model and the computational procedures used for the evaluation of the transmittances are discussed. Application is demonstrated of the model to several homogenous path laboratory absorption examples.

  13. Astrocytic laminin regulates pericyte differentiation and maintains blood brain barrier integrity

    NASA Astrophysics Data System (ADS)

    Yao, Yao; Chen, Zu-Lin; Norris, Erin H.; Strickland, Sidney

    2014-03-01

    Blood brain barrier (BBB) breakdown is not only a consequence of but also contributes to many neurological disorders, including stroke and Alzheimer’s disease. How the basement membrane (BM) contributes to the normal functioning of the BBB remains elusive. Here we use conditional knockout mice and an acute adenovirus-mediated knockdown model to show that lack of astrocytic laminin, a brain-specific BM component, induces BBB breakdown. Using functional blocking antibody and RNAi, we further demonstrate that astrocytic laminin, by binding to integrin α2 receptor, prevents pericyte differentiation from the BBB-stabilizing resting stage to the BBB-disrupting contractile stage, and thus maintains the integrity of BBB. Additionally, loss of astrocytic laminin decreases aquaporin-4 (AQP4) and tight junction protein expression. Altogether, we report a critical role for astrocytic laminin in BBB regulation and pericyte differentiation. These results indicate that astrocytic laminin maintains the integrity of BBB through, at least in part, regulation of pericyte differentiation.

  14. Modulation of semantic integration as a function of syntactic expectations: event-related brain potential evidence.

    PubMed

    Isel, Frédéric; Shen, Weilin

    2011-03-30

    This study investigated syntax-semantics interactions during spoken sentence comprehension. We showed that expectations of phrase-structure incongruencies, which were induced by the experimental instructions, although not actually present in the sentences, were able to block the process of semantic integration. Although this process is usually associated with an N400 event-related brain potential component, here we found a P600, that is, an event-related brain potential component that is thought to reflect syntactic revision. This finding lends support to neurophysiological models of sentence interpretation, which postulates that the lexical-semantic integration of a given word can take place only when syntactic analysis has been successfully completed. PMID:21358555

  15. Integration of vascular systems between the brain and spinal cord in zebrafish.

    PubMed

    Kimura, Eiji; Isogai, Sumio; Hitomi, Jiro

    2015-10-01

    Cerebral and spinal vascular systems are organized individually, and they then conjugate at their border, through the integration of basilar artery and vertebral arteries. Zebrafish (Danio rerio) is an ideal organism for studying early vascular development, and the precise procedure of cranial and truncal vascular formation has been previously demonstrated using this model. However, the stepwise process of the integration between the brain and spinal cord has not been clearly elucidated. In this study, we describe the integration of the independent vascular systems for the brain and spinal cord, using transgenic zebrafish expressing enhanced green fluorescent protein in endothelial cells. Initially, basilar artery and primordial hindbrain channels, into which internal carotid arteries supplied blood, were connected with dorsal longitudinal anastomose vessels, via the first intersegmental artery. This initial connection was not influenced by flow dynamics, suggesting that vascular integration in this region is controlled by genetic cues. Vertebral arteries were formed individually as longitudinal vessels beneath the spinal cord, and became integrated with the basilar artery during subsequent remodeling. Furthermore, we confirmed the basal vasculature was well conserved in adult zebrafish. Observations of vascular integration presented herein will contribute to an understanding of regulatory mechanisms behind this process. PMID:26234750

  16. Neurodynamical model of collective brain

    NASA Technical Reports Server (NTRS)

    Zak, Michail

    1992-01-01

    A dynamical system which mimics collective purposeful activities of a set of units of intelligence is introduced and discussed. A global control of the unit activities is replaced by the probabilistic correlations between them. These correlations are learned during a long term period of performing collective tasks, and are stored in the synaptic interconnections. The model is represented by a system of ordinary differential equations with terminal attractors and repellers, and does not contain any man-made digital devices.

  17. Brain mechanisms for reading words and pseudowords: an integrated approach.

    PubMed

    Simos, Panagiotis G; Breier, Joshua I; Fletcher, Jack M; Foorman, Barbara R; Castillo, Eduardo M; Papanicolaou, Andrew C

    2002-03-01

    The present study tested two predictions of dual-process models of reading: (i) that the brain structures involved in sublexical phonological analysis and those involved in whole-word phonological access during reading are different; and (ii) that reading of meaningful items, by means of the addressed phonology process, is mediated by different brain structures than reading of meaningless letter strings. We obtained brain activation profiles using Magnetic Source Imaging and, in addition, pronunciation latencies during reading of: (i) exception words (primarily involving addressed phonology and having meaning), (ii) pseudohomophones (requiring assembled phonology and having meaning), and (iii) pseudowords (requiring assembled phonology but having no meaning). Reading of meaningful items entailed a high degree of activation of the left posterior middle temporal gyrus (MTGp) and mesial temporal lobe areas, whereas reading the meaningless pseudowords was associated with much reduced activation of these two regions. Reading of all three types of print resulted in activation of the posterior superior temporal gyrus (STGp), inferior parietal and basal temporal areas. In addition, pronunciation speed of exception words correlated significantly with the onset of activity in MTGp but not STGp, whereas the opposite was true for pseudohomophones and pseudowords. These findings are consistent with the existence of two different brain mechanisms that support phonological processing in word reading: one mechanism that subserves assembled phonology and depends on the posterior part of STGp, and a second mechanism that is responsible for pronouncing words with rare print-to-sound correspondences and does not necessarily involve this region but instead appears to depend on MTGp. PMID:11839603

  18. Integrated modeling for the VLTI

    NASA Astrophysics Data System (ADS)

    Muller, Michael; Wilhelm, Rainer C.; Baier, Horst J.; Koch, Franz

    2004-07-01

    Within the scope of the Very Large Telescope Interferometer (VLTI) project, ESO has developed a software package for integrated modeling of single- and multi-aperture optical telescopes. Integrated modeling is aiming at time-dependent system analysis combining different technical disciplines (optics, mechanical structure, control system with sensors and actuators, environmental disturbances). This allows multi-disciplinary analysis and gives information about cross-coupling effects for system engineering of complex stellar interferometers and telescopes. At the moment the main components of the Integrated Modeling Toolbox are BeamWarrior, a numerical tool for optical analysis of single- and multi-aperture telescopes, and the Structural Modeling Interface, which allows to generate Simulink blocks with reduced size from Finite Element Models of a telescope structure. Based on these tools, models of the various subsystems (e.g. telescope, delay line, beam combiner, atmosphere) can be created in the appropriate disciplines (e.g. optics, structure, disturbance). All subsystem models are integrated into the Matlab/Simulink environment for dynamic control system simulations. The basic output of the model is a complete description of the time-dependent electromagnetic field in each interferometer arm. Alternatively, a more elaborated output can be created, such as an interference fringe pattern at the focus of a beam combining instrument. The concern of this paper is the application of the modeling concept to large complex telescope systems. The concept of the Simulink-based integrated model with the main components telescope structure, optics and control loops is presented. The models for wind loads and atmospheric turbulence are explained. Especially the extension of the modeling approach to a 50 - 100 m class telescope is discussed.

  19. INTEGRATED PLANNING MODEL - EPA APPLICATIONS

    EPA Science Inventory

    The Integrated Planning Model (IPM) is a multi-regional, dynamic, deterministic linear programming (LP) model of the electric power sector in the continental lower 48 states and the District of Columbia. It provides forecasts up to year 2050 of least-cost capacity expansion, elec...

  20. Multiscale modeling of brain blow flow

    NASA Astrophysics Data System (ADS)

    Karniadakis, George

    2014-11-01

    Cardiovascular pathologies, such as brain aneurysms, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum, 3D or 1D) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We will present a physical model of the brain vasculature consisting at the macro level of all major arteries (about 200 down to 0.5 mm), at the mesoscale the fractal arteriolar tree (more than 10 millions down to 20 nm) and at the microscale the capillary bed. Correspondingly, we employ three different methods to model the total brain vasculature by developing proper interface conditions at each level. We will present examples from aneurysms and other hematological diseases, where red blood cell rheology is modeled explicitly.

  1. Melatonin Preserves Blood-Brain Barrier Integrity and Permeability via Matrix Metalloproteinase-9 Inhibition

    PubMed Central

    Alluri, Himakarnika; Wilson, Rickesha L.; Anasooya Shaji, Chinchusha; Wiggins-Dohlvik, Katie; Patel, Savan; Liu, Yang; Peng, Xu; Beeram, Madhava R.; Davis, Matthew L.; Huang, Jason H.; Tharakan, Binu

    2016-01-01

    Microvascular hyperpermeability that occurs at the level of the blood-brain barrier (BBB) often leads to vasogenic brain edema and elevated intracranial pressure following traumatic brain injury (TBI). At a cellular level, tight junction proteins (TJPs) between neighboring endothelial cells maintain the integrity of the BBB via TJ associated proteins particularly, zonula occludens-1 (ZO-1) that binds to the transmembrane TJPs and actin cytoskeleton intracellularly. The pro-inflammatory cytokine, interleukin-1β (IL-1β) as well as the proteolytic enzymes, matrix metalloproteinase-9 (MMP-9) are key mediators of trauma-associated brain edema. Recent studies indicate that melatonin a pineal hormone directly binds to MMP-9 and also might act as its endogenous inhibitor. We hypothesized that melatonin treatment will provide protection against TBI-induced BBB hyperpermeability via MMP-9 inhibition. Rat brain microvascular endothelial cells grown as monolayers were used as an in vitro model of the BBB and a mouse model of TBI using a controlled cortical impactor was used for all in vivo studies. IL-1β (10 ng/mL; 2 hours)-induced endothelial monolayer hyperpermeability was significantly attenuated by melatonin (10 μg/mL; 1 hour), GM6001 (broad spectrum MMP inhibitor; 10 μM; 1 hour), MMP-9 inhibitor-1 (MMP-9 specific inhibitor; 5 nM; 1 hour) or MMP-9 siRNA transfection (48 hours) in vitro. Melatonin and MMP-9 inhibitor-1 pretreatment attenuated IL-1β-induced MMP-9 activity, loss of ZO-1 junctional integrity and f-actin stress fiber formation. IL-1β treatment neither affected ZO-1 protein or mRNA expression or cell viability. Acute melatonin treatment attenuated BBB hyperpermeability in a mouse controlled cortical impact model of TBI in vivo. In conclusion, one of the protective effects of melatonin against BBB hyperpermeability occurs due to enhanced BBB integrity via MMP-9 inhibition. In addition, acute melatonin treatment provides protection against BBB

  2. A Logical Model of Conceptual Integrity in Data Integration

    PubMed Central

    Flater, David

    2003-01-01

    Conceptual integrity is required for the result of data integration to be cohesive and sensible. Compromised conceptual integrity results in “semantic faults,” which are commonly blamed for latent integration bugs. A logical model of conceptual integrity in data integration and a simple example application are presented. Unlike constructive models that attempt to prevent semantic faults, this model allows both correct and incorrect integrations to be described. Imperfect legacy systems can therefore be modeled, allowing a more formal analysis of their flaws and the possible remedies.

  3. Separations and safeguards model integration.

    SciTech Connect

    Cipiti, Benjamin B.; Zinaman, Owen

    2010-09-01

    Research and development of advanced reprocessing plant designs can greatly benefit from the development of a reprocessing plant model capable of transient solvent extraction chemistry. This type of model can be used to optimize the operations of a plant as well as the designs for safeguards, security, and safety. Previous work has integrated a transient solvent extraction simulation module, based on the Solvent Extraction Process Having Interaction Solutes (SEPHIS) code developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM) developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The goal of this work was to strengthen the integration by linking more variables between the two codes. The results from this integrated model show expected operational performance through plant transients. Additionally, ORIGEN source term files were integrated into the SSPM to provide concentrations, radioactivity, neutron emission rate, and thermal power data for various spent fuels. This data was used to generate measurement blocks that can determine the radioactivity, neutron emission rate, or thermal power of any stream or vessel in the plant model. This work examined how the code could be expanded to integrate other separation steps and benchmark the results to other data. Recommendations for future work will be presented.

  4. Mouse Genetic Models of Human Brain Disorders.

    PubMed

    Leung, Celeste; Jia, Zhengping

    2016-01-01

    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 behavioral 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. PMID:27047540

  5. Mouse Genetic Models of Human Brain Disorders

    PubMed Central

    Leung, Celeste; Jia, Zhengping

    2016-01-01

    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 behavioral 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. PMID:27047540

  6. Dynamic geometry, brain function modeling, and consciousness.

    PubMed

    Roy, Sisir; Llinás, Rodolfo

    2008-01-01

    Pellionisz and Llinás proposed, years ago, a geometric interpretation towards understanding brain function. This interpretation assumes that the relation between the brain and the external world is determined by the ability of the central nervous system (CNS) to construct an internal model of the external world using an interactive geometrical relationship between sensory and motor expression. This approach opened new vistas not only in brain research but also in understanding the foundations of geometry itself. The approach named tensor network theory is sufficiently rich to allow specific computational modeling and addressed the issue of prediction, based on Taylor series expansion properties of the system, at the neuronal level, as a basic property of brain function. It was actually proposed that the evolutionary realm is the backbone for the development of an internal functional space that, while being purely representational, can interact successfully with the totally different world of the so-called "external reality". Now if the internal space or functional space is endowed with stochastic metric tensor properties, then there will be a dynamic correspondence between events in the external world and their specification in the internal space. We shall call this dynamic geometry since the minimal time resolution of the brain (10-15 ms), associated with 40 Hz oscillations of neurons and their network dynamics, is considered to be responsible for recognizing external events and generating the concept of simultaneity. The stochastic metric tensor in dynamic geometry can be written as five-dimensional space-time where the fifth dimension is a probability space as well as a metric space. This extra dimension is considered an imbedded degree of freedom. It is worth noticing that the above-mentioned 40 Hz oscillation is present both in awake and dream states where the central difference is the inability of phase resetting in the latter. This framework of dynamic

  7. Integrative variable selection via Bayesian model uncertainty.

    PubMed

    Quintana, M A; Conti, D V

    2013-12-10

    We are interested in developing integrative approaches for variable selection problems that incorporate external knowledge on a set of predictors of interest. In particular, we have developed an integrative Bayesian model uncertainty (iBMU) method, which formally incorporates multiple sources of data via a second-stage probit model on the probability that any predictor is associated with the outcome of interest. Using simulations, we demonstrate that iBMU leads to an increase in power to detect true marginal associations over more commonly used variable selection techniques, such as least absolute shrinkage and selection operator and elastic net. In addition, iBMU leads to a more efficient model search algorithm over the basic BMU method even when the predictor-level covariates are only modestly informative. The increase in power and efficiency of our method becomes more substantial as the predictor-level covariates become more informative. Finally, we demonstrate the power and flexibility of iBMU for integrating both gene structure and functional biomarker information into a candidate gene study investigating over 50 genes in the brain reward system and their role with smoking cessation from the Pharmacogenetics of Nicotine Addiction and Treatment Consortium. PMID:23824835

  8. White Matter Integrity Supports BOLD Signal Variability and Cognitive Performance in the Aging Human Brain

    PubMed Central

    Burzynska, Agnieszka Z.; Wong, Chelsea N.; Voss, Michelle W.; Cooke, Gillian E.; McAuley, Edward; Kramer, Arthur F.

    2015-01-01

    Decline in cognitive performance in old age is linked to both suboptimal neural processing in grey matter (GM) and reduced integrity of white matter (WM), but the whole-brain structure-function-cognition associations remain poorly understood. Here we apply a novel measure of GM processing–moment-to-moment variability in the blood oxygenation level-dependent signal (SDBOLD)—to study the associations between GM function during resting state, performance on four main cognitive domains (i.e., fluid intelligence, perceptual speed, episodic memory, vocabulary), and WM microstructural integrity in 91 healthy older adults (aged 60-80 years). We modeled the relations between whole-GM SDBOLD with cognitive performance using multivariate partial least squares analysis. We found that greater SDBOLD was associated with better fluid abilities and memory. Most of regions showing behaviorally relevant SDBOLD (e.g., precuneus and insula) were localized to inter- or intra-network “hubs” that connect and integrate segregated functional domains in the brain. Our results suggest that optimal dynamic range of neural processing in hub regions may support cognitive operations that specifically rely on the most flexible neural processing and complex cross-talk between different brain networks. Finally, we demonstrated that older adults with greater WM integrity in all major WM tracts had also greater SDBOLD and better performance on tests of memory and fluid abilities. We conclude that SDBOLD is a promising functional neural correlate of individual differences in cognition in healthy older adults and is supported by overall WM integrity. PMID:25853882

  9. ITI: The Model. Integrated Thematic Instruction. Third Edition.

    ERIC Educational Resources Information Center

    Kovalik, Susan; Olsen, Karen

    This book presents Integrated Thematic Instruction (ITI), a model for implementing a "brain-compatible" learning environment for students and teachers using a year-long theme to organize curriculum content and skills. The book's introduction identifies six "mismemes" (or mistaken ideas) that have hindered educational reform, and proposes seven…

  10. Verbal Neuropsychological Functions in Aphasia: An Integrative Model

    ERIC Educational Resources Information Center

    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…

  11. Imatinib treatment reduces brain injury in a murine model of traumatic brain injury

    PubMed Central

    Su, Enming J.; Fredriksson, Linda; Kanzawa, Mia; Moore, Shannon; Folestad, Erika; Stevenson, Tamara K.; Nilsson, Ingrid; Sashindranath, Maithili; Schielke, Gerald P.; Warnock, Mark; Ragsdale, Margaret; Mann, Kris; Lawrence, Anna-Lisa E.; Medcalf, Robert L.; Eriksson, Ulf; Murphy, Geoffrey G.; Lawrence, Daniel A.

    2015-01-01

    Current therapies for Traumatic brain injury (TBI) focus on stabilizing individuals and on preventing further damage from the secondary consequences of TBI. A major complication of TBI is cerebral edema, which can be caused by the loss of blood brain barrier (BBB) integrity. Recent studies in several CNS pathologies have shown that activation of latent platelet derived growth factor-CC (PDGF-CC) within the brain can promote BBB permeability through PDGF receptor α (PDGFRα) signaling, and that blocking this pathway improves outcomes. In this study we examine the efficacy for the treatment of TBI of an FDA approved antagonist of the PDGFRα, Imatinib. Using a murine model we show that Imatinib treatment, begun 45 min after TBI and given twice daily for 5 days, significantly reduces BBB dysfunction. This is associated with significantly reduced lesion size 24 h, 7 days, and 21 days after TBI, reduced cerebral edema, determined from apparent diffusion co-efficient (ADC) measurements, and with the preservation of cognitive function. Finally, analysis of cerebrospinal fluid (CSF) from human TBI patients suggests a possible correlation between high PDGF-CC levels and increased injury severity. Thus, our data suggests a novel strategy for the treatment of TBI with an existing FDA approved antagonist of the PDGFRα. PMID:26500491

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

    PubMed

    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. PMID:26192748

  13. Traumatic Brain Injury Models in Animals.

    PubMed

    Rostami, Elham

    2016-01-01

    Traumatic brain injury (TBI) is the leading cause of death in young adults in industrialized nations and in the developing world the WHO considers TBI a silent epidemic caused by an increasing number of traffic accidents. Despite the major improvement of TBI outcome in the acute setting in the past 20 years, the assessment, therapeutic interventions, and prevention of long-term complications remain a challenge. In order to get a deeper insight into the pathology of TBI and advancement of medical understanding and clinical progress experimental animal models are an essential requirement. This chapter provides an overview of most commonly used experimental animal TBI models and the pathobiological findings based on current data. In addition, limitations and advantages of each TBI model are mentioned. This will hopefully give an insight into the possibilities of each model and be of value in choosing one when designing a study. PMID:27604712

  14. Modelling the anesthetized brain with ensembles of neuronal and astrocytic oscillators

    NASA Astrophysics Data System (ADS)

    Hansard, T.; Hale, A. C.; Stefanovska, A.

    2013-01-01

    We propose a minimalistic model of the anesthetized brain in order to study the generation of rhythms observed in electroencephalograms (EEGs) recorded from anesthetized humans. We propose that non-neuronal brain cells-astrocytes-play an important role in brain dynamics and that oscillation-based models may provide a simple way to study such dynamics. The model is capable of replicating the main features (i.e. slow and alpha oscillations) observed in EEGs. In addition, this model suggests that astrocytes are integral to the generation of slow EEG (˜0.7 Hz) rhythms. By including astrocytes in the model we take a first step towards investigating the interaction of the brain and cardiovasular system which are primarily connected via astrocytes. The model also illustrates that rich nonlinear dynamics can arise from basic oscillatory "building blocks" and therefore complex systems may be modelled in an uncomplicated way.

  15. Lifetime experiences, the brain and personalized medicine: an integrative perspective.

    PubMed

    McEwen, Bruce S; Getz, Linn

    2013-01-01

    The aim of personalized medicine is to base medical prevention and therapy on the unique health and disease susceptibility profile of each individual. Starting from this idea, we briefly discuss the meaning of the word 'personalized' before analyzing the practical content of personalized healthcare. From a medical perspective, knowledge of a person encompasses both biological and biographical perspectives. The latter includes significant events and experiences throughout the person's lifespan, from conception to the present, in which epigenetic influences play an important role. In practice, we believe personalized medicine should emphasize the development and maintenance of a healthy nervous system. The neurobiological processes involved here depend heavily on the psychosocial environment, in particular the presence of responsible, caring adults and integration in a reasonably fair society. A healthy brain subsequently promotes good health throughout life, both through direct, favorable influences on the body's intrinsic biological pathways, and indirectly by enabling the person to engage in supportive relationships, make wise decisions and take good care of him/herself. From a public health perspective, we conclude that hi-tech personalized medicine based on detailed bio-molecular mapping, monitoring and tailored drug interventions holds promise only as part of a wider, socio-culturally informed approach to the person. PMID:23009787

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

    PubMed

    Knudsen, Gitte M; Jensen, Peter S; Erritzoe, David; Baaré, William F C; Ettrup, Anders; Fisher, Patrick M; Gillings, Nic; Hansen, Hanne D; Hansen, Lars Kai; Hasselbalch, Steen G; Henningsson, Susanne; Herth, Matthias M; Holst, Klaus K; Iversen, Pernille; Kessing, Lars V; Macoveanu, Julian; Madsen, Kathrine Skak; Mortensen, Erik L; Nielsen, Finn Årup; Paulson, Olaf B; Siebner, Hartwig R; Stenbæk, Dea S; Svarer, Claus; Jernigan, Terry L; Strother, Stephen C; Frokjaer, Vibe G

    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 related to the serotonergic transmitter system with its normative data on the serotonergic subtype receptors 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4 and the 5-HT transporter (5-HTT), but can easily serve other purposes. The Cimbi database and Cimbi biobank were formally established in 2008 with the purpose to store the wealth of Cimbi-acquired data in a highly structured and standardized manner in accordance with the regulations issued by the Danish Data Protection Agency as well as to provide a quality-controlled resource for future hypothesis-generating and hypothesis-driven studies. The Cimbi database currently comprises a total of 1100 PET and 1000 structural and functional MRI scans and it holds a multitude of additional data, such as genetic and biochemical data, and scores from 17 self-reported questionnaires and from 11 neuropsychological paper/computer tests. The database associated Cimbi biobank 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. PMID:25891375

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

    PubMed Central

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

    2005-01-01

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

  18. Combining the boundary shift integral and tensor-based morphometry for brain atrophy estimation

    NASA Astrophysics Data System (ADS)

    Michalkiewicz, Mateusz; Pai, Akshay; Leung, Kelvin K.; Sommer, Stefan; Darkner, Sune; Sørensen, Lauge; Sporring, Jon; Nielsen, Mads

    2016-03-01

    Brain atrophy from structural magnetic resonance images (MRIs) is widely used as an imaging surrogate marker for Alzheimers disease. Their utility has been limited due to the large degree of variance and subsequently high sample size estimates. The only consistent and reasonably powerful atrophy estimation methods has been the boundary shift integral (BSI). In this paper, we first propose a tensor-based morphometry (TBM) method to measure voxel-wise atrophy that we combine with BSI. The combined model decreases the sample size estimates significantly when compared to BSI and TBM alone.

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

    PubMed Central

    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.

    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 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. Results 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). Conclusions Children with mildRF+ TBI or moderate/severe TBI have impaired visual integration efficiency, which may contribute to poorer general

  20. Integrated modeling: a look back

    NASA Astrophysics Data System (ADS)

    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.

  1. Fractional Modeling of Viscoelasticity in Brain Aneurysms

    NASA Astrophysics Data System (ADS)

    Yu, Yue; Karniadakis, George

    2014-11-01

    We develop fundamental new numerical methods for fractional order PDEs, and investigate corresponding models for arterial walls. Specifically, the arterial wall is a heterogeneous soft tissue with complex biomechanical properties, and its constitutive laws are typically derived using integer-order differential equations. However, recent simulations on 1D model have indicated that fractional order models may offer a more powerful alternative for describing arterial wall mechanics, because they are less sensitive to the parameter estimation compared with the integer-calculus-based models. We study the specific fractional PDEs that better model the properties of the 3D arterial walls, and for the first time employ them in simulating flow structure interactions for patient-specific brain aneurysms. A comparison study indicates that for the integer order models, the viscous behavior strongly depends on the relaxation parameters while the fractional order models are less sensitive. This finding is consistent with what is observed in the 1D models for arterial networks (Perdikaris & Karniadakis, 2014), except that when the fractional order is small, the 3D fractional-order models are more sensitive to the fractional order compared to the 1D models.

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

    PubMed Central

    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

  3. Highlighting the structure-function relationship of the brain with the Ising model and graph theory.

    PubMed

    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

  4. SyM-BBB: A Microfluidic Blood Brain Barrier Model

    PubMed Central

    Prabhakarpandian, Balabhaskar; Shen, Ming-Che; Nichols, Joseph B.; Mills, Ivy R.; Sidoryk-Wegrzynowicz, Marta; Aschner, Michael; Pant, Kapil

    2013-01-01

    Current techniques for mimicking the Blood-Brain Barrier (BBB) largely use incubation chambers (Transwell) separated with a filter and matrix coating to represent and to study barrier permeability. These devices have several critical shortcomings; (a) they do not reproduce critical microenvironmental parameters, primarily anatomical size or hemodynamic shear stress, (b) they often do not provide real-time visualization capability, and (c) they require a large amount of consumables. To overcome these limitations, we have developed a microfluidics based Synthetic Microvasculature model of the Blood-Brain Barrier (SyM-BBB). The SyM-BBB platform is comprised of a plastic, disposable and optically clear microfluidic chip with a microcirculation sized two-compartment chamber. The chamber is designed in such a way as to permit the realization of side-by-side apical and basolateral compartments, thereby simplifying fabrication and facilitating integration with standard instrumentation. The individually addressable apical side is seeded with endothelial cells and the basolateral side can support neuronal cells or conditioned media. In the present study, an immortalized Rat Brain Endothelial cell line (RBE4) was cultured in SyM-BBB with a perfusate of Astrocyte Conditioned Media (ACM). Biochemical analysis showed upregulation of tight junction molecules while permeation studies showed an intact BBB. Finally, transporter assay was successfully demonstrated in SyM-BBB indicating a functional model. PMID:23344641

  5. On a Quantum Model of Brain Activities

    NASA Astrophysics Data System (ADS)

    Fichtner, K.-H.; Fichtner, L.; Freudenberg, W.; Ohya, M.

    2010-01-01

    One of the main activities of the brain is the recognition of signals. A first attempt to explain the process of recognition in terms of quantum statistics was given in [6]. Subsequently, details of the mathematical model were presented in a (still incomplete) series of papers (cf. [7, 2, 5, 10]). In the present note we want to give a general view of the principal ideas of this approach. We will introduce the basic spaces and justify the choice of spaces and operations. Further, we bring the model face to face with basic postulates any statistical model of the recognition process should fulfill. These postulates are in accordance with the opinion widely accepted in psychology and neurology.

  6. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.

    PubMed

    Niessen, Wiro J

    2016-10-01

    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role. PMID:27344937

  7. The integrated environmental control model

    SciTech Connect

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

    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. Why Brains Matter: An Integrational Perspective on "The Symbolic Species."

    ERIC Educational Resources Information Center

    Cowley, Stephen J.

    2002-01-01

    Argues that Deacon's coevolutionary theory provides a basis for changing how we think about language and brains. Instead of ascribing language to either nature or nurture, it is seen as intrinsic to both: biological principles ensure the brain can only function by attuning to its body's worlds. (Author/VWL)

  9. Multiscale modeling and simulation of brain blood flow

    NASA Astrophysics Data System (ADS)

    Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

    2016-02-01

    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.

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

    PubMed

    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. PMID:27385926

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

    PubMed Central

    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. PMID:27385926

  12. Statistical analysis of brain sulci based on active ribbon modeling

    NASA Astrophysics Data System (ADS)

    Barillot, Christian; Le Goualher, Georges; Hellier, Pierre; Gibaud, Bernard

    1999-05-01

    This paper presents a general statistical framework for modeling deformable object. This model is devoted being used in digital brain atlases. We first present a numerical modeling of brain sulci. We present also a method to characterize the high inter-individual variability of basic cortical structures on which the description of the cerebral cortex is based. The aimed applications use numerical modeling of brain sulci to assist non-linear registration of human brains by inter-individual anatomical matching or to better compare neuro-functional recordings performed on a series of individuals. The utilization of these methods is illustrated using a few examples.

  13. The integrated urban land model

    NASA Astrophysics Data System (ADS)

    Meng, Chunlei

    2015-06-01

    An integrated urban land model (IUM) was developed based on the Common Land Model (CoLM). A whole layer soil evaporation parameterization scheme was developed to improve soil evaporation simulation especially in arid areas. For the urban underlying surface, the energy and water balance model were modified; urban land parameters such as the anthropogenic heat (AH), albedo, surface roughness length, imperious surface evaporation etc. were also reparameterized. IUM was validated and compared with CoLM and the urbanized high-resolution land data assimilation system (u-HRLDAS) in single and regional scale. The validation results indicate that IUM can improve the simulation of land surface parameters and land-atmosphere interaction fluxes.

  14. Bryostatin-1 Restores Blood Brain Barrier Integrity following Blast-Induced Traumatic Brain Injury.

    PubMed

    Lucke-Wold, Brandon P; Logsdon, Aric F; Smith, Kelly E; Turner, Ryan C; Alkon, Daniel L; Tan, Zhenjun; Naser, Zachary J; Knotts, Chelsea M; Huber, Jason D; Rosen, Charles L

    2015-12-01

    Recent wars in Iraq and Afghanistan have accounted for an estimated 270,000 blast exposures among military personnel. Blast traumatic brain injury (TBI) is the 'signature injury' of modern warfare. Blood brain barrier (BBB) disruption following blast TBI can lead to long-term and diffuse neuroinflammation. In this study, we investigate for the first time the role of bryostatin-1, a specific protein kinase C (PKC) modulator, in ameliorating BBB breakdown. Thirty seven Sprague-Dawley rats were used for this study. We utilized a clinically relevant and validated blast model to expose animals to moderate blast exposure. Groups included: control, single blast exposure, and single blast exposure + bryostatin-1. Bryostatin-1 was administered i.p. 2.5 mg/kg after blast exposure. Evan's blue, immunohistochemistry, and western blot analysis were performed to assess injury. Evan's blue binds to albumin and is a marker for BBB disruption. The single blast exposure caused an increase in permeability compared to control (t = 4.808, p < 0.05), and a reduction back toward control levels when bryostatin-1 was administered (t = 5.113, p < 0.01). Three important PKC isozymes, PKCα, PKCδ, and PKCε, were co-localized primarily with endothelial cells but not astrocytes. Bryostatin-1 administration reduced toxic PKCα levels back toward control levels (t = 4.559, p < 0.01) and increased the neuroprotective isozyme PKCε (t = 6.102, p < 0.01). Bryostatin-1 caused a significant increase in the tight junction proteins VE-cadherin, ZO-1, and occludin through modulation of PKC activity. Bryostatin-1 ultimately decreased BBB breakdown potentially due to modulation of PKC isozymes. Future work will examine the role of bryostatin-1 in preventing chronic neurodegeneration following repetitive neurotrauma. PMID:25301233

  15. An Integrated Vehicle Modeling Environment

    NASA Technical Reports Server (NTRS)

    Totah, Joseph J.; Kinney, David J.; Kaneshige, John T.; Agabon, Shane

    1999-01-01

    This paper describes an Integrated Vehicle Modeling Environment for estimating aircraft geometric, inertial, and aerodynamic characteristics, and for interfacing with a high fidelity, workstation based flight simulation architecture. The goals in developing this environment are to aid in the design of next generation intelligent fight control technologies, conduct research in advanced vehicle interface concepts for autonomous and semi-autonomous applications, and provide a value-added capability to the conceptual design and aircraft synthesis process. Results are presented for three aircraft by comparing estimates generated by the Integrated Vehicle Modeling Environment with known characteristics of each vehicle under consideration. The three aircraft are a modified F-15 with moveable canards attached to the airframe, a mid-sized, twin-engine commercial transport concept, and a small, single-engine, uninhabited aerial vehicle. Estimated physical properties and dynamic characteristics are correlated with those known for each aircraft over a large portion of the flight envelope of interest. These results represent the completion of a critical step toward meeting the stated goals for developing this modeling environment.

  16. Brain functional integration decreases during propofol-induced loss of consciousness.

    PubMed

    Schrouff, Jessica; Perlbarg, Vincent; Boly, Mélanie; Marrelec, Guillaume; Boveroux, Pierre; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurélie; Laureys, Steven; Phillips, Christophe; Pélégrini-Issac, Mélanie; Maquet, Pierre; Benali, Habib

    2011-07-01

    Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol anesthesia is associated with a significant reduction in the capacity of the brain to integrate information. To assess the functional structure of the whole brain, functional integration and partial correlations were computed from fMRI data acquired from 18 healthy volunteers during resting wakefulness and propofol-induced deep sedation. Total integration was significantly reduced from wakefulness to deep sedation in the whole brain as well as within and between its constituent networks (or systems). Integration was systematically reduced within each system (i.e., brain or networks), as well as between networks. However, the ventral attentional network maintained interactions with most other networks during deep sedation. Partial correlations further suggested that functional connectivity was particularly affected between parietal areas and frontal or temporal regions during deep sedation. Our findings suggest that the breakdown in brain integration is the neural correlate of the loss of consciousness induced by propofol. They stress the important role played by parietal and frontal areas in the generation of consciousness. PMID:21524704

  17. Phenotypic integration of brain size and head morphology in Lake Tanganyika Cichlids

    PubMed Central

    2014-01-01

    Background Phenotypic integration among different anatomical parts of the head is a common phenomenon across vertebrates. Interestingly, despite centuries of research into the factors that contribute to the existing variation in brain size among vertebrates, little is known about the role of phenotypic integration in brain size diversification. Here we used geometric morphometrics on the morphologically diverse Tanganyikan cichlids to investigate phenotypic integration across key morphological aspects of the head. Then, while taking the effect of shared ancestry into account, we tested if head shape was associated with brain size while controlling for the potentially confounding effect of feeding strategy. Results The shapes of the anterior and posterior parts of the head were strongly correlated, indicating that the head represents an integrated morphological unit in Lake Tanganyika cichlids. After controlling for phylogenetic non-independence, we also found evolutionary associations between head shape, brain size and feeding ecology. Conclusions Geometric morphometrics and phylogenetic comparative analyses revealed that the anterior and posterior parts of the head are integrated, and that head morphology is associated with brain size and feeding ecology in Tanganyikan cichlid fishes. In light of previous results on mammals, our results suggest that the influence of phenotypic integration on brain diversification is a general process. PMID:24593160

  18. Integrated Resource Planning Model (IRPM)

    SciTech Connect

    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.

  19. Modeling the current distribution across the depth electrode-brain interface in deep brain stimulation.

    PubMed

    Yousif, Nada; Liu, Xuguang

    2007-09-01

    The mismatch between the extensive clinical use of deep brain stimulation (DBS), which is being used to treat an increasing number of neurological disorders, and the lack of understanding of the underlying mechanisms is confounded by the difficulty of measuring the spread of electric current in the brain in vivo. In this article we present a brief review of the recent computational models that simulate the electric current and field distribution in 3D space and, consequently, make estimations of the brain volume being modulated by therapeutic DBS. Such structural modeling work can be categorized into three main approaches: target-specific modeling, models of instrumentation and modeling the electrode-brain interface. Comments are made for each of these approaches with emphasis on our electrode-brain interface modeling, since the stimulating current must travel across the electrode-brain interface in order to reach the surrounding brain tissue and modulate the pathological neural activity. For future modeling work, a combined approach needs to be taken to reveal the underlying mechanisms, and both structural and dynamic models need to be clinically validated to make reliable predictions about the therapeutic effect of DBS in order to assist clinical practice. PMID:17850197

  20. Modeling Brain Resonance Phenomena Using a Neural Mass Model

    PubMed Central

    Spiegler, Andreas; Knösche, Thomas R.; Schwab, Karin; Haueisen, Jens; Atay, Fatihcan M.

    2011-01-01

    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. PMID:22215992

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

    PubMed

    Spiegler, Andreas; Knösche, Thomas R; Schwab, Karin; Haueisen, Jens; Atay, Fatihcan M

    2011-12-01

    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. PMID:22215992

  2. Adaptive Urban Dispersion Integrated Model

    SciTech Connect

    Wissink, A; Chand, K; Kosovic, B; Chan, S; Berger, M; Chow, F K

    2005-11-03

    Numerical simulations represent a unique predictive tool for understanding the three-dimensional flow fields and associated concentration distributions from contaminant releases in complex urban settings (Britter and Hanna 2003). Utilization of the most accurate urban models, based on fully three-dimensional computational fluid dynamics (CFD) that solve the Navier-Stokes equations with incorporated turbulence models, presents many challenges. We address two in this work; first, a fast but accurate way to incorporate the complex urban terrain, buildings, and other structures to enforce proper boundary conditions in the flow solution; second, ways to achieve a level of computational efficiency that allows the models to be run in an automated fashion such that they may be used for emergency response and event reconstruction applications. We have developed a new integrated urban dispersion modeling capability based on FEM3MP (Gresho and Chan 1998, Chan and Stevens 2000), a CFD model from Lawrence Livermore National Lab. The integrated capability incorporates fast embedded boundary mesh generation for geometrically complex problems and full three-dimensional Cartesian adaptive mesh refinement (AMR). Parallel AMR and embedded boundary gridding support are provided through the SAMRAI library (Wissink et al. 2001, Hornung and Kohn 2002). Embedded boundary mesh generation has been demonstrated to be an automatic, fast, and efficient approach for problem setup. It has been used for a variety of geometrically complex applications, including urban applications (Pullen et al. 2005). The key technology we introduce in this work is the application of AMR, which allows the application of high-resolution modeling to certain important features, such as individual buildings and high-resolution terrain (including important vegetative and land-use features). It also allows the urban scale model to be readily interfaced with coarser resolution meso or regional scale models. This talk

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

    PubMed

    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

  4. Volatile Anesthetics Influence Blood-Brain Barrier Integrity by Modulation of Tight Junction Protein Expression in Traumatic Brain Injury

    PubMed Central

    Schaible, Eva-Verena; Timaru-Kast, Ralph; Hedrich, Jana; Luhmann, Heiko J.; Engelhard, Kristin

    2012-01-01

    Disruption of the blood-brain barrier (BBB) results in cerebral edema formation, which is a major cause for high mortality after traumatic brain injury (TBI). As anesthetic care is mandatory in patients suffering from severe TBI it may be important to elucidate the effect of different anesthetics on cerebral edema formation. Tight junction proteins (TJ) such as zonula occludens-1 (ZO-1) and claudin-5 (cl5) play a central role for BBB stability. First, the influence of the volatile anesthetics sevoflurane and isoflurane on in-vitro BBB integrity was investigated by quantification of the electrical resistance (TEER) in murine brain endothelial monolayers and neurovascular co-cultures of the BBB. Secondly brain edema and TJ expression of ZO-1 and cl5 were measured in-vivo after exposure towards volatile anesthetics in native mice and after controlled cortical impact (CCI). In in-vitro endothelial monocultures, both anesthetics significantly reduced TEER within 24 hours after exposure. In BBB co-cultures mimicking the neurovascular unit (NVU) volatile anesthetics had no impact on TEER. In healthy mice, anesthesia did not influence brain water content and TJ expression, while 24 hours after CCI brain water content increased significantly stronger with isoflurane compared to sevoflurane. In line with the brain edema data, ZO-1 expression was significantly higher in sevoflurane compared to isoflurane exposed CCI animals. Immunohistochemical analyses revealed disruption of ZO-1 at the cerebrovascular level, while cl5 was less affected in the pericontusional area. The study demonstrates that anesthetics influence brain edema formation after experimental TBI. This effect may be attributed to modulation of BBB permeability by differential TJ protein expression. Therefore, selection of anesthetics may influence the barrier function and introduce a strong bias in experimental research on pathophysiology of BBB dysfunction. Future research is required to investigate adverse or

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

    SciTech Connect

    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.

  6. Integrating Genomes, Brain and Behavior in the Study of Songbirds

    PubMed Central

    Clayton, David F.; Balakrishnan, Christopher N.; London, Sarah E.

    2010-01-01

    Songbirds share some essential traits but are extraordinarily diverse, allowing comparative analyses aimed at identifying specific genotype–phenotype associations. This diversity encompasses traits like vocal communication and complex social behaviors that are of great interest to humans, but that are not well represented in other accessible research organisms. Many songbirds are readily observable in nature and thus afford unique insight into the links between environment and organism. The distinctive organization of the songbird brain will facilitate analysis of genomic links to brain and behavior. Access to the zebra finch genome sequence will, therefore, prompt new questions and provide the ability to answer those questions. PMID:19788884

  7. Mathematical modelling of blood-brain barrier failure and edema

    NASA Astrophysics Data System (ADS)

    Waters, Sarah; Lang, Georgina; Vella, Dominic; Goriely, Alain

    2015-11-01

    Injuries such as traumatic brain injury and stroke can result in increased blood-brain barrier permeability. This increase may lead to water accumulation in the brain tissue resulting in vasogenic edema. Although the initial injury may be localised, the resulting edema causes mechanical damage and compression of the vasculature beyond the original injury site. We employ a biphasic mixture model to investigate the consequences of blood-brain barrier permeability changes within a region of brain tissue and the onset of vasogenic edema. We find that such localised changes can indeed result in brain tissue swelling and that the type of damage that results (stress damage or strain damage) depends on the ability of the brain to clear edema fluid.

  8. S-values calculated from a tomographic head/brain model for brain imaging

    NASA Astrophysics Data System (ADS)

    Chao, Tsi-chian; Xu, X. George

    2004-11-01

    A tomographic head/brain model was developed from the Visible Human images and used to calculate S-values for brain imaging procedures. This model contains 15 segmented sub-regions including caudate nucleus, cerebellum, cerebral cortex, cerebral white matter, corpus callosum, eyes, lateral ventricles, lenses, lentiform nucleus, optic chiasma, optic nerve, pons and middle cerebellar peduncle, skull CSF, thalamus and thyroid. S-values for C-11, O-15, F-18, Tc-99m and I-123 have been calculated using this model and a Monte Carlo code, EGS4. Comparison of the calculated S-values with those calculated from the MIRD (1999) stylized head/brain model shows significant differences. In many cases, the stylized head/brain model resulted in smaller S-values (as much as 88%), suggesting that the doses to a specific patient similar to the Visible Man could have been underestimated using the existing clinical dosimetry.

  9. On a Mathematical Model of Brain Activities

    SciTech Connect

    Fichtner, K.-H.; Fichtner, L.; Freudenberg, W.; Ohya, M.

    2007-12-03

    The procedure of recognition can be described as follows: There is a set of complex signals stored in the memory. Choosing one of these signals may be interpreted as generating a hypothesis concerning an 'expexted view of the world'. Then the brain compares a signal arising from our senses with the signal chosen from the memory leading to a change of the state of both signals. Furthermore, measurements of that procedure like EEG or MEG are based on the fact that recognition of signals causes a certain loss of excited neurons, i.e. the neurons change their state from 'excited' to 'nonexcited'. For that reason a statistical model of the recognition process should reflect both--the change of the signals and the loss of excited neurons. A first attempt to explain the process of recognition in terms of quantum statistics was given. In the present note it is not possible to present this approach in detail. In lieu we will sketch roughly a few of the basic ideas and structures of the proposed model of the recognition process (Section). Further, we introduce the basic spaces and justify the choice of spaces used in this approach. A more elaborate presentation including all proofs will be given in a series of some forthcoming papers. In this series also the procedures of creation of signals from the memory, amplification, accumulation and transformation of input signals, and measurements like EEG and MEG will be treated in detail.

  10. Permeability of ergot alkaloids across the blood-brain barrier in vitro and influence on the barrier integrity

    PubMed Central

    Mulac, Dennis; Hüwel, Sabine; Galla, Hans-Joachim; Humpf, Hans-Ulrich

    2012-01-01

    Scope Ergot alkaloids are secondary metabolites of Claviceps spp. and they have been in the focus of research for many years. Experiments focusing on ergotamine as a former migraine drug referring to the ability to reach the brain revealed controversial results. The question to which extent ergot alkaloids are able to cross the blood-brain barrier is still not answered. Methods and results In order to answer this question we have studied the ability of ergot alkaloids to penetrate the blood-brain barrier in a well established in vitro model system using primary porcine brain endothelial cells. It could clearly be demonstrated that ergot alkaloids are able to cross the blood-brain barrier in high quantities in only a few hours. We could further identify an active transport for ergometrine as a substrate for the BCRP/ABCG2 transporter. Investigations concerning barrier integrity properties have identified ergocristinine as a potent substance to accumulate in these cells ultimately leading to a weakened barrier function. Conclusion For the first time we could show that the so far as biologically inactive described 8-(S) isomers of ergot alkaloids seem to have an influence on barrier integrity underlining the necessity for a risk assessment of ergot alkaloids in food and feed. PMID:22147614

  11. PLATO: data-oriented approach to collaborative large-scale brain system modeling.

    PubMed

    Kannon, Takayuki; Inagaki, Keiichiro; Kamiji, Nilton L; Makimura, Kouji; Usui, Shiro

    2011-11-01

    The brain is a complex information processing system, which can be divided into sub-systems, such as the sensory organs, functional areas in the cortex, and motor control systems. In this sense, most of the mathematical models developed in the field of neuroscience have mainly targeted a specific sub-system. In order to understand the details of the brain as a whole, such sub-system models need to be integrated toward the development of a neurophysiologically plausible large-scale system model. In the present work, we propose a model integration library where models can be connected by means of a common data format. Here, the common data format should be portable so that models written in any programming language, computer architecture, and operating system can be connected. Moreover, the library should be simple so that models can be adapted to use the common data format without requiring any detailed knowledge on its use. Using this library, we have successfully connected existing models reproducing certain features of the visual system, toward the development of a large-scale visual system model. This library will enable users to reuse and integrate existing and newly developed models toward the development and simulation of a large-scale brain system model. The resulting model can also be executed on high performance computers using Message Passing Interface (MPI). PMID:21767932

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

    ERIC Educational Resources Information Center

    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…

  13. Integration of Neuropsychology in Educational Planning Following Traumatic Brain Injury

    ERIC Educational Resources Information Center

    Stavinoha, Peter L.

    2005-01-01

    Traumatic brain injuries (TBIs) have the potential to significantly disrupt a student's cognitive, academic, social, emotional, behavioral, and physical functioning. It is important for educators to appreciate the array of difficulties students with TBI may experience in order to appropriately assess needs and create an educational plan that…

  14. TMT/VLOT integrated modeling

    NASA Astrophysics Data System (ADS)

    Dunn, Jennifer; Roberts, Scott C.; Kerley, Dan; Fitzsimmons, Joeleff T.; Pazder, John S.; Herriot, Glen; Smith, Malcolm J.

    2004-11-01

    The National Research Council's Herzberg Institute of Astrophysics (NRC-HIA) has developed an opto-mechanical integrated modeling toolset called TM-IM. This time-domain state-space toolset has been implemented using Matlab/Simulink/C. The toolset was originally developed for the Very Large Optical Telescope (VLOT) design work, and continued when Canada joined in the Thirty Meter Telescope (TMT) project. The TM-IM toolset has been developed to accommodate different structural and optical designs and has been used to evaluate telescope performance to assist in making decisions for the TMT reference design expected fall 2004. Preliminary results include delivered image quality as a function of wind loading on the structure, primary and secondary mirror, and the simulation of an Adaptive Optics system which provides control feedback to the primary mirror.

  15. An integrated model of learning.

    PubMed

    Trigg, A M; Cordova, F D

    1987-01-01

    Worldwide, most educational systems are based on three levels of education that utilize the pedagogical approaches to learning. In the 1960s, scholars formulated another approach to education that has become known as andragogy and has been applied to adult education. Several innovative scholars have seen how andragogy can be applied to teaching children. As a result, both andragogy and pedagogy are viewed as the opposite ends of the educational spectrum. Both of these approaches have a place and function within the modern educational framework. If one assumes that the goal of education is for the acquisition and application of knowledge, then both of these approaches can be used effectively for the attainment of that goal. In order to utilize these approaches effectively, an integrated model of learning has been developed that consists of initial teaching and exploratory learning phases. This model has both the directive and flexible qualities found in the theories of pedagogy and andragogy. With careful consideration and analysis this educational model can be utilized effectively within most educational systems. PMID:3588888

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

    PubMed

    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. PMID:26463967

  17. Whole-Brain Radiotherapy With Simultaneous Integrated Boost to Multiple Brain Metastases Using Volumetric Modulated Arc Therapy

    SciTech Connect

    Lagerwaard, Frank J. Hoorn, Elles A.P. van der; Verbakel, Wilko; Haasbeek, Cornelis J.A.; Slotman, Ben J.; Senan, Suresh

    2009-09-01

    Purpose: Volumetric modulated arc therapy (RapidArc [RA]; Varian Medical Systems, Palo Alto, CA) allows for the generation of intensity-modulated dose distributions by use of a single gantry rotation. We used RA to plan and deliver whole-brain radiotherapy (WBRT) with a simultaneous integrated boost in patients with multiple brain metastases. Methods and Materials: Composite RA plans were generated for 8 patients, consisting of WBRT (20 Gy in 5 fractions) with an integrated boost, also 20 Gy in 5 fractions, to Brain metastases, and clinically delivered in 3 patients. Summated gross tumor volumes were 1.0 to 37.5 cm{sup 3}. RA plans were measured in a solid water phantom by use of Gafchromic films (International Specialty Products, Wayne, NJ). Results: Composite RA plans could be generated within 1 hour. Two arcs were needed to deliver the mean of 1,600 monitor units with a mean 'beam-on' time of 180 seconds. RA plans showed excellent coverage of planning target volume for WBRT and planning target volume for the boost, with mean volumes receiving at least 95% of the prescribed dose of 100% and 99.8%, respectively. The mean conformity index was 1.36. Composite plans showed much steeper dose gradients outside Brain metastases than plans with a conventional summation of WBRT and radiosurgery. Comparison of calculated and measured doses showed a mean gamma for double-arc plans of 0.30, and the area with a gamma larger than 1 was 2%. In-room times for clinical RA sessions were approximately 20 minutes for each patient. Conclusions: RA treatment planning and delivery of integrated plans of WBRT and boosts to multiple brain metastases is a rapid and accurate technique that has a higher conformity index than conventional summation of WBRT and radiosurgery boost.

  18. The application of integrated knowledge-based systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

    NASA Technical Reports Server (NTRS)

    Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris

    1992-01-01

    One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through BRAIN, an integrated network of both human and computer elements. BRAIN will function as an advisor to mission managers by assessing the risk of inflight biomedical problems and recommending appropriate countermeasures. Described here is a joint effort among various NASA elements to develop BRAIN and the Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of knowledge acquisition, integration of IDRA components, the use of expert systems to automate the biomedical prediction process, development of a user friendly interface, and integration of IDRA and ExerCISys systems. Because C language, CLIPS and the X-Window System are portable and easily integrated, they were chosen ss the tools for the initial IDRA prototype.

  19. A revised dosimetric model of the adult head and brain

    SciTech Connect

    Bouchet, L.G.; Bolch, W.E.; Weber, D.A.

    1996-06-01

    During the last decade, new radiopharmaceutical have been introduced for brain imaging. The marked differences of these tracers in tissue specificity within the brain and their increasing use for diagnostic studies support the need for a more anthropomorphic model of the human brain and head. Brain and head models developed in the past have been only simplistic representations of this anatomic region. For example, the brain within the phantom of MIRD Pamphlet No. 5 Revised is modeled simply as a single ellipsoid of tissue With no differentiation of its internal structures. To address this need, the MIRD Committee established a Task Group in 1992 to construct a more detailed brain model to include the cerebral cortex, the white matter, the cerebellum, the thalamus, the caudate nucleus, the lentiform nucleus, the cerebral spinal fluid, the lateral ventricles, and the third ventricle. This brain model has been included within a slightly modified version of the head model developed by Poston et al. in 1984. This model has been incorporated into the radiation transport code EGS4 so as to calculate photon and electron absorbed fractions in the energy range 10 keV to 4 MeV for each of thirteen sources in the brain. Furthermore, explicit positron transport have been considered, separating the contribution by the positron itself and its associated annihilations photons. No differences are found between the electron and positron absorbed fractions; however, for initial energies of positrons greater than {approximately}0.5 MeV, significant differences are found between absorbed fractions from explicit transport of annihilation photons and those from an assumed uniform distribution of 0.511-MeV photons. Subsequently, S values were calculated for a variety of beta-particle and positron emitters brain imaging agents. Moreover, pediatric head and brain dosimetric models are currently being developed based on this adult head model.

  20. Action and language mechanisms in the brain: data, models and neuroinformatics.

    PubMed

    Arbib, Michael A; 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

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

    PubMed Central

    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

  2. Integrated Urban Dispersion Modeling Capability

    SciTech Connect

    Kosovic, B; Chan, S T

    2003-11-03

    Numerical simulations represent a unique predictive tool for developing a detailed understanding of three-dimensional flow fields and associated concentration distributions from releases in complex urban settings (Britter and Hanna 2003). The accurate and timely prediction of the atmospheric dispersion of hazardous materials in densely populated urban areas is a critical homeland and national security need for emergency preparedness, risk assessment, and vulnerability studies. The main challenges in high-fidelity numerical modeling of urban dispersion are the accurate prediction of peak concentrations, spatial extent and temporal evolution of harmful levels of hazardous materials, and the incorporation of detailed structural geometries. Current computational tools do not include all the necessary elements to accurately represent hazardous release events in complex urban settings embedded in high-resolution terrain. Nor do they possess the computational efficiency required for many emergency response and event reconstruction applications. We are developing a new integrated urban dispersion modeling capability, able to efficiently predict dispersion in diverse urban environments for a wide range of atmospheric conditions, temporal and spatial scales, and release event scenarios. This new computational fluid dynamics capability includes adaptive mesh refinement and it can simultaneously resolve individual buildings and high-resolution terrain (including important vegetative and land-use features), treat complex building and structural geometries (e.g., stadiums, arenas, subways, airplane interiors), and cope with the full range of atmospheric conditions (e.g. stability). We are developing approaches for seamless coupling with mesoscale numerical weather prediction models to provide realistic forcing of the urban-scale model, which is critical to its performance in real-world conditions.

  3. INTEGRATED HYDROGEN STORAGE SYSTEM MODEL

    SciTech Connect

    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

  4. Modeling brain circuitry over a wide range of scales

    PubMed Central

    Fua, Pascal; Knott, Graham W.

    2015-01-01

    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. PMID:25904852

  5. Integrable open boundary conditions for XXC models

    NASA Astrophysics Data System (ADS)

    Arnaudon, Daniel; Maassarani, Ziad

    1998-10-01

    The XXC models are multistate generalizations of the well known spin-½ XXZ model. These integrable models share a common underlying su(2) structure. We derive integrable open boundary conditions for the hierarchy of conserved quantities of the XXC models . Due to lack of crossing unitarity of the R-matrix, we develop specific methods to prove integrability. The symmetry of the spectrum is determined.

  6. Brain

    MedlinePlus

    ... will return after updating. Resources Archived Modules Updates Brain Cerebrum The cerebrum is the part of the ... the outside of the brain and spinal cord. Brain Stem The brain stem is the part of ...

  7. Ontogenetic ritualization of primate gesture as a case study in dyadic brain modeling.

    PubMed

    Gasser, Brad; Cartmill, Erica A; Arbib, Michael A

    2014-01-01

    This paper introduces dyadic brain modeling - the simultaneous, computational modeling of the brains of two interacting agents - to explore ways in which our understanding of macaque brain circuitry can ground new models of brain mechanisms involved in ape interaction. Specifically, we assess a range of data on gestural communication of great apes as the basis for developing an account of the interactions of two primates engaged in ontogenetic ritualization, a proposed learning mechanism through which a functional action may become a communicative gesture over repeated interactions between two individuals (the 'dyad'). The integration of behavioral, neural, and computational data in dyadic (or, more generally, social) brain modeling has broad application to comparative and evolutionary questions, particularly for the evolutionary origins of cognition and language in the human lineage. We relate this work to the neuroinformatics challenges of integrating and sharing data to support collaboration between primatologists, neuroscientists and modelers that will help speed the emergence of what may be called comparative neuro-primatology. PMID:23608958

  8. Integrated modeling, data transfers, and physical models

    NASA Astrophysics Data System (ADS)

    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

  9. Progress on the paternal brain: theory, animal models, human brain research, and mental health implications.

    PubMed

    Swain, J E; Dayton, C J; Kim, P; Tolman, R M; Volling, B L

    2014-01-01

    With a secure foundation in basic research across mammalian species in which fathers participate in the raising of young, novel brain-imaging approaches are outlining a set of consistent brain circuits that regulate paternal thoughts and behaviors in humans. The newest experimental paradigms include increasingly realistic baby-stimuli to provoke paternal cognitions and behaviors with coordinated hormone measures to outline brain networks that regulate motivation, reflexive caring, emotion regulation, and social brain networks with differences and similarities to those found in mothers. In this article, on the father brain, we review all brain-imaging studies on PubMed to date on the human father brain and introduce the topic with a selection of theoretical models and foundational neurohormonal research on animal models in support of the human work. We discuss potentially translatable models for the identification and treatment of paternal mood and father-child relational problems, which could improve infant mental health and developmental trajectories with potentially broad public health importance. PMID:25798491

  10. The History and Evolution of Experimental Traumatic Brain Injury Models.

    PubMed

    Povlishock, John

    2016-01-01

    This narrative provides a brief history of experimental animal model development for the study of traumatic brain injury. It draws upon a relatively rich history of early animal modeling that employed higher order animals to assess concussive brain injury while exploring the importance of head movement versus stabilization in evaluating the animal's response to injury. These themes are extended to the development of angular/rotational acceleration/deceleration models that also exploited brain movement to generate both the morbidity and pathology typically associated with human traumatic brain injury. Despite the significance of these early model systems, their limitations and overall practicality are discussed. Consideration is given to more contemporary rodent animal models that replicate individual/specific features of human injury, while via various transgenic technologies permitting the evaluation of injury-mediated pathways. The narrative closes on a reconsideration of higher order, porcine animal models of injury and their implication for preclinical/translational research. PMID:27604709

  11. Evaluation of Autophagy Using Mouse Models of Brain Injury

    PubMed Central

    Au, Alicia K.; Bayir, Hülya; Kochanek, Patrick M.; Clark, Robert S. B.

    2009-01-01

    SUMMARY Autophagy is a homeostatic, carefully regulated, and dynamic process for intracellular recycling of bulk proteins, aging organelles, and lipids. Autophagy occurs in all tissues and cell types, including the brain and neurons. Alteration in the dynamics of autophagy has been observed in many diseases of the central nervous system. Disruption of autophagy for an extended period of time results in accumulation of unwanted proteins and neurodegeneration. However, the role of enhanced autophagy after acute brain injury remains undefined. Established mouse models of brain injury will be valuable in clarifying the role of autophagy after brain injury, and are the topic of discussion in this review. PMID:19879944

  12. Bayesian approach for network modeling of brain structural features

    NASA Astrophysics Data System (ADS)

    Joshi, Anand A.; Joshi, Shantanu H.; Leahy, Richard M.; Shattuck, David W.; Dinov, Ivo; Toga, Arthur W.

    2010-03-01

    Brain connectivity patterns are useful in understanding brain function and organization. Anatomical brain connectivity is largely determined using the physical synaptic connections between neurons. In contrast statistical brain connectivity in a given brain population refers to the interaction and interdependencies of statistics of multitudes of brain features including cortical area, volume, thickness etc. Traditionally, this dependence has been studied by statistical correlations of cortical features. In this paper, we propose the use of Bayesian network modeling for inferring statistical brain connectivity patterns that relate to causal (directed) as well as non-causal (undirected) relationships between cortical surface areas. We argue that for multivariate cortical data, the Bayesian model provides for a more accurate representation by removing the effect of confounding correlations that get introduced due to canonical dependence between the data. Results are presented for a population of 466 brains, where a SEM (structural equation modeling) approach is used to generate a Bayesian network model, as well as a dependency graph for the joint distribution of cortical areas.

  13. Multi-scale integration and predictability in resting state brain activity

    PubMed Central

    Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

    2014-01-01

    The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

  14. Canine spontaneous brain tumors: A large animal model for BNCT

    SciTech Connect

    Gavin, P.R.; Kraft, S.L.; Wendling, L.R.; Miller, D.L.

    1988-01-01

    Brain tumors occur spontaneously on dogs with an incidence similar to that in humans. Brain tumors of dogs have histologic, radiologic, and other diagnostic similarities to human brain tumors. Tumor kinetics and biologic behavior of these tumors in dogs are also similar to that in man. Recent studies indicate that conventional radiation therapy of brain tumors of dogs result in a survival interval appropriate to study the late radiation reactions in the surrounding normal brain and other tissues within the irradiated field. The relatively large size of the dog allows identical diagnostic and therapeutic modalities and methodology. The dog's head size enables the complex dosimetric variables to be relevant to that found in human radiation therapy. For these reasons, spontaneous brain tumors in the dog are an excellent model to study neuon capture theory (NCT). 7 refs., 1 fig., 3 tabs.

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

    PubMed

    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. PMID:23319423

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

    PubMed

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

    2012-10-01

    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. PMID:22575713

  17. Zebrafish as an emerging model for studying complex brain disorders

    PubMed Central

    Kalueff, Allan V.; Stewart, Adam Michael; Gerlai, Robert

    2014-01-01

    The zebrafish (Danio rerio) is rapidly becoming a popular model organism in pharmacogenetics and neuropharmacology. Both larval and adult zebrafish are currently used to increase our understanding of brain function, dysfunction, and their genetic and pharmacological modulation. Here we review the developing utility of zebrafish in the analysis of complex brain disorders (including, for example, depression, autism, psychoses, drug abuse and cognitive disorders), also covering zebrafish applications towards the goal of modeling major human neuropsychiatric and drug-induced syndromes. We argue that zebrafish models of complex brain disorders and drug-induced conditions have become a rapidly emerging critical field in translational neuropharmacology research. PMID:24412421

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

    PubMed

    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. PMID:27062510

  19. Human action recognition using integrated model

    NASA Astrophysics Data System (ADS)

    Yi, Yang; Lin, Yikun

    2013-07-01

    A novel action recognition framework based on integrated model is proposed in the paper. First, the covariance descriptor is utilized to extract features from video sequences, and then each class specific codebook is constructed and appended to the global codebook. A static model applying the template matching technique and a dynamic model employing the trigram model are learned to capture complementary information in an action. And lastly, an integrated model is used to estimate the confidence of the static and dynamic models and produces a reliable result. Comparative experiments show that our presented method achieves superior results over other state-of-the-art approaches. Keywords: human action recognition, covariance descriptor, integrated model

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

    NASA Astrophysics Data System (ADS)

    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 <= a <= 2.0 mm and length c: 3.0 <= c <= 6.0 mm) with 5-65 μm thick reflective layers on its five sides and sixth side optically coupled to the matching array of dGAPDs and processing electronics with total thickness of 50 μm. Simulated energy resolution was 10.8% and 3.3% for LSO and LaBr3 respectively and the coincidence window was set at 2 ns. The brain was simulated as a sphere of uniform F-18 activity with diameter of 10 cm embedded in a center of water sphere with diameter of 10 cm. Results: Analytical and Monte Carlo models showed similar results for lower energy window values (458 keV versus 445 keV for LSO, and 492 keV versus 485 keV for LaBr3

  1. An Integrated Bayesian Model for DIF Analysis

    ERIC Educational Resources Information Center

    Soares, Tufi M.; Goncalves, Flavio B.; Gamerman, Dani

    2009-01-01

    In this article, an integrated Bayesian model for differential item functioning (DIF) analysis is proposed. The model is integrated in the sense of modeling the responses along with the DIF analysis. This approach allows DIF detection and explanation in a simultaneous setup. Previous empirical studies and/or subjective beliefs about the item…

  2. Dynamic Integrated Climate Economy model (DICE)

    EPA Science Inventory

    The DICE model is an Integrated Assessment model of climate change impacts and costs, which “integrate[s] in an end-to-end fashion the economics, carbon cycle, climate science, and impacts in a highly aggregated model that allow[s] a weighing of the costs and benefits of taking s...

  3. Modeling the brain morphology distribution in the general aging population

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

    Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.

  4. An integrated model-based neurosurgical guidance system

    NASA Astrophysics Data System (ADS)

    Ji, Songbai; Fan, Xiaoyao; Fontaine, Kathryn; Hartov, Alex; Roberts, David; Paulsen, Keith

    2010-02-01

    Maximal tumor resection without damaging healthy tissue in open cranial surgeries is critical to the prognosis for patients with brain cancers. Preoperative images (e.g., preoperative magnetic resonance images (pMR)) are typically used for surgical planning as well as for intraoperative image-guidance. However, brain shift even at the start of surgery significantly compromises the accuracy of neuronavigation, if the deformation is not compensated for. Compensating for brain shift during surgical operation is, therefore, critical for improving the accuracy of image-guidance and ultimately, the accuracy of surgery. To this end, we have developed an integrated neurosurgical guidance system that incorporates intraoperative three-dimensional (3D) tracking, acquisition of volumetric true 3D ultrasound (iUS), stereovision (iSV) and computational modeling to efficiently generate model-updated MR image volumes for neurosurgical guidance. The system is implemented with real-time Labview to provide high efficiency in data acquisition as well as with Matlab to offer computational convenience in data processing and development of graphical user interfaces related to computational modeling. In a typical patient case, the patient in the operating room (OR) is first registered to pMR image volume. Sparse displacement data extracted from coregistered intraoperative US and/or stereovision images are employed to guide a computational model that is based on consolidation theory. Computed whole-brain deformation is then used to generate a model-updated MR image volume for subsequent surgical guidance. In this paper, we present the key modular components of our integrated, model-based neurosurgical guidance system.

  5. Brain microabscesses in a porcine model of Staphylococcus aureus sepsis

    PubMed Central

    2013-01-01

    Background Sepsis caused by Staphylococcus aureus often leads to brain microabscesses in humans. Animal models of haematogenous brain abscesses would be useful to study this condition in detail. Recently, we developed a model of S. aureus sepsis in pigs and here we report that brain microabscesses develop in pigs with such induced S. aureus sepsis. Twelve pigs were divided into three groups. Nine pigs received an intravenous inoculation of S. aureus once at time 0 h (group 1) or twice at time 0 h and 12 h (groups 2 and 3). In each group the fourth pig served as control. The pigs were euthanized at time 12 h (Group 1), 24 h (Group 2) and 48 h (Group 3) after the first inoculation. The brains were collected and examined histopathologically. Results All inoculated pigs developed sepsis and seven out of nine pigs developed brain microabscesses. The microabscesses contained S. aureus and were located in the prosencephalon and mesencephalon. Chorioditis and meningitis occurred from 12 h after inoculation. Conclusions Pigs with experimental S. aureus sepsis often develop brain microabscesses. The porcine brain pathology mirrors the findings in human sepsis patients. We therefore suggest the pig as a useful animal model of the development of brain microabscesses caused by S. aureus sepsis. PMID:24176029

  6. Controlling ferrofluid permeability across the blood-brain barrier model

    NASA Astrophysics Data System (ADS)

    Shi, Di; Sun, Linlin; Mi, Gujie; Sheikh, Lubna; Bhattacharya, Soumya; Nayar, Suprabha; Webster, Thomas J.

    2014-02-01

    In the present study, an in vitro blood-brain barrier model was developed using murine brain endothelioma cells (b.End3 cells). Confirmation of the blood-brain barrier model was completed by examining the permeability of FITC-Dextran at increasing exposure times up to 96 h in serum-free medium and comparing such values with values from the literature. After such confirmation, the permeability of five novel ferrofluid (FF) nanoparticle samples, GGB (ferrofluids synthesized using glycine, glutamic acid and BSA), GGC (glycine, glutamic acid and collagen), GGP (glycine, glutamic acid and PVA), BPC (BSA, PEG and collagen) and CPB (collagen, PVA and BSA), was determined using this blood-brain barrier model. All of the five FF samples were characterized by zeta potential to determine their charge as well as TEM and dynamic light scattering for determining their hydrodynamic diameter. Results showed that FF coated with collagen passed more easily through the blood-brain barrier than FF coated with glycine and glutamic acid based on an increase of 4.5% in permeability. Through such experiments, diverse magnetic nanomaterials (such as FF) were identified for: (1) MRI use since they were less permeable to penetrate the blood-brain barrier to avoid neural tissue toxicity (e.g. GGB) or (2) brain drug delivery since they were more permeable to the blood-brain barrier (e.g. CPB).

  7. Controlling ferrofluid permeability across the blood–brain barrier model.

    PubMed

    Shi, Di; Sun, Linlin; Mi, Gujie; Sheikh, Lubna; Bhattacharya, Soumya; Nayar, Suprabha; Webster, Thomas J

    2014-02-21

    In the present study, an in vitro blood–brain barrier model was developed using murine brain endothelioma cells (b.End3 cells). Confirmation of the blood–brain barrier model was completed by examining the permeability of FITCDextran at increasing exposure times up to 96 h in serum-free medium and comparing such values with values from the literature. After such confirmation, the permeability of five novel ferrofluid (FF) nanoparticle samples, GGB (ferrofluids synthesized using glycine, glutamic acid and BSA), GGC (glycine, glutamic acid and collagen), GGP (glycine, glutamic acid and PVA), BPC (BSA, PEG and collagen) and CPB (collagen, PVA and BSA), was determined using this blood–brain barrier model. All of the five FF samples were characterized by zeta potential to determine their charge as well as TEM and dynamic light scattering for determining their hydrodynamic diameter. Results showed that FF coated with collagen passed more easily through the blood–brain barrier than FF coated with glycine and glutamic acid based on an increase of 4.5% in permeability. Through such experiments, diverse magnetic nanomaterials (such as FF) were identified for: (1) MRI use since they were less permeable to penetrate the blood–brain barrier to avoid neural tissue toxicity (e.g. GGB) or (2) brain drug delivery since they were more permeable to the blood–brain barrier (e.g. CPB). PMID:24457539

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Integrated Brain Circuits: Astrocytic Networks Modulate Neuronal Activity and Behavior

    PubMed Central

    Halassa, Michael M.; Haydon, Philip G.

    2011-01-01

    The past decade has seen an explosion of research on roles of neuron-astrocyte interactions in the control of brain function. We highlight recent studies performed on the tripartite synapse, the structure consisting of pre- and postsynaptic elements of the synapse and an associated astrocytic process. Astrocytes respond to neuronal activity and neuro-transmitters, through the activation of metabotropic receptors, and can release the gliotransmitters ATP, D-serine, and glutamate, which act on neurons. Astrocyte-derived ATP modulates synaptic transmission, either directly or through its metabolic product adenosine. D-serine modulates NMDA receptor function, whereas glia-derived glutamate can play important roles in relapse following withdrawal from drugs of abuse. Cell type–specific molecular genetics has allowed a new level of examination of the function of astrocytes in brain function and has revealed an important role of these glial cells that is mediated by adenosine accumulation in the control of sleep and in cognitive impairments that follow sleep deprivation. PMID:20148679

  10. Brain Penetration and Efficacy of Different Mebendazole Polymorphs in a Mouse Brain Tumor Model

    PubMed Central

    Wanjiku, Teresia; Rudek, Michelle A; Joshi, Avadhut; Gallia, Gary L.; Riggins, Gregory J.

    2015-01-01

    Purpose Mebendazole (MBZ), first used as an antiparasitic drug, shows preclinical efficacy in models of glioblastoma and medulloblastoma. Three different MBZ polymorphs (A, B and C) exist and a detailed assessment of the brain penetration, pharmacokinetics and anti-tumor properties of each individual MBZ polymorph is necessary to improve mebendazole-based brain cancer therapy. Experimental Design and Results In this study, various marketed and custom-formulated MBZ tablets were analyzed for their polymorph content by IR spectroscopy and subsequently tested in orthotopic GL261 mouse glioma model for efficacy and tolerability. The pharmacokinetics and brain concentration of MBZ polymorphs and two main metabolites were analyzed by LC-MS. We found that polymorph B and C both increased survival in a GL261 glioma model, as B exhibited greater toxicity. Polymorph A showed no benefit. Both, polymorph B and C, reached concentrations in the brain that exceeded the IC50 in GL261 cells 29-fold. In addition, polymorph C demonstrated an AUC0-24h brain-to-plasma (B/P) ratio of 0.82, whereas B showed higher plasma AUC and lower B/P ratio. In contrast, polymorph A presented markedly lower levels in the plasma and brain. Furthermore, the combination with elacridar was able to significantly improve the efficacy of polymorph C in GL261 glioma and D425 medulloblastoma models in mice. Conclusion Among MBZ polymorphs, C reaches therapeutically effective concentrations in the brain tissue and tumor with less side effects and is the better choice for brain cancer therapy. Its efficacy can be further enhanced by combination with elacridar. PMID:25862759

  11. Erythropoietin as a Neuroprotectant for Neonatal Brain Injury: Animal Models

    PubMed Central

    Traudt, Christopher M.; Juul, Sandra E.

    2016-01-01

    Prematurity and perinatal hypoxia-ischemia are common problems that result in significant neurodevelopmental morbidity and high mortality worldwide. The Vannucci model of unilateral brain injury was developed to model perinatal brain injury due to hypoxia-ischemia. Because the rodent brain is altricial, i.e., it develops postnatally, investigators can model either preterm or term brain injury by varying the age at which injury is induced. This model has allowed investigators to better understand developmental changes that occur in susceptibility of the brain to injury, evolution of brain injury over time, and response to potential neuroprotective treatments. The Vannucci model combines unilateral common carotid artery ligation with a hypoxic insult. This produces injury of the cerebral cortex, basal ganglia, hippocampus, and periventricular white matter ipsilateral to the ligated artery. Varying degrees of injury can be obtained by varying the depth and duration of the hypoxic insult. This chapter details one approach to the Vannucci model and also reviews the neuroprotective effects of erythropoietin (Epo), a neuroprotective treatment that has been extensively investigated using this model and others. PMID:23456865

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

    PubMed Central

    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

  13. Mesenchymal Stem Cells Regulate Blood Brain Barrier Integrity in Traumatic Brain Injury Through Production of the Soluble Factor TIMP3

    PubMed Central

    Menge, Tyler; Zhao, Yuhai; Zhao, Jing; Wataha, Kathryn; Geber, Michael; Zhang, Jianhu; Letourneau, Phillip; Redell, John; Shen, Li; Wang, Jing; Peng, Zhalong; Xue, Hasen; Kozar, Rosemary; Cox, Charles S.; Khakoo, Aarif Y.; Holcomb, John B.; Dash, Pramod K.; Pati, Shibani

    2013-01-01

    Mesenchymal stem cells (MCSs) have been shown to have therapeutic potential in multiple disease states associated with vascular instability including traumatic brain injury (TBI). In the present study, Tissue Inhibitor of Matrix Metalloproteinase-3 (TIMP3) is identified as the soluble factor produced by MSCs that can recapitulate the beneficial effects of MSCs on endothelial function and blood brain barrier (BBB) compromise in TBI. Attenuation of TIMP3 expression in MSCs completely abrogates the effect of MSCs on BBB permeability and stability, while intravenous administration of rTIMP3 alone can inhibit BBB permeability in TBI. Our results demonstrate that MSCs increase circulating levels of soluble TIMP3, which inhibits VEGF-A induced breakdown of endothelial AJs in vitro and in vivo. These findings elucidate a clear molecular mechanism for the effects of MSCs on the BBB in TBI, and directly demonstrate a role for TIMP3 in regulation of BBB integrity. PMID:23175708

  14. Concordance: A Framework for Managing Model Integrity

    NASA Astrophysics Data System (ADS)

    Rose, Louis M.; Kolovos, Dimitrios S.; Drivalos, Nicholas; Williams, James R.; Paige, Richard F.; Polack, Fiona A. C.; Fernandes, Kiran J.

    A change to a software development artefact, such as source code or documentation, can affect the integrity of others. Many contemporary software development environments provide tools that automatically manage (detect, report and reconcile) integrity. For instance, incremental background compilation can reconcile object code with changing source code and report calls to a method that are inconsistent with its definition. Although models are increasingly first-class citizens in software development, contemporary development environments are less able to automatically detect, manage and reconcile the integrity of models than the integrity of other types of artefact. In this paper, we discuss the scalability and efficiency problems faced when managing model integrity for two categories of change that occur in MDE. We present a framework to support the incremental management of model integrity, evaluating the efficiency of the proposed approach atop Eclipse and EMF.

  15. Brain tumor modeling: glioma growth and interaction with chemotherapy

    NASA Astrophysics Data System (ADS)

    Banaem, Hossein Y.; Ahmadian, Alireza; Saberi, Hooshangh; Daneshmehr, Alireza; Khodadad, Davood

    2011-10-01

    In last decade increasingly mathematical models of tumor growths have been studied, particularly on solid tumors which growth mainly caused by cellular proliferation. In this paper we propose a modified model to simulate the growth of gliomas in different stages. Glioma growth is modeled by a reaction-advection-diffusion. We begin with a model of untreated gliomas and continue with models of polyclonal glioma following chemotherapy. From relatively simple assumptions involving homogeneous brain tissue bounded by a few gross anatomical landmarks (ventricles and skull) the models have been expanded to include heterogeneous brain tissue with different motilities of glioma cells in grey and white matter. Tumor growth is characterized by a dangerous change in the control mechanisms, which normally maintain a balance between the rate of proliferation and the rate of apoptosis (controlled cell death). Result shows that this model closes to clinical finding and can simulate brain tumor behavior properly.

  16. A novel model for brain iron uptake: introducing the concept of regulation

    PubMed Central

    Simpson, Ian A; Ponnuru, Padmavathi; Klinger, Marianne E; Myers, Roland L; Devraj, Kavi; Coe, Christopher L; Lubach, Gabriele R; Carruthers, Anthony; Connor, James R

    2015-01-01

    Neurologic disorders such as Alzheimer's, Parkinson's disease, and Restless Legs Syndrome involve a loss of brain iron homeostasis. Moreover, iron deficiency is the most prevalent nutritional concern worldwide with many associated cognitive and neural ramifications. Therefore, understanding the mechanisms by which iron enters the brain and how those processes are regulated addresses significant global health issues. The existing paradigm assumes that the endothelial cells (ECs) forming the blood–brain barrier (BBB) serve as a simple conduit for transport of transferrin-bound iron. This concept is a significant oversimplification, at minimum failing to account for the iron needs of the ECs. Using an in vivo model of brain iron deficiency, the Belgrade rat, we show the distribution of transferrin receptors in brain microvasculature is altered in luminal, intracellular, and abluminal membranes dependent on brain iron status. We used a cell culture model of the BBB to show the presence of factors that influence iron release in non-human primate cerebrospinal fluid and conditioned media from astrocytes; specifically apo-transferrin and hepcidin were found to increase and decrease iron release, respectively. These data have been integrated into an interactive model where BBB ECs are central in the regulation of cerebral iron metabolism. PMID:25315861

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

    PubMed

    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. PMID:25314715

  18. Finite element modeling of human brain response to football helmet impacts.

    PubMed

    Darling, T; Muthuswamy, J; Rajan, S D

    2016-10-01

    The football helmet is used to help mitigate the occurrence of impact-related traumatic (TBI) and minor traumatic brain injuries (mTBI) in the game of American football. While the current helmet design methodology may be adequate for reducing linear acceleration of the head and minimizing TBI, it however has had less effect in minimizing mTBI. The objectives of this study are (a) to develop and validate a coupled finite element (FE) model of a football helmet and the human body, and (b) to assess responses of different regions of the brain to two different impact conditions - frontal oblique and crown impact conditions. The FE helmet model was validated using experimental results of drop tests. Subsequently, the integrated helmet-human body FE model was used to assess the responses of different regions of the brain to impact loads. Strain-rate, strain, and stress measures in the corpus callosum, midbrain, and brain stem were assessed. Results show that maximum strain-rates of 27 and 19 s(-1) are observed in the brain-stem and mid-brain, respectively. This could potentially lead to axonal injuries and neuronal cell death during crown impact conditions. The developed experimental-numerical framework can be used in the study of other helmet-related impact conditions. PMID:26867124

  19. GABA regulates synaptic integration of newly generated neurons in the adult brain

    NASA Astrophysics Data System (ADS)

    Ge, Shaoyu; Goh, Eyleen L. K.; Sailor, Kurt A.; Kitabatake, Yasuji; Ming, Guo-Li; Song, Hongjun

    2006-02-01

    Adult neurogenesis, the birth and integration of new neurons from adult neural stem cells, is a striking form of structural plasticity and highlights the regenerative capacity of the adult mammalian brain. Accumulating evidence suggests that neuronal activity regulates adult neurogenesis and that new neurons contribute to specific brain functions. The mechanism that regulates the integration of newly generated neurons into the pre-existing functional circuitry in the adult brain is unknown. Here we show that newborn granule cells in the dentate gyrus of the adult hippocampus are tonically activated by ambient GABA (γ-aminobutyric acid) before being sequentially innervated by GABA- and glutamate-mediated synaptic inputs. GABA, the major inhibitory neurotransmitter in the adult brain, initially exerts an excitatory action on newborn neurons owing to their high cytoplasmic chloride ion content. Conversion of GABA-induced depolarization (excitation) into hyperpolarization (inhibition) in newborn neurons leads to marked defects in their synapse formation and dendritic development in vivo. Our study identifies an essential role for GABA in the synaptic integration of newly generated neurons in the adult brain, and suggests an unexpected mechanism for activity-dependent regulation of adult neurogenesis, in which newborn neurons may sense neuronal network activity through tonic and phasic GABA activation.

  20. Fuzzy object models for newborn brain MR image segmentation

    NASA Astrophysics Data System (ADS)

    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.

  1. A Bayesian model of category-specific emotional brain responses.

    PubMed

    Wager, Tor D; Kang, Jian; Johnson, Timothy D; Nichols, Thomas E; Satpute, Ajay B; Barrett, Lisa Feldman

    2015-04-01

    Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories--fear, anger, disgust, sadness, or happiness--is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches. PMID:25853490

  2. A Bayesian Model of Category-Specific Emotional Brain Responses

    PubMed Central

    Wager, Tor D.; Kang, Jian; Johnson, Timothy D.; Nichols, Thomas E.; Satpute, Ajay B.; Barrett, Lisa Feldman

    2015-01-01

    Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories—fear, anger, disgust, sadness, or happiness—is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches. PMID:25853490

  3. Integrating Functional Neuroimaging and Human Operant Research: Brain Activation Correlated with Presentation of Discriminative Stimuli

    ERIC Educational Resources Information Center

    Schlund, Michael W.; Cataldo, Michael F.

    2005-01-01

    Results of numerous human imaging studies and nonhuman neurophysiological studies on "reward" highlight a role for frontal, striatal, and thalamic regions in operant learning. By integrating operant and functional neuroimaging methodologies, the present investigation examined brain activation to two types of discriminative stimuli correlated with…

  4. A planning study of simultaneous integrated boost with forward IMRT for multiple brain metastases

    SciTech Connect

    Liang, Xiaodong; Ni, Lingqin; Hu, Wei; Chen, Weijun; Ying, Shenpeng; Gong, Qiangjun; Liu, Yanmei

    2013-07-01

    The objective of this study was to evaluate the dose conformity and feasibility of whole-brain radiotherapy with a simultaneous integrated boost by forward intensity-modulated radiation therapy in patients with 1 to 3 brain metastases. Forward intensity-modulated radiation therapy plans were generated for 10 patients with 1 to 3 brain metastases on Pinnacle 6.2 Treatment Planning System. The prescribed dose was 30 Gy to the whole brain (planning target volume [PTV]{sub wbrt}) and 40 Gy to individual brain metastases (PTV{sub boost}) simultaneously, and both doses were given in 10 fractions. The maximum diameters of individual brain metastases ranged from 1.6 to 6 cm, and the summated PTVs per patient ranged from 1.62 to 69.81 cm{sup 3}. Conformity and feasibility were evaluated regarding conformation number and treatment delivery time. One hundred percent volume of the PTV{sub boost} received at least 95% of the prescribed dose in all cases. The maximum doses were less than 110% of the prescribed dose to the PTV{sub boost}, and all of the hot spots were within the PTV{sub boost}. The volume of the PTV{sub wbrt} that received at least 95% of the prescribed dose ranged from 99.2% to 100%. The mean values of conformation number were 0.682. The mean treatment delivery time was 2.79 minutes. Ten beams were used on an average in these plans. Whole-brain radiotherapy with a simultaneous integrated boost by forward intensity-modulated radiation therapy in 1 to 3 brain metastases is feasible, and treatment delivery time is short.

  5. INTEGRATED FISCHER TROPSCH MODULAR PROCESS MODEL

    SciTech Connect

    Donna Post Guillen; Richard Boardman; Anastasia M. Gribik; Rick A. Wood; Robert A. Carrington

    2007-12-01

    With declining petroleum reserves, increased world demand, and unstable politics in some of the world’s richest oil producing regions, the capability for the U.S. to produce synthetic liquid fuels from domestic resources is critical to national security and economic stability. Coal, biomass and other carbonaceous materials can be converted to liquid fuels using several conversion processes. The leading candidate for large-scale conversion of coal to liquid fuels is the Fischer Tropsch (FT) process. Process configuration, component selection, and performance are interrelated and dependent on feed characteristics. This paper outlines a flexible modular approach to model an integrated FT process that utilizes a library of key component models, supporting kinetic data and materials and transport properties allowing rapid development of custom integrated plant models. The modular construction will permit rapid assessment of alternative designs and feed stocks. The modeling approach consists of three thrust areas, or “strands” – model/module development, integration of the model elements into an end to end integrated system model, and utilization of the model for plant design. Strand 1, model/module development, entails identifying, developing, and assembling a library of codes, user blocks, and data for FT process unit operations for a custom feedstock and plant description. Strand 2, integration development, provides the framework for linking these component and subsystem models to form an integrated FT plant simulation. Strand 3, plant design, includes testing and validation of the comprehensive model and performing design evaluation analyses.

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

    ERIC Educational Resources Information Center

    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. Image guided constitutive modeling of the silicone brain phantom

    NASA Astrophysics Data System (ADS)

    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.

  8. Adolescent Emotional Maturation through Divergent Models of Brain Organization.

    PubMed

    Oron Semper, Jose V; Murillo, Jose I; Bernacer, Javier

    2016-01-01

    In this article we introduce the hypothesis that neuropsychological adolescent maturation, and in particular emotional management, may have opposing explanations depending on the interpretation of the assumed brain architecture, that is, whether a componential computational account (CCA) or a dynamic systems perspective (DSP) is used. According to CCA, cognitive functions are associated with the action of restricted brain regions, and this association is temporally stable; by contrast, DSP argues that cognitive functions are better explained by interactions between several brain areas, whose engagement in specific functions is temporal and context-dependent and based on neural reuse. We outline the main neurobiological facts about adolescent maturation, focusing on the neuroanatomical and neurofunctional processes associated with adolescence. We then explain the importance of emotional management in adolescent maturation. We explain the interplay between emotion and cognition under the scope of CCA and DSP, both at neural and behavioral levels. Finally, we justify why, according to CCA, emotional management is understood as regulation, specifically because the cognitive aspects of the brain are in charge of regulating emotion-related modules. However, the key word in DSP is integration, since neural information from different brain areas is integrated from the beginning of the process. Consequently, although the terms should not be conceptually confused, there is no cognition without emotion, and vice versa. Thus, emotional integration is not an independent process that just happens to the subject, but a crucial part of personal growth. Considering the importance of neuropsychological research in the development of educational and legal policies concerning adolescents, we intend to expose that the holistic view of adolescents is dependent on whether one holds the implicit or explicit interpretation of brain functioning. PMID:27602012

  9. Adolescent Emotional Maturation through Divergent Models of Brain Organization

    PubMed Central

    Oron Semper, Jose V.; Murillo, Jose I.; Bernacer, Javier

    2016-01-01

    In this article we introduce the hypothesis that neuropsychological adolescent maturation, and in particular emotional management, may have opposing explanations depending on the interpretation of the assumed brain architecture, that is, whether a componential computational account (CCA) or a dynamic systems perspective (DSP) is used. According to CCA, cognitive functions are associated with the action of restricted brain regions, and this association is temporally stable; by contrast, DSP argues that cognitive functions are better explained by interactions between several brain areas, whose engagement in specific functions is temporal and context-dependent and based on neural reuse. We outline the main neurobiological facts about adolescent maturation, focusing on the neuroanatomical and neurofunctional processes associated with adolescence. We then explain the importance of emotional management in adolescent maturation. We explain the interplay between emotion and cognition under the scope of CCA and DSP, both at neural and behavioral levels. Finally, we justify why, according to CCA, emotional management is understood as regulation, specifically because the cognitive aspects of the brain are in charge of regulating emotion-related modules. However, the key word in DSP is integration, since neural information from different brain areas is integrated from the beginning of the process. Consequently, although the terms should not be conceptually confused, there is no cognition without emotion, and vice versa. Thus, emotional integration is not an independent process that just happens to the subject, but a crucial part of personal growth. Considering the importance of neuropsychological research in the development of educational and legal policies concerning adolescents, we intend to expose that the holistic view of adolescents is dependent on whether one holds the implicit or explicit interpretation of brain functioning. PMID:27602012

  10. Closed traumatic brain injury model in sheep mimicking high-velocity, closed head trauma in humans.

    PubMed

    Grimmelt, A-C; Eitzen, S; Balakhadze, I; Fischer, B; Wölfer, J; Schiffbauer, H; Gorji, A; Greiner, C

    2011-08-01

    To date, there are only a few, non-evidence based, cerebroprotective therapeutic strategies for treatment and, accordingly, for prevention of secondary brain injuries following severe closed head trauma. In order to develop new therapy strategies, existing realistic animal models need to be advanced. The objective is to bridge standardized small animal models and actual patient medical care, since the results of experimental small animal studies often cannot be transferred to brain-injured humans. For improved standardization of high-velocity trauma, new trauma devices for initiating closed traumatic brain injury in sheep were developed. The following new devices were tested: 1. An anatomically shaped rubber bolt with an integrated oscillation absorber for prevention of skull fractures; 2. Stationary mounting of the bolt to guarantee stable experimental conditions; 3. Varying degrees of trauma severity, i. e., mild and severe closed traumatic brain injury, using different cartridges; and 4. Trauma analysis via high-speed video recording. Peritraumatic measurements of intracranial pressure, brain tissue pH, brain tissue oxygen, and carbon dioxide pressure, as well as neurotransmitter concentrations were performed. Cerebral injuries were documented with magnetic resonance imaging and compared to neuropathological results. Due to the new trauma devices, skull fractures were prevented. The high-speed video recording documented a realistic trauma mechanism for a car accident. Enhancement of extracellular glutamate, aspartate, and gamma amino butyric acid concentrations began 60 min after the trauma. Magnetic resonance imaging and neuropathological results showed characteristic injury patterns of mild, and severe, closed traumatic brain injury. The severe, closed traumatic brain injury group showed diffuse axonal injuries, traumatic subarachnoid hemorrhage, and hemorrhagic contusions with inconsistent distribution among the animals. The model presented here achieves

  11. MOS integrated circuit fault modeling

    NASA Technical Reports Server (NTRS)

    Sievers, M.

    1985-01-01

    Three digital simulation techniques for MOS integrated circuit faults were examined. These techniques embody a hierarchy of complexity bracketing the range of simulation levels. The digital approaches are: transistor-level, connector-switch-attenuator level, and gate level. The advantages and disadvantages are discussed. Failure characteristics are also described.

  12. Mobile Technology Integrated Pedagogical Model

    ERIC Educational Resources Information Center

    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…

  13. The definition of community integration: perspectives of people with brain injuries.

    PubMed

    McColl, M A; Carlson, P; Johnston, J; Minnes, P; Shue, K; Davies, D; Karlovits, T

    1998-01-01

    Despite considerable attention to community integration and related topics in the past decades, a clear definition of community integration continues to elude researchers and service providers. Common to most discussions of the topic, however, are three ideas: that integration involves relationships with others, independence in one's living situation and activities to fill one's time. The present study sought to expand this conceptualization of community integration by asking people with brain injuries for their own perspectives on community integration. This qualitative study resulted in a definition of community integration consisting of nine indicators: orientation, acceptance, conformity, close and diffuse relationships, living situation, independence, productivity and leisure. These indicators were empirically derived from the text of 116 interviews with people with moderate-severe brain injuries living in the community. Eighteen adults living in supported living programmes were followed for 1 year, to track their evolving definition of integration and the factors they felt were related to integration. The study also showed a general trend toward more positive evaluation over the year, and revealed that positive evaluation was frequently related to meeting new people and freedom from staff supervision. These findings are interpreted in the light of recommendations for community programmes. PMID:9483334

  14. Large-scale in silico modeling of metabolic interactions between cell types in the human brain.

    PubMed

    Lewis, Nathan E; Schramm, Gunnar; Bordbar, Aarash; Schellenberger, Jan; Andersen, Michael P; Cheng, Jeffrey K; Patel, Nilam; Yee, Alex; Lewis, Randall A; Eils, Roland; König, Rainer; Palsson, Bernhard Ø

    2010-12-01

    Metabolic interactions between multiple cell types are difficult to model using existing approaches. Here we present a workflow that integrates gene expression data, proteomics data and literature-based manual curation to model human metabolism within and between different types of cells. Transport reactions are used to account for the transfer of metabolites between models of different cell types via the interstitial fluid. We apply the method to create models of brain energy metabolism that recapitulate metabolic interactions between astrocytes and various neuron types relevant to Alzheimer's disease. Analysis of the models identifies genes and pathways that may explain observed experimental phenomena, including the differential effects of the disease on cell types and regions of the brain. Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in the human tissue microenvironment and provide detailed mechanistic insight into high-throughput data analysis. PMID:21102456

  15. Mathematical Modeling of Human Glioma Growth Based on Brain Topological Structures: Study of Two Clinical Cases

    PubMed Central

    Suarez, Cecilia; Maglietti, Felipe; Colonna, Mario; Breitburd, Karina; Marshall, Guillermo

    2012-01-01

    Gliomas are the most common primary brain tumors and yet almost incurable due mainly to their great invasion capability. This represents a challenge to present clinical oncology. Here, we introduce a mathematical model aiming to improve tumor spreading capability definition. The model consists in a time dependent reaction-diffusion equation in a three-dimensional spatial domain that distinguishes between different brain topological structures. The model uses a series of digitized images from brain slices covering the whole human brain. The Talairach atlas included in the model describes brain structures at different levels. Also, the inclusion of the Brodmann areas allows prediction of the brain functions affected during tumor evolution and the estimation of correlated symptoms. The model is solved numerically using patient-specific parametrization and finite differences. Simulations consider an initial state with cellular proliferation alone (benign tumor), and an advanced state when infiltration starts (malign tumor). Survival time is estimated on the basis of tumor size and location. The model is used to predict tumor evolution in two clinical cases. In the first case, predictions show that real infiltrative areas are underestimated by current diagnostic imaging. In the second case, tumor spreading predictions were shown to be more accurate than those derived from previous models in the literature. Our results suggest that the inclusion of differential migration in glioma growth models constitutes another step towards a better prediction of tumor infiltration at the moment of surgical or radiosurgical target definition. Also, the addition of physiological/psychological considerations to classical anatomical models will provide a better and integral understanding of the patient disease at the moment of deciding therapeutic options, taking into account not only survival but also life quality. PMID:22761843

  16. A revised dosimetric model of the adult head and brain

    SciTech Connect

    Bouchet, L.G.; Bolch, W.E.; Weber, D.A.; Atkins, H.L.; Poston, J.W. ||

    1996-07-01

    During the last decade, several new radiopharmaceuticals have been introduced for brain imaging. The marked differences of these tracers in tissue specificicity within the brain and their increasing use for diagnostic studies support the need for a more antihropomorphic model of the human brain and head. Brain and head models developed in the past have comprised only simplistic representations of this anatomic region. A new brain model has been developed which includes eight subregions: the caudate nucleus, the cerebellium, the cerebral cortex, the lateral ventricles, the lentiform nucleus, the thalamus, the third ventricle and the white matter. This brain model has been included within a slightly modified version of the head model developed by Poston et al. in 1984. The head model, which includes both the thyroid and eyes, was modified in this work to include the cerebrospinal fluid within the cranial and spinal regions. Absorbed fractions of energy for photon and electron sources located in thirteen source regions within the new head model were calculated using the EGS4 Monte Carlo radiation transport code for radiations in the energy range 10 keV to 4 MeV. S-values were calculated for five radionuclides used in brain imaging ({sup 11}C, {sup 15}O, {sup 18}F, {sup 99m}Tc and {sup 123}I) and for three radionuclides showing selective uptake in the thyroid ({sup 99m}Tc, {sup 123}I, and {sup 131}I). S-values were calculated using 100 discrete energy points in the beta-emission spectrum of the different radionuclides. 17 refs., 14 figs., 3 tabs.

  17. Comparison of electrical conductivities of various brain phantom gels: Developing a 'Brain Gel Model'

    PubMed

    Kandadai, Madhuvanthi A; Raymond, Jason L; Shaw, George J

    2012-12-01

    The use of conducting gels to mimic brain and other tissues is of increasing interest in the development of new medical devices. Currently, there are few such models that can be utilized at physiologic temperatures. In this work, the conductivities of agar, agarose and gelatin gels were manipulated by varying NaCl concentration from 0-1 mg/ml. The AC conductivity was measured at room and physiological temperatures (37°C) in the 100-500 Hz frequency range. Conductivity (σ) was nearly independent of frequency but increased linearly with NaCl concentration and was higher at physiological temperatures in these gels. A formula for predicting conductivity as a function of NaCl concentration was derived for each gel type. The overall goal is to develop a 'brain gel model', for studying low frequency electrical properties of the brain and other tissues at physiological temperatures. PMID:23139442

  18. A Two-Part Mixed-Effects Modeling Framework For Analyzing Whole-Brain Network Data

    PubMed Central

    Simpson, Sean L.; Laurienti, Paul J.

    2015-01-01

    Whole-brain network analyses remain the vanguard in neuroimaging research, coming to prominence within the last decade. Network science approaches have facilitated these analyses and allowed examining the brain as an integrated system. However, statistical methods for modeling and comparing groups of networks have lagged behind. Fusing multivariate statistical approaches with network science presents the best path to develop these methods. Toward this end, we propose a two-part mixed-effects modeling framework that allows modeling both the probability of a connection (presence/absence of an edge) and the strength of a connection if it exists. Models within this framework enable quantifying the relationship between an outcome (e.g., disease status) and connectivity patterns in the brain while reducing spurious correlations through inclusion of confounding covariates. They also enable prediction about an outcome based on connectivity structure and vice versa, simulating networks to gain a better understanding of normal ranges of topological variability, and thresholding networks leveraging group information. Thus, they provide a comprehensive approach to studying system level brain properties to further our understanding of normal and abnormal brain function. PMID:25796135

  19. The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

    NASA Technical Reports Server (NTRS)

    Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris; Holden, Tina; Rudisill, Marianne

    1993-01-01

    One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry.

  20. Mouse Models of Brain Metastasis for Unravelling Tumour Progression.

    PubMed

    Soto, Manuel Sarmiento; Sibson, Nicola R

    2016-01-01

    Secondary tumours in the brain account for 40 % of triple negative breast cancer patients, and the percentage may be higher at the time of autopsy. The use of in vivo models allow us to recapitulate the molecular mechanisms potentially used by circulating breast tumour cells to proliferate within the brain.Metastasis is a multistep process that depends on the success of several stages including cell evasion from the primary tumour, distribution and survival within the blood stream and cerebral microvasculature, penetration of the blood-brain barrier and proliferation within the brain microenvironment. Cellular adhesion molecules are key proteins involved in all of the steps in the metastatic process. Our group has developed two different in vivo models to encompass both seeding and colonisation stages of the metastatic process: (1) haematogenous dissemination of tumour cells by direct injection into the left ventricle of the heart, and (2) direct implantation of the tumour cells into the mouse brain.This chapter describes, in detail, the practical implementation of the intracerebral model, which can be used to analyse tumour proliferation within a specific area of the central nervous system and tumour-host cell interactions. We also describe the use of immunohistochemistry techniques to identify, at the molecular scale, tumour-host cell interactions, which may open new windows for brain metastasis therapy. PMID:27325270

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

    ERIC Educational Resources Information Center

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

    2007-01-01

    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…

  2. A novel approach for integrative studies on neurodegenerative diseases in human brains

    PubMed Central

    Theofilas, Panos; Polichiso, Livia; Wang, Xuehua; Lima, Luzia C.; Alho, Ana T. L.; Leite, Renata E. P.; Suemoto, Claudia K.; Pasqualucci, Carlos A.; Filho, Wilson Jacob; Heinsen, Helmut; Grinberg, Lea T.

    2014-01-01

    Despite a massive research effort to elucidate Alzheimer’s disease (AD) in recent decades, effective treatment remains elusive. This failure may relate to an oversimplification of the pathogenic processes underlying AD and also lack of understanding of AD progression during its long latent stages. Although evidence shows that the two specific neuropathological hallmarks in AD (neuronal loss and protein accumulation), which are opposite in nature, do not progress in parallel, the great majority of studies have focused on only one of these aspects. Furthermore, research focusing on single structures is likely to render an incomplete picture of AD pathogenesis because as AD involves complete brain networks, potential compensatory mechanisms within the network may ameliorate impairment of the system to a certain extent. Here, we describe an approach for enabling integrative analysis of the dual-nature lesions, simultaneously, in all components of one of the brain networks most vulnerable to AD. This approach is based on significant development of methods previously described mainly by our group that were optimized and complemented for this study. It combines unbiased stereology with immunohistochemistry and immunofluorescence, making use of advanced graphics computing for three-dimensional (3D) volume reconstructions. Although this study was performed inhuman brainstem and focused in AD, it may be applied to the study of any neurological disease characterized by dual-nature lesions, in humans and animal models. This approach does not require a high level of investment in new equipment and a significant number of specimens can be processed and analyzed within a funding cycle. PMID:24503023

  3. Neural mass model-based tracking of anesthetic brain states.

    PubMed

    Kuhlmann, Levin; Freestone, Dean R; Manton, Jonathan H; Heyse, Bjorn; Vereecke, Hugo E M; Lipping, Tarmo; Struys, Michel M R F; Liley, David T J

    2016-06-01

    Neural mass model-based tracking of brain states from electroencephalographic signals holds the promise of simultaneously tracking brain states while inferring underlying physiological changes in various neuroscientific and clinical applications. Here, neural mass model-based tracking of brain states using the unscented Kalman filter applied to estimate parameters of the Jansen-Rit cortical population model is evaluated through the application of propofol-based anesthetic state monitoring. In particular, 15 subjects underwent propofol anesthesia induction from awake to anesthetised while behavioral responsiveness was monitored and frontal electroencephalographic signals were recorded. The unscented Kalman filter Jansen-Rit model approach applied to frontal electroencephalography achieved reasonable testing performance for classification of the anesthetic brain state (sensitivity: 0.51; chance sensitivity: 0.17; nearest neighbor sensitivity 0.75) when compared to approaches based on linear (autoregressive moving average) modeling (sensitivity 0.58; nearest neighbor sensitivity: 0.91) and a high performing standard depth of anesthesia monitoring measure, Higuchi Fractal Dimension (sensitivity: 0.50; nearest neighbor sensitivity: 0.88). Moreover, it was found that the unscented Kalman filter based parameter estimates of the inhibitory postsynaptic potential amplitude varied in the physiologically expected direction with increases in propofol concentration, while the estimates of the inhibitory postsynaptic potential rate constant did not. These results combined with analysis of monotonicity of parameter estimates, error analysis of parameter estimates, and observability analysis of the Jansen-Rit model, along with considerations of extensions of the Jansen-Rit model, suggests that the Jansen-Rit model combined with unscented Kalman filtering provides a valuable reference point for future real-time brain state tracking studies. This is especially true for studies of

  4. MR image denoising method for brain surface 3D modeling

    NASA Astrophysics Data System (ADS)

    Zhao, De-xin; Liu, Peng-jie; Zhang, De-gan

    2014-11-01

    Three-dimensional (3D) modeling of medical images is a critical part of surgical simulation. In this paper, we focus on the magnetic resonance (MR) images denoising for brain modeling reconstruction, and exploit a practical solution. We attempt to remove the noise existing in the MR imaging signal and preserve the image characteristics. A wavelet-based adaptive curve shrinkage function is presented in spherical coordinates system. The comparative experiments show that the denoising method can preserve better image details and enhance the coefficients of contours. Using these denoised images, the brain 3D visualization is given through surface triangle mesh model, which demonstrates the effectiveness of the proposed method.

  5. An integrated communications demand model

    NASA Astrophysics Data System (ADS)

    Doubleday, C. F.

    1980-11-01

    A computer model of communications demand is being developed to permit dynamic simulations of the long-term evolution of demand for communications media in the U.K. to be made under alternative assumptions about social, economic and technological trends in British Telecom's business environment. The context and objectives of the project and the potential uses of the model are reviewed, and four key concepts in the demand for communications media, around which the model is being structured are discussed: (1) the generation of communications demand; (2) substitution between media; (3) technological convergence; and (4) competition. Two outline perspectives on the model itself are given.

  6. Model Identification of Integrated ARMA Processes

    ERIC Educational Resources Information Center

    Stadnytska, Tetiana; Braun, Simone; Werner, Joachim

    2008-01-01

    This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…

  7. Social Ecological Model Analysis for ICT Integration

    ERIC Educational Resources Information Center

    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…

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

    PubMed Central

    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

  9. Jamaica Integrated National Energy Planning Model

    SciTech Connect

    Macal, C.M.

    1987-01-01

    The Jamaica Integrated National Energy Planning (JINEP) Model was developed by Argonne National Laboratory under contract to the Jamaica Ministry of Mining, Energy, and Tourism. JINEP is a comprehensive model of the energy-producing sector and the major energy consuming sectors of Jamaica. The JINEP Model is an application of a modelling system, the Integrated Demand and Energy Supply (IDES) Model, that was previously developed at Argonne for the purpose of analyzing energy systems of developing countries. IDES is based on several years of experience in analyzing energy planning issues characteristic of developing countries.

  10. Classical Wave Model of Quantum-Like Processing in Brain

    NASA Astrophysics Data System (ADS)

    Khrennikov, A.

    2011-01-01

    We discuss the conjecture on quantum-like (QL) processing of information in the brain. It is not based on the physical quantum brain (e.g., Penrose) - quantum physical carriers of information. In our approach the brain created the QL representation (QLR) of information in Hilbert space. It uses quantum information rules in decision making. The existence of such QLR was (at least preliminary) confirmed by experimental data from cognitive psychology. The violation of the law of total probability in these experiments is an important sign of nonclassicality of data. In so called "constructive wave function approach" such data can be represented by complex amplitudes. We presented 1,2 the QL model of decision making. In this paper we speculate on a possible physical realization of QLR in the brain: a classical wave model producing QLR . It is based on variety of time scales in the brain. Each pair of scales (fine - the background fluctuations of electromagnetic field and rough - the cognitive image scale) induces the QL representation. The background field plays the crucial role in creation of "superstrong QL correlations" in the brain.

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

    PubMed Central

    Budday, Silvia; Raybaud, Charles; Kuhl, Ellen

    2014-01-01

    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. PMID:25008163

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

    NASA Astrophysics Data System (ADS)

    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.

  13. Integrated Environmental Modeling: Quantitative Microbial Risk Assessment

    EPA Science Inventory

    The presentation discusses the need for microbial assessments and presents a road map associated with quantitative microbial risk assessments, through an integrated environmental modeling approach. A brief introduction and the strengths of the current knowledge are illustrated. W...

  14. Predictive modeling of neuroanatomic structures for brain atrophy detection

    NASA Astrophysics Data System (ADS)

    Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

    2010-03-01

    In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.

  15. A Measure for Brain Complexity: Relating Functional Segregation and Integration in the Nervous System

    NASA Astrophysics Data System (ADS)

    Tononi, Giulio; Sporns, Olaf; Edelman, Gerald M.

    1994-05-01

    In brains of higher vertebrates, the functional segregation of local areas that differ in their anatomy and physiology contrasts sharply with their global integration during perception and behavior. In this paper, we introduce a measure, called neural complexity (C_N), that captures the interplay between these two fundamental aspects of brain organization. We express functional segregation within a neural system in terms of the relative statistical independence of small subsets of the system and functional integration in terms of significant deviations from independence of large subsets. C_N is then obtained from estimates of the average deviation from statistical independence for subsets of increasing size. C_N is shown to be high when functional segregation coexists with integration and to be low when the components of a system are either completely independent (segregated) or completely dependent (integrated). We apply this complexity measure in computer simulations of cortical areas to examine how some basic principles of neuroanatomical organization constrain brain dynamics. We show that the connectivity patterns of the cerebral cortex, such as a high density of connections, strong local connectivity organizing cells into neuronal groups, patchiness in the connectivity among neuronal groups, and prevalent reciprocal connections, are associated with high values of C_N. The approach outlined here may prove useful in analyzing complexity in other biological domains such as gene regulation and embryogenesis.

  16. Midline (Central) Fluid Percussion Model of Traumatic Brain Injury.

    PubMed

    Rowe, Rachel K; Griffiths, Daniel R; Lifshitz, Jonathan

    2016-01-01

    Research models of traumatic brain injury (TBI) hold significant validity towards the human condition, with each model replicating a subset of clinical features and symptoms. After 30 years of characterization and implementation, fluid percussion injury (FPI) is firmly recognized as a clinically relevant model of TBI, encompassing concussion through severe injury. The midline variation of FPI may best represent mild and diffuse clinical brain injury, because of the acute behavioral deficits, the late onset of subtle behavioral morbidities, and the absence of gross histopathology. This chapter outlines the procedures for midline (diffuse) FPI in adult male rats and mice. With these procedures, it becomes possible to generate brain-injured laboratory animals for studies of injury-induced pathophysiology and behavioral deficits, for which rational therapeutic interventions can be implemented. PMID:27604721

  17. A Normalization Model of Multisensory Integration

    PubMed Central

    Ohshiro, Tomokazu; Angelaki, Dora E.; DeAngelis, Gregory C.

    2011-01-01

    Responses of neurons that integrate multiple sensory inputs are traditionally characterized in terms of a set of empirical principles. However, a simple computational framework that accounts for these empirical features of multisensory integration has not been established. We propose that divisive normalization, acting at the stage of multisensory integration, can account for many of the empirical principles of multisensory integration exhibited by single neurons, such as the principle of inverse effectiveness and the spatial principle. This model, which employs a simple functional operation (normalization) for which there is considerable experimental support, also accounts for the recent observation that the mathematical rule by which multisensory neurons combine their inputs changes with cue reliability. The normalization model, which makes a strong testable prediction regarding cross-modal suppression, may therefore provide a simple unifying computational account of the key features of multisensory integration by neurons. PMID:21552274

  18. Resolving structural variability in network models and the brain.

    PubMed

    Klimm, Florian; Bassett, Danielle S; Carlson, Jean M; Mucha, Peter J

    2014-03-01

    Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for the

  19. Resolving Structural Variability in Network Models and the Brain

    PubMed Central

    Klimm, Florian; Bassett, Danielle S.; Carlson, Jean M.; Mucha, Peter J.

    2014-01-01

    Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling—in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity) do not in general simultaneously display a second (e.g., hierarchy). This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful starting point for

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

    PubMed

    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. PMID:26146132

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

    PubMed

    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. PMID:26054960

  2. 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

    PubMed Central

    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

  3. A revised dosimetric model of the head and brain

    SciTech Connect

    Bolch, W.E.; Poston, J.W. Sr.

    1995-05-01

    The use of PET and SPECT radiopharmaceuticals in brain imaging has greatly expanded over the past several years. Many of these agents localize within particular subregions of the brain, thus allowing for detailed physiologic and metabolic imaging. Dosimetric models to support these advances in nuclear medicine have been lacking. For example, the brain within the phantom of MIRD Pamphlet No. 5 Revised is modeled simply as a single ellipsoid of tissue with no differentiation of its internal structures. To address this need, the MIRD Committee established a Task Group in 1992 to construct a revised dosimetric model of the brain to include the following subregions: the cerebral cortex, the white matter, the cerebellum, the thalamus, the caudate nucleus, the lentiform nucleus (putamen and globus pallidus), the cerebral spinal fluid (within the subarachnoid space of the brain), the lateral ventricles, and the third ventricle. Estimates of both electron and photon absorbed fractions (AF) were subsequently calculated using the EGS4 radiation transport code. For most of the internal brain structures, electron AFs are shown to fall fellow unity for all regions within the energy range of {approximately}200 keV to 4 MeV. For example, AFs for the caudate nucleus as both a source and target region and estimated as 0.98, 0.84, 0.39 for 200-keV, 1-MeV, and 4-MeV electron sources, respectively. Corresponding AFs within the white matter as a source and target region are estimated as 1.0, 0.95, and 0.79 for these same electron energies. Revised S values were subsequently calculated for a variety of beta-particle and positron emitters used in brain imaging.

  4. Brain White Matter Tract Integrity and Cognitive Abilities in Community-Dwelling Older People: The Lothian Birth Cohort, 1936

    PubMed Central

    2013-01-01

    Objective: The present study investigates associations between brain white matter tract integrity and cognitive abilities in community-dwelling older people (N = 655). We explored two potential confounds of white matter tract−cognition associations in later life: (a) whether the associations between tracts and specific cognitive abilities are accounted for by general cognitive ability (g); and (b) how the presence of atrophy and white matter lesions affect these associations. Method: Tract integrity was determined using quantitative diffusion magnetic resonance imaging tractography (tract-averaged fractional anisotropy [FA]). Using confirmatory factor analysis, we compared first-order and bifactor models to investigate whether specific tract-ability associations were accounted for by g. Results: Significant associations were found between g and FA in bilateral anterior thalamic radiations (r range: .16−.18, p < .01), uncinate (r range: .19−.26, p < .001), arcuate fasciculi (r range: .11−.12, p < .05), and the splenium of corpus callosum (r = .14, p < .01). After controlling for g within the bifactor model, some significant specific cognitive domain associations remained. Results also suggest that the primary effects of controlling for whole brain integrity were on g associations, not specific abilities. Conclusion: Results suggest that g accounts for most of, but not all, the tract−cognition associations in the current data. When controlling for age-related overall brain structural changes, only minor attenuations of the tract−cognition associations were found, and these were primarily with g. In totality, the results highlight the importance of controlling for g when investigating associations between specific cognitive abilities and neuropsychology variables. PMID:23937481

  5. C5a alters blood-brain barrier integrity in experimental lupus.

    PubMed

    Jacob, Alexander; Hack, Bradley; Chiang, Eddie; Garcia, Joe G N; Quigg, Richard J; Alexander, Jessy J

    2010-06-01

    The blood-brain barrier (BBB) is a crucial anatomic location in the brain. Its dysfunction complicates many neurodegenerative diseases, from acute conditions, such as sepsis, to chronic diseases, such as systemic lupus erythematosus (SLE). Several studies suggest an altered BBB in lupus, but the underlying mechanism remains unknown. In the current study, we observed a definite loss of BBB integrity in MRL/MpJ-Tnfrsf6(lpr) (MRL/lpr) lupus mice by IgG infiltration into brain parenchyma. In line with this result, we examined the role of complement activation, a key event in this setting, in maintenance of BBB integrity. Complement activation generates C5a, a molecule with multiple functions. Because the expression of the C5a receptor (C5aR) is significantly increased in brain endothelial cells treated with lupus serum, the study focused on the role of C5a signaling through its G-protein-coupled receptor C5aR in brain endothelial cells, in a lupus setting. Reactive oxygen species production increased significantly in endothelial cells, in both primary cells and the bEnd3 cell line treated with lupus serum from MRL/lpr mice, compared with those treated with control serum from MRL(+/+) mice. In addition, increased permeability monitored by changes in transendothelial electrical resistance, cytoskeletal remodeling caused by actin fiber rearrangement, and increased iNOS mRNA expression were observed in bEnd3 cells. These disruptive effects were alleviated by pretreating cells with a C5a receptor antagonist (C5aRant) or a C5a antibody. Furthermore, the structural integrity of the vasculature in MRL/lpr brain was maintained by C5aR inhibition. These results demonstrate the regulation of BBB integrity by the complement system in a neuroinflammatory setting. For the first time, a novel role of C5a in the maintenance of BBB integrity is identified and the potential of C5a/C5aR blockade highlighted as a promising therapeutic strategy in SLE and other neurodegenerative diseases

  6. Inferring brain-computational mechanisms with models of activity measurements.

    PubMed

    Kriegeskorte, Nikolaus; Diedrichsen, Jörn

    2016-10-01

    High-resolution functional imaging is providing increasingly rich measurements of brain activity in animals and humans. A major challenge is to leverage such data to gain insight into the brain's computational mechanisms. The first step is to define candidate brain-computational models (BCMs) that can perform the behavioural task in question. We would then like to infer which of the candidate BCMs best accounts for measured brain-activity data. Here we describe a method that complements each BCM by a measurement model (MM), which simulates the way the brain-activity measurements reflect neuronal activity (e.g. local averaging in functional magnetic resonance imaging (fMRI) voxels or sparse sampling in array recordings). The resulting generative model (BCM-MM) produces simulated measurements. To avoid having to fit the MM to predict each individual measurement channel of the brain-activity data, we compare the measured and predicted data at the level of summary statistics. We describe a novel particular implementation of this approach, called probabilistic representational similarity analysis (pRSA) with MMs, which uses representational dissimilarity matrices (RDMs) as the summary statistics. We validate this method by simulations of fMRI measurements (locally averaging voxels) based on a deep convolutional neural network for visual object recognition. Results indicate that the way the measurements sample the activity patterns strongly affects the apparent representational dissimilarities. However, modelling of the measurement process can account for these effects, and different BCMs remain distinguishable even under substantial noise. The pRSA method enables us to perform Bayesian inference on the set of BCMs and to recognize the data-generating model in each case.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. PMID:27574316

  7. Animal models of brain maldevelopment induced by cycad plant genotoxins.

    PubMed

    Kisby, Glen E; Moore, Holly; Spencer, Peter S

    2013-12-01

    Cycads are long-lived tropical and subtropical plants that contain azoxyglycosides (e.g., cycasin, macrozamin) and neurotoxic amino acids (notably β-N-methylamino-l-alanine l-BMAA), toxins that have been implicated in the etiology of a disappearing neurodegenerative disease, amyotrophic lateral sclerosis and parkinsonism-dementia complex that has been present in high incidence among three genetically distinct populations in the western Pacific. The neuropathology of amyotrophic lateral sclerosis/parkinsonism-dementia complex includes features suggestive of brain maldevelopment, an experimentally proven property of cycasin attributable to the genotoxic action of its aglycone methylazoxymethanol (MAM). This property of MAM has been exploited by neurobiologists as a tool to study perturbations of brain development. Depending on the neurodevelopmental stage, MAM can induce features in laboratory animals that model certain characteristics of epilepsy, schizophrenia, or ataxia. Studies in DNA repair-deficient mice show that MAM perturbs brain development through a DNA damage-mediated mechanism. The brain DNA lesions produced by systemic MAM appear to modulate the expression of genes that regulate neurodevelopment and contribute to neurodegeneration. Epigenetic changes (histone lysine methylation) have also been detected in the underdeveloped brain after MAM administration. The DNA damage and epigenetic changes produced by MAM and, perhaps by chemically related substances (e.g., nitrosamines, nitrosoureas, hydrazines), might be an important mechanism by which early-life exposure to genotoxicants can induce long-term brain dysfunction. PMID:24339036

  8. Animal Models of Brain Maldevelopment Induced by Cycad Plant Genotoxins

    PubMed Central

    Kisby, Glen E.; Moore, Holly; Spencer, Peter S.

    2014-01-01

    Cycads are long-lived tropical and subtropical plants that contain azoxyglycosides (e.g., cycasin, macrozamin) and neurotoxic amino acids (notably β-N-methylamino-L-alanine L-BMAA), toxins that have been implicated in the etiology of a disappearing neurodegenerative disease, amyotrophic lateral sclerosis and parkinsonism-dementia complex that has been present in high incidence among three genetically distinct populations in the western Pacific. The neuropathology of amyotrophic lateral sclerosis/parkinsonism-dementia complex includes features suggestive of brain maldevelopment, an experimentally proven property of cycasin attributable to the genotoxic action of its aglycone methylazoxymethanol (MAM). This property of MAM has been exploited by neurobiologists as a tool to study perturbations of brain development. Depending on the neurodevelopmental stage, MAM can induce features in laboratory animals that model certain characteristics of epilepsy, schizophrenia, or ataxia. Studies in DNA repair-deficient mice show that MAM perturbs brain development through a DNA damage-mediated mechanism. The brain DNA lesions produced by systemic MAM appear to modulate the expression of genes that regulate neurodevelopment and contribute to neurodegeneration. Epigenetic changes (histone lysine methylation) have also been detected in the underdeveloped brain after MAM administration. The DNA damage and epigenetic changes produced by MAM and, perhaps by chemically related substances (e.g., nitrosamines, nitrosoureas, hydrazines), might be an important mechanism by which early-life exposure to genotoxicants can induce long-term brain dysfunction. PMID:24339036

  9. Construction of a GP integration model.

    PubMed

    Batterham, R; Southern, D; Appleby, N; Elsworth, G; Fabris, S; Dunt, D; Young, D

    2002-04-01

    There are frequent calls to improve integration of health services, within and between primary and secondary care sectors. In Australia, general medical practitioners (GPs) are central to these endeavours. This paper aims to better conceptualise GP integration and to develop a model and index based on this. A conceptualisation of integration is proposed based on integration fundamentally as an activity or process not structure. Integration process is the frequency and quality of episodes of information exchange involving the GP and another practitioner or patient and aimed at fulfilling the objectives of the health care system with regard to patient care. These are both direct responses to structural forces and emergent GP capacities and dispositions. The content of this typology was studied using Concept Mapping in 11 groups of GPs, consumers and other practitioners. Clusters of related statements within thematic domains were used as the basis for a provisional model. This was tested using confirmatory factor analysis in a data set derived from a national probability sample of 501 GPs. Some re-specification of the model was necessary, with three integration process factors needing to be subdivided. One factor congeneric model assumptions were used to identify the constituent items for these factors. The result was a model in which 50 items measured nine integration process factors and 20 items measured five enabling factors. Two distinct but correlated higher order factors, relating to individual patient care and public (or community) health--in contrast to a single higher order factor for integration--were identified. The re-specified model was tested with a new sample of 151 GPs and exhibited strong psychometric properties. Reliability and validity were acceptable to this stage of the indices' development. Further testing of the index is necessary to demonstrate factor invariance of the indices in other contexts as well as their utility in cross

  10. Characterisation and modelling of brain tissue for surgical simulation.

    PubMed

    Mendizabal, A; Aguinaga, I; Sánchez, E

    2015-05-01

    Interactive surgical simulators capable of providing a realistic visual and haptic feedback to users are a promising technology for medical training and surgery planification. However, modelling the physical behaviour of human organs and tissues for surgery simulation remains a challenge. On the one hand, this is due to the difficulty to characterise the physical properties of biological soft tissues. On the other hand, the challenge still remains in the computation time requirements of real-time simulation required in interactive systems. Real-time surgical simulation and medical training must employ a sufficiently accurate and simple model of soft tissues in order to provide a realistic haptic and visual response. This study attempts to characterise the brain tissue at similar conditions to those that take place on surgical procedures. With this aim, porcine brain tissue is characterised, as a surrogate of human brain, on a rotational rheometer at low strain rates and large strains. In order to model the brain tissue with an adequate level of accuracy and simplicity, linear elastic, hyperelastic and quasi-linear viscoelastic models are defined. These models are simulated using the ABAQUS finite element platform and compared with the obtained experimental data. PMID:25676499

  11. Computational modeling of an endovascular approach to deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Teplitzky, Benjamin A.; Connolly, Allison T.; Bajwa, Jawad A.; Johnson, Matthew D.

    2014-04-01

    Objective. Deep brain stimulation (DBS) therapy currently relies on a transcranial neurosurgical technique to implant one or more electrode leads into the brain parenchyma. In this study, we used computational modeling to investigate the feasibility of using an endovascular approach to target DBS therapy. Approach. Image-based anatomical reconstructions of the human brain and vasculature were used to identify 17 established and hypothesized anatomical targets of DBS, of which five were found adjacent to a vein or artery with intraluminal diameter ≥1 mm. Two of these targets, the fornix and subgenual cingulate white matter (SgCwm) tracts, were further investigated using a computational modeling framework that combined segmented volumes of the vascularized brain, finite element models of the tissue voltage during DBS, and multi-compartment axon models to predict the direct electrophysiological effects of endovascular DBS. Main results. The models showed that: (1) a ring-electrode conforming to the vessel wall was more efficient at neural activation than a guidewire design, (2) increasing the length of a ring-electrode had minimal effect on neural activation thresholds, (3) large variability in neural activation occurred with suboptimal placement of a ring-electrode along the targeted vessel, and (4) activation thresholds for the fornix and SgCwm tracts were comparable for endovascular and stereotactic DBS, though endovascular DBS was able to produce significantly larger contralateral activation for a unilateral implantation. Significance. Together, these results suggest that endovascular DBS can serve as a complementary approach to stereotactic DBS in select cases.

  12. Identification of Differentially Expressed Genes through Integrated Study of Alzheimer’s Disease Affected Brain Regions

    PubMed Central

    Berretta, Regina; Moscato, Pablo

    2016-01-01

    Background Alzheimer’s disease (AD) is the most common form of dementia in older adults that damages the brain and results in impaired memory, thinking and behaviour. The identification of differentially expressed genes and related pathways among affected brain regions can provide more information on the mechanisms of AD. In the past decade, several studies have reported many genes that are associated with AD. This wealth of information has become difficult to follow and interpret as most of the results are conflicting. In that case, it is worth doing an integrated study of multiple datasets that helps to increase the total number of samples and the statistical power in detecting biomarkers. In this study, we present an integrated analysis of five different brain region datasets and introduce new genes that warrant further investigation. Methods The aim of our study is to apply a novel combinatorial optimisation based meta-analysis approach to identify differentially expressed genes that are associated to AD across brain regions. In this study, microarray gene expression data from 161 samples (74 non-demented controls, 87 AD) from the Entorhinal Cortex (EC), Hippocampus (HIP), Middle temporal gyrus (MTG), Posterior cingulate cortex (PC), Superior frontal gyrus (SFG) and visual cortex (VCX) brain regions were integrated and analysed using our method. The results are then compared to two popular meta-analysis methods, RankProd and GeneMeta, and to what can be obtained by analysing the individual datasets. Results We find genes related with AD that are consistent with existing studies, and new candidate genes not previously related with AD. Our study confirms the up-regualtion of INFAR2 and PTMA along with the down regulation of GPHN, RAB2A, PSMD14 and FGF. Novel genes PSMB2, WNK1, RPL15, SEMA4C, RWDD2A and LARGE are found to be differentially expressed across all brain regions. Further investigation on these genes may provide new insights into the development of AD

  13. Brain-gut interaction in irritable bowel syndrome: new findings of a multicomponent disease model.

    PubMed

    Schmulson, M J

    2001-02-01

    Knowledge on the pathophysiology of irritable bowel syndrome has evolved, beginning with disturbances in motility to visceral hypersensitivity, and ultimately to alterations in brain-gut bi-directional communication, where neurotransmitters such as serotonin play a key role. Recently, a multicomponent disease model that integrates all these alterations was proposed. This model is divided into physiological, cognitive, emotional and behavioral components that explain the gastrointestinal as well as the constitutional symptoms. In recent years there has been an explosion of research together with new developments in pharmacological treatments for IBS that support each component of this model. This review presents recent data in favor of these alterations in IBS. PMID:11347592

  14. Brain Network Analysis: Separating Cost from Topology Using Cost-Integration

    PubMed Central

    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. PMID:21829437

  15. Integrating model abstraction into monitoring strategies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study was designed and performed to investigate the opportunities and benefits of integrating model abstraction techniques into monitoring strategies. The study focused on future applications of modeling to contingency planning and management of potential and actual contaminant release sites wi...

  16. Modeling "Soft" Errors in Bipolar Integrated Circuits

    NASA Technical Reports Server (NTRS)

    Zoutendyk, J.; Benumof, R.; Vonroos, O.

    1985-01-01

    Mathematical models represent single-event upset in bipolar memory chips. Physics of single-event upset in integrated circuits discussed in theoretical paper. Pair of companion reports present mathematical models to predict critical charges for producing single-event upset in bipolar randomaccess memory (RAM) chips.

  17. Transcranial magnetic stimulation and brain atrophy: a computer-based human brain model study

    PubMed Central

    Eden, Uri; Fregni, Felipe; Valero-Cabre, Antoni; Ramos-Estebanez, Ciro; Pronio-Stelluto, Valerie; Grodzinsky, Alan; Zahn, Markus; Pascual-Leone, Alvaro

    2012-01-01

    This paper is aimed at exploring the effect of cortical brain atrophy on the currents induced by transcranial magnetic stimulation (TMS). We compared the currents induced by various TMS conditions on several different MRI derived finite element head models of brain atrophy, incorporating both decreasing cortical volume and widened sulci. The current densities induced in the cortex were dependent upon the degree and type of cortical atrophy and were altered in magnitude, location, and orientation when compared to healthy head models. Predictive models of the degree of current density attenuation as a function of the scalp-to-cortex distance were analyzed, concluding that those which ignore the electromagnetic field–tissue interactions lead to inaccurate conclusions. Ultimately, the precise site and population of neural elements stimulated by TMS in an atrophic brain cannot be predicted based on healthy head models which ignore the effects of the altered cortex on the stimulating currents. Clinical applications of TMS should be carefully considered in light of these findings. PMID:18193208

  18. Read My Lips: Brain Dynamics Associated with Audiovisual Integration and Deviance Detection.

    PubMed

    Tse, Chun-Yu; Gratton, Gabriele; Garnsey, Susan M; Novak, Michael A; Fabiani, Monica

    2015-09-01

    Information from different modalities is initially processed in different brain areas, yet real-world perception often requires the integration of multisensory signals into a single percept. An example is the McGurk effect, in which people viewing a speaker whose lip movements do not match the utterance perceive the spoken sounds incorrectly, hearing them as more similar to those signaled by the visual rather than the auditory input. This indicates that audiovisual integration is important for generating the phoneme percept. Here we asked when and where the audiovisual integration process occurs, providing spatial and temporal boundaries for the processes generating phoneme perception. Specifically, we wanted to separate audiovisual integration from other processes, such as simple deviance detection. Building on previous work employing ERPs, we used an oddball paradigm in which task-irrelevant audiovisually deviant stimuli were embedded in strings of non-deviant stimuli. We also recorded the event-related optical signal, an imaging method combining spatial and temporal resolution, to investigate the time course and neuroanatomical substrate of audiovisual integration. We found that audiovisual deviants elicit a short duration response in the middle/superior temporal gyrus, whereas audiovisual integration elicits a more extended response involving also inferior frontal and occipital regions. Interactions between audiovisual integration and deviance detection processes were observed in the posterior/superior temporal gyrus. These data suggest that dynamic interactions between inferior frontal cortex and sensory regions play a significant role in multimodal integration. PMID:25848682

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

    PubMed

    Sánchez-Ramón, Silvia; Faure, Florence

    2016-01-01

    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. PMID:26869886

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

    ERIC Educational Resources Information Center

    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…

  1. Virtual model of the human brain for neurosurgical simulation.

    PubMed

    De Paolis, Lucio T; De Mauro, Alessandro; Raczkowsky, Joerg; Aloisio, Giovanni

    2009-01-01

    The aim of this work is to develop a realistic virtual model of the human brain that could be used in a neurosurgical simulation for both educational and preoperative planning purposes. The goal of such a system would be to enhance the practice of surgery students, avoiding the use of animals, cadavers and plastic phantoms. A surgeon, before carrying out the real procedure, will, with this system, be able to rehearse by using a surgical simulator based on detailed virtual reality models of the human brain, reconstructed with real patient's medical images. In order to obtain a realistic and useful simulation we focused our research on the physical modelling of the brain as a deformable body and on the interactions with surgical instruments. The developed prototype is based on the mass-spring-damper model and, in order to obtain deformations similar to the real ones, a three tiered structure has been built. In this way, we have obtained local and realistic deformations using an ad-hoc point distribution in the volume where the contact between the brain surface and a surgical instrument takes place. PMID:19745425

  2. Effects of exercise on brain functions in diabetic animal models

    PubMed Central

    Yi, Sun Shin

    2015-01-01

    Human life span has dramatically increased over several decades, and the quality of life has been considered to be equally important. However, diabetes mellitus (DM) characterized by problems related to insulin secretion and recognition has become a serious health problem in recent years that threatens human health by causing decline in brain functions and finally leading to neurodegenerative diseases. Exercise is recognized as an effective therapy for DM without medication administration. Exercise studies using experimental animals are a suitable option to overcome this drawback, and animal studies have improved continuously according to the needs of the experimenters. Since brain health is the most significant factor in human life, it is very important to assess brain functions according to the different exercise conditions using experimental animal models. Generally, there are two types of DM; insulin-dependent type 1 DM and an insulin-independent type 2 DM (T2DM); however, the author will mostly discuss brain functions in T2DM animal models in this review. Additionally, many physiopathologic alterations are caused in the brain by DM such as increased adiposity, inflammation, hormonal dysregulation, uncontrolled hyperphagia, insulin and leptin resistance, and dysregulation of neurotransmitters and declined neurogenesis in the hippocampus and we describe how exercise corrects these alterations in animal models. The results of changes in the brain environment differ according to voluntary, involuntary running exercises and resistance exercise, and gender in the animal studies. These factors have been mentioned in this review, and this review will be a good reference for studying how exercise can be used with therapy for treating DM. PMID:25987956

  3. Modeling for System Integration Studies (Presentation)

    SciTech Connect

    Orwig, K. D.

    2012-05-01

    This presentation describes some the data requirements needed for grid integration modeling and provides real-world examples of such data and its format. Renewable energy integration studies evaluate the operational impacts of variable generation. Transmission planning studies investigate where new transmission is needed to transfer energy from generation sources to load centers. Both use time-synchronized wind and solar energy production and load as inputs. Both examine high renewable energy penetration scenarios in the future.

  4. High-Throughput Screening for Identification of Blood-Brain Barrier Integrity Enhancers: A Drug Repurposing Opportunity to Rectify Vascular Amyloid Toxicity.

    PubMed

    Qosa, Hisham; Mohamed, Loqman A; Al Rihani, Sweilem B; Batarseh, Yazan S; Duong, Quoc-Viet; Keller, Jeffrey N; Kaddoumi, Amal

    2016-07-01

    The blood-brain barrier (BBB) is a dynamic interface that maintains brain homeostasis and protects it from free entry of chemicals, toxins, and drugs. The barrier function of the BBB is maintained mainly by capillary endothelial cells that physically separate brain from blood. Several neurological diseases, such as Alzheimer's disease (AD), are known to disrupt BBB integrity. In this study, a high-throughput screening (HTS) was developed to identify drugs that rectify/protect BBB integrity from vascular amyloid toxicity associated with AD progression. Assessing Lucifer Yellow permeation across in-vitro BBB model composed from mouse brain endothelial cells (bEnd3) grown on 96-well plate inserts was used to screen 1280 compounds of Sigma LOPAC®1280 library for modulators of bEnd3 monolayer integrity. HTS identified 62 compounds as disruptors, and 50 compounds as enhancers of the endothelial barrier integrity. From these 50 enhancers, 7 FDA approved drugs were identified with EC50 values ranging from 0.76-4.56 μM. Of these 7 drugs, 5 were able to protect bEnd3-based BBB model integrity against amyloid toxicity. Furthermore, to test the translational potential to humans, the 7 drugs were tested for their ability to rectify the disruptive effect of Aβ in the human endothelial cell line hCMEC/D3. Only 3 (etodolac, granisetron, and beclomethasone) out of the 5 effective drugs in the bEnd3-based BBB model demonstrated a promising effect to protect the hCMEC/D3-based BBB model integrity. These drugs are compelling candidates for repurposing as therapeutic agents that could rectify dysfunctional BBB associated with AD. PMID:27392852

  5. Systems integrity in health and aging - an animal model approach

    PubMed Central

    2013-01-01

    Human lifespan is positively correlated with childhood intelligence, as measured by psychometric (IQ) tests. The strength of this correlation is similar to the negative effect that smoking has on the life course. This result suggests that people who perform well on psychometric tests in childhood may remain healthier and live longer. The correlation, however, is debated: is it caused exclusively by social-environmental factors or could it also have a biological component? Biological traits of systems integrity that might result in correlations between brain function and lifespan have been suggested but are not well-established, and it is questioned what useful knowledge can come from understanding such mechanisms. In a recent study, we found a positive correlation between brain function and longevity in honey bees. Honey bees are highly social, but relevant social-environmental factors that contribute to cognition-survival correlations in humans are largely absent from insect colonies. Our results, therefore, suggest a biological explanation for the correlation in the bee. Here, we argue that individual differences in stress handling (coping) mechanisms, which both affect the bees’ performance in tests of brain function and their survival could be a trait of systems integrity. Individual differences in coping are much studied in vertebrates, and several species provide attractive models. Here, we discuss how pigs are an interesting model for studying behavioural, physiological and molecular mechanisms that are recruited during stress and that can drive correlations between health, cognition and longevity traits. By revealing biological factors that make individuals susceptible to stress, it might be possible to alleviate health and longevity disparities in people. PMID:24472488

  6. Systems integrity in health and aging - an animal model approach.

    PubMed

    Oostindjer, Marije; Amdam, Gro V

    2013-01-01

    Human lifespan is positively correlated with childhood intelligence, as measured by psychometric (IQ) tests. The strength of this correlation is similar to the negative effect that smoking has on the life course. This result suggests that people who perform well on psychometric tests in childhood may remain healthier and live longer. The correlation, however, is debated: is it caused exclusively by social-environmental factors or could it also have a biological component? Biological traits of systems integrity that might result in correlations between brain function and lifespan have been suggested but are not well-established, and it is questioned what useful knowledge can come from understanding such mechanisms. In a recent study, we found a positive correlation between brain function and longevity in honey bees. Honey bees are highly social, but relevant social-environmental factors that contribute to cognition-survival correlations in humans are largely absent from insect colonies. Our results, therefore, suggest a biological explanation for the correlation in the bee. Here, we argue that individual differences in stress handling (coping) mechanisms, which both affect the bees' performance in tests of brain function and their survival could be a trait of systems integrity. Individual differences in coping are much studied in vertebrates, and several species provide attractive models. Here, we discuss how pigs are an interesting model for studying behavioural, physiological and molecular mechanisms that are recruited during stress and that can drive correlations between health, cognition and longevity traits. By revealing biological factors that make individuals susceptible to stress, it might be possible to alleviate health and longevity disparities in people. PMID:24472488

  7. Neuroanatomical and morphological trait clusters in the ant genus Pheidole: evidence for modularity and integration in brain structure.

    PubMed

    Ilieş, Iulian; Muscedere, Mario L; Traniello, James F A

    2015-01-01

    A central question in brain evolution concerns how selection has structured neuromorphological variation to generate adaptive behavior. In social insects, brain structures differ between reproductive and sterile castes, and worker behavioral specializations related to morphology, age, and ecology are associated with intra- and interspecific variation in investment in functionally different brain compartments. Workers in the hyperdiverse ant genus Pheidole are morphologically and behaviorally differentiated into minor and major subcastes that exhibit distinct species-typical patterns of brain compartment size variation. We examined integration and modularity in brain organization and its developmental patterning in three ecotypical Pheidole species by analyzing intra- and interspecific morphological and neuroanatomical covariation. Our results identified two trait clusters, the first involving olfaction and social information processing and the second composed of brain regions regulating nonolfactory sensorimotor functions. Patterns of size covariation between brain compartments within subcastes were consistent with levels of behavioral differentiation between minor and major workers. Globally, brains of mature workers were more heterogeneous than brains of newly eclosed workers, suggesting diversified developmental trajectories underscore species- and subcaste-typical brain organization. Variation in brain structure associated with the striking worker polyphenism in our sample of Pheidole appears to originate from initially differentiated brain templates that further diverge through species- and subcaste-specific processes of maturation and behavioral development. PMID:25766867

  8. Markers for blood-brain barrier integrity: how appropriate is Evans blue in the twenty-first century and what are the alternatives?

    PubMed Central

    Saunders, Norman R.; Dziegielewska, Katarzyna M.; Møllgård, Kjeld; Habgood, Mark D.

    2015-01-01

    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 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 of HRP in the mid twentieth-century was an important advance because its reaction product can be visualized at the electron microscopical level, but it also has limitations. Advantages and disadvantages of these markers will be discussed together with a critical evaluation of alternative approaches. There is no single marker suitable for all purposes. A combination of different sized, visualizable dextrans and radiolabeled molecules currently seems to be the most appropriate approach for qualitative and quantitative assessment of barrier integrity. PMID:26578854

  9. Insight into Pre-Clinical Models of Traumatic Brain Injury Using Circulating Brain Damage Biomarkers: Operation Brain Trauma Therapy.

    PubMed

    Mondello, Stefania; Shear, Deborah A; Bramlett, Helen M; Dixon, C Edward; Schmid, Kara E; Dietrich, W Dalton; Wang, Kevin K W; Hayes, Ronald L; Glushakova, Olena; Catania, Michael; Richieri, Steven P; Povlishock, John T; Tortella, Frank C; Kochanek, Patrick M

    2016-03-15

    Operation Brain Trauma Therapy (OBTT) is a multicenter pre-clinical drug screening consortium testing promising therapies for traumatic brain injury (TBI) in three well-established models of TBI in rats--namely, parasagittal fluid percussion injury (FPI), controlled cortical impact (CCI), and penetrating ballistic-like brain injury (PBBI). This article presents unique characterization of these models using histological and behavioral outcomes and novel candidate biomarkers from the first three treatment trials of OBTT. Adult rats underwent CCI, FPI, or PBBI and were treated with vehicle (VEH). Shams underwent all manipulations except trauma. The glial marker glial fibrillary acidic protein (GFAP) and the neuronal marker ubiquitin C-terminal hydrolase (UCH-L1) were measured by enzyme-linked immunosorbent assay in blood at 4 and 24 h, and their delta 24-4 h was calculated for each marker. Comparing sham groups across experiments, no differences were found in the same model. Similarly, comparing TBI + VEH groups across experiments, no differences were found in the same model. GFAP was acutely increased in injured rats in each model, with significant differences in levels and temporal patterns mirrored by significant differences in delta 24-4 h GFAP levels and neuropathological and behavioral outcomes. Circulating GFAP levels at 4 and 24 h were powerful predictors of 21 day contusion volume and tissue loss. UCH-L1 showed similar tendencies, albeit with less robust differences between sham and injury groups. Significant differences were also found comparing shams across the models. Our findings (1) demonstrate that TBI models display specific biomarker profiles, functional deficits, and pathological consequence; (2) support the concept that there are different cellular, molecular, and pathophysiological responses to TBI in each model; and (3) advance our understanding of TBI, providing opportunities for a successful translation and holding promise for theranostic

  10. Computational models to understand decision making and pattern recognition in the insect brain

    PubMed Central

    Mosqueiro, Thiago S.; Huerta, Ramón

    2014-01-01

    Odor stimuli reaching olfactory systems of mammals and insects are characterized by remarkable non-stationary and noisy time series. Their brains have evolved to discriminate subtle changes in odor mixtures and find meaningful variations in complex spatio-temporal patterns. Insects with small brains can effectively solve two computational tasks: identify the presence of an odor type and estimate the concentration levels of the odor. Understanding the learning and decision making processes in the insect brain can not only help us to uncover general principles of information processing in the brain, but it can also provide key insights to artificial chemical sensing. Both olfactory learning and memory are dominantly organized in the Antennal Lobe (AL) and the Mushroom Bodies (MBs). Current computational models yet fail to deliver an integrated picture of the joint computational roles of the AL and MBs. This review intends to provide an integrative overview of the computational literature analyzed in the context of the problem of classification (odor discrimination) and regression (odor concentration estimation), particularly identifying key computational ingredients necessary to solve pattern recognition. PMID:25593793

  11. Integrated Modelling - the next steps (Invited)

    NASA Astrophysics Data System (ADS)

    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

  12. Lateral (Parasagittal) Fluid Percussion Model of Traumatic Brain Injury.

    PubMed

    Van, Ken C; Lyeth, Bruce G

    2016-01-01

    Fluid percussion was first conceptualized in the 1940s and has evolved into one of the leading laboratory methods for studying experimental traumatic brain injury (TBI). Over the decades, fluid percussion has been used in numerous species and today is predominantly applied to the rat. The fluid percussion technique rapidly injects a small volume of fluid, such as isotonic saline, through a circular craniotomy onto the intact dura overlying the brain cortex. In brief, the methods involve surgical production of a circular craniotomy, attachment of a fluid-filled conduit between the dura overlying the cortex and the outlet port of the fluid percussion device. A fluid pulse is then generated by the free-fall of a pendulum striking a piston on the fluid-filled cylinder of the device. The fluid enters the cranium, producing a compression and displacement of the brain parenchyma resulting in a sharp, high magnitude elevation of intracranial pressure that is propagated diffusely through the brain. This results in an immediate and transient period of traumatic unconsciousness as well as a combination of focal and diffuse damage to the brain, which is evident upon histological and behavioral analysis. Numerous studies have demonstrated that the rat fluid percussion model reproduces a wide range of pathological features associated with human TBI. PMID:27604722

  13. Modelling Brain Temperature and Perfusion for Cerebral Cooling

    NASA Astrophysics Data System (ADS)

    Blowers, Stephen; Valluri, Prashant; Marshall, Ian; Andrews, Peter; Harris, Bridget; Thrippleton, Michael

    2015-11-01

    Brain temperature relies heavily on two aspects: i) blood perfusion and porous heat transport through tissue and ii) blood flow and heat transfer through embedded arterial and venous vasculature. Moreover brain temperature cannot be measured directly unless highly invasive surgical procedures are used. A 3D two-phase fluid-porous model for mapping flow and temperature in brain is presented with arterial and venous vessels extracted from MRI scans. Heat generation through metabolism is also included. The model is robust and reveals flow and temperature maps in unprecedented 3D detail. However, the Karmen-Kozeny parameters of the porous (tissue) phase need to be optimised for expected perfusion profiles. In order to optimise the K-K parameters a reduced order two-phase model is developed where 1D vessels are created with a tree generation algorithm embedded inside a 3D porous domain. Results reveal that blood perfusion is a strong function of the porosity distribution in the tissue. We present a qualitative comparison between the simulated perfusion maps and those obtained clinically. We also present results studying the effect of scalp cooling on core brain temperature and preliminary results agree with those observed clinically.

  14. Models to Tailor Brain Stimulation Therapies in Stroke

    PubMed Central

    Plow, E. B.; Sankarasubramanian, V.; Cunningham, D. A.; Potter-Baker, K.; Varnerin, N.; Cohen, L. G.; Sterr, A.; Conforto, A. B.; Machado, A. G.

    2016-01-01

    A great challenge facing stroke rehabilitation is the lack of information on how to derive targeted therapies. As such, techniques once considered promising, such as brain stimulation, have demonstrated mixed efficacy across heterogeneous samples in clinical studies. Here, we explain reasons, citing its one-type-suits-all approach as the primary cause of variable efficacy. We present evidence supporting the role of alternate substrates, which can be targeted instead in patients with greater damage and deficit. Building on this groundwork, this review will also discuss different frameworks on how to tailor brain stimulation therapies. To the best of our knowledge, our report is the first instance that enumerates and compares across theoretical models from upper limb recovery and conditions like aphasia and depression. Here, we explain how different models capture heterogeneity across patients and how they can be used to predict which patients would best respond to what treatments to develop targeted, individualized brain stimulation therapies. Our intent is to weigh pros and cons of testing each type of model so brain stimulation is successfully tailored to maximize upper limb recovery in stroke. PMID:27006833

  15. The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

    PubMed Central

    Falcon, Maria Inez; Riley, Jeffrey D.; Jirsa, Viktor; McIntosh, Anthony R.; Shereen, Ahmed D.; Chen, E. Elinor; Solodkin, Ana

    2015-01-01

    There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual’s brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic

  16. Separate Brain Circuits Support Integrative and Semantic Priming in the Human Language System.

    PubMed

    Feng, Gangyi; Chen, Qi; Zhu, Zude; Wang, Suiping

    2016-07-01

    Semantic priming is a crucial phenomenon to study the organization of semantic memory. A novel type of priming effect, integrative priming, has been identified behaviorally, whereby a prime word facilitates recognition of a target word when the 2 concepts can be combined to form a unitary representation. We used both functional and anatomical imaging approaches to investigate the neural substrates supporting such integrative priming, and compare them with those in semantic priming. Similar behavioral priming effects for both semantic (Bread-Cake) and integrative conditions (Cherry-Cake) were observed when compared with an unrelated condition. However, a clearly dissociated brain response was observed between these 2 types of priming. The semantic-priming effect was localized to the posterior superior temporal and middle temporal gyrus. In contrast, the integrative-priming effect localized to the left anterior inferior frontal gyrus and left anterior temporal cortices. Furthermore, fiber tractography showed that the integrative-priming regions were connected via uncinate fasciculus fiber bundle forming an integrative circuit, whereas the semantic-priming regions connected to the posterior frontal cortex via separated pathways. The results point to dissociable neural pathways underlying the 2 distinct types of priming, illuminating the neural circuitry organization of semantic representation and integration. PMID:26209843

  17. Creating Physical 3D Stereolithograph Models of Brain and Skull

    PubMed Central

    Kelley, Daniel J.; Farhoud, Mohammed; Meyerand, M. Elizabeth; Nelson, David L.; Ramirez, Lincoln F.; Dempsey, Robert J.; Wolf, Alan J.; Alexander, Andrew L.; Davidson, Richard J.

    2007-01-01

    The human brain and skull are three dimensional (3D) anatomical structures with complex surfaces. However, medical images are often two dimensional (2D) and provide incomplete visualization of structural morphology. To overcome this loss in dimension, we developed and validated a freely available, semi-automated pathway to build 3D virtual reality (VR) and hand-held, stereolithograph models. To evaluate whether surface visualization in 3D was more informative than in 2D, undergraduate students (n = 50) used the Gillespie scale to rate 3D VR and physical models of both a living patient-volunteer's brain and the skull of Phineas Gage, a historically famous railroad worker whose misfortune with a projectile tamping iron provided the first evidence of a structure-function relationship in brain. Using our processing pathway, we successfully fabricated human brain and skull replicas and validated that the stereolithograph model preserved the scale of the VR model. Based on the Gillespie ratings, students indicated that the biological utility and quality of visual information at the surface of VR and stereolithograph models were greater than the 2D images from which they were derived. The method we developed is useful to create VR and stereolithograph 3D models from medical images and can be used to model hard or soft tissue in living or preserved specimens. Compared to 2D images, VR and stereolithograph models provide an extra dimension that enhances both the quality of visual information and utility of surface visualization in neuroscience and medicine. PMID:17971879

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

    PubMed

    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. PMID:26834428

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

    PubMed Central

    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. PMID:26834428

  20. Treatment of penetrating brain injury in a rat model using collagen scaffolds incorporating soluble Nogo receptor.

    PubMed

    Elias, Paul Z; Spector, Myron

    2015-02-01

    Injuries and diseases of the central nervous system (CNS) have the potential to cause permanent loss of brain parenchyma, with severe neurological consequences. Cavitary defects in the brain may afford the possibility of treatment with biomaterials that fill the lesion site while delivering therapeutic agents. This study examined the treatment of penetrating brain injury (PBI) in a rat model with collagen biomaterials and a soluble Nogo receptor (sNgR) molecule. sNgR was aimed at neutralizing myelin proteins that hinder axon regeneration by inducing growth cone collapse. Scaffolds containing sNgR were implanted in the brains of adult rats 1 week after injury and analysed 4 weeks or 8 weeks later. Histological analysis revealed that the scaffolds filled the lesion sites, remained intact with open pores and were infiltrated with cells and extracellular matrix. Immunohistochemical staining demonstrated the composition of the cellular infiltrate to include macrophages, astrocytes and vascular endothelial cells. Isolated regions of the scaffold borders showed integration with surrounding viable brain tissue that included neurons and oligodendrocytes. While axon regeneration was not detected in the scaffolds, the cellular infiltration and vascularization of the lesion site demonstrated a modification of the injury environment with implications for regenerative strategies. PMID:23038669

  1. Blood-Brain Barrier Alterations Provide Evidence of Subacute Diaschisis in an Ischemic Stroke Rat Model

    PubMed Central

    Garbuzova-Davis, Svitlana; Rodrigues, Maria C. O.; Hernandez-Ontiveros, Diana G.; Tajiri, Naoki; Frisina-Deyo, Aric; Boffeli, Sean M.; Abraham, Jerry V.; Pabon, Mibel; Wagner, Andrew; Ishikawa, Hiroto; Shinozuka, Kazutaka; Haller, Edward; Sanberg, Paul R.; Kaneko, Yuji; Borlongan, Cesario V.

    2013-01-01

    Background Comprehensive stroke studies reveal diaschisis, a loss of function due to pathological deficits in brain areas remote from initial ischemic lesion. However, blood-brain barrier (BBB) competence in subacute diaschisis is uncertain. The present study investigated subacute diaschisis in a focal ischemic stroke rat model. Specific focuses were BBB integrity and related pathogenic processes in contralateral brain areas. Methodology/Principal Findings In ipsilateral hemisphere 7 days after transient middle cerebral artery occlusion (tMCAO), significant BBB alterations characterized by large Evans Blue (EB) parenchymal extravasation, autophagosome accumulation, increased reactive astrocytes and activated microglia, demyelinization, and neuronal damage were detected in the striatum, motor and somatosensory cortices. Vascular damage identified by ultrastuctural and immunohistochemical analyses also occurred in the contralateral hemisphere. In contralateral striatum and motor cortex, major ultrastructural BBB changes included: swollen and vacuolated endothelial cells containing numerous autophagosomes, pericyte degeneration, and perivascular edema. Additionally, prominent EB extravasation, increased endothelial autophagosome formation, rampant astrogliosis, activated microglia, widespread neuronal pyknosis and decreased myelin were observed in contralateral striatum, and motor and somatosensory cortices. Conclusions/Significance These results demonstrate focal ischemic stroke-induced pathological disturbances in ipsilateral, as well as in contralateral brain areas, which were shown to be closely associated with BBB breakdown in remote brain microvessels and endothelial autophagosome accumulation. This microvascular damage in subacute phase likely revealed ischemic diaschisis and should be considered in development of treatment strategies for stroke. PMID:23675488

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

    PubMed

    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. Corticonic models of brain mechanisms underlying cognition and intelligence

    NASA Astrophysics Data System (ADS)

    Farhat, Nabil H.

    The concern of this review is brain theory or more specifically, in its first part, a model of the cerebral cortex and the way it: (a) interacts with subcortical regions like the thalamus and the hippocampus to provide higher-level-brain functions that underlie cognition and intelligence, (b) handles and represents dynamical sensory patterns imposed by a constantly changing environment, (c) copes with the enormous number of such patterns encountered in a lifetime by means of dynamic memory that offers an immense number of stimulus-specific attractors for input patterns (stimuli) to select from, (d) selects an attractor through a process of “conjugation” of the input pattern with the dynamics of the thalamo-cortical loop, (e) distinguishes between redundant (structured) and non-redundant (random) inputs that are void of information, (f) can do categorical perception when there is access to vast associative memory laid out in the association cortex with the help of the hippocampus, and (g) makes use of “computation” at the edge of chaos and information driven annealing to achieve all this. Other features and implications of the concepts presented for the design of computational algorithms and machines with brain-like intelligence are also discussed. The material and results presented suggest, that a Parametrically Coupled Logistic Map network (PCLMN) is a minimal model of the thalamo-cortical complex and that marrying such a network to a suitable associative memory with re-entry or feedback forms a useful, albeit, abstract model of a cortical module of the brain that could facilitate building a simple artificial brain. In the second part of the review, the results of numerical simulations and drawn conclusions in the first part are linked to the most directly relevant works and views of other workers. What emerges is a picture of brain dynamics on the mesoscopic and macroscopic scales that gives a glimpse of the nature of the long sought after brain code

  4. Integrated facilities modeling using QUEST and IGRIP

    SciTech Connect

    Davis, K.R.; Haan, E.R.

    1995-08-01

    A QUEST model and associated detailed IGRIP models were developed and used to simulate several workcells in a proposed Plutonium Storage Facility (PSF). The models are being used by team members assigned to the program to improve communication and to assist in evaluating concepts and in performing trade-off studies which will result in recommendations and a final design. The model was designed so that it could be changed easily. The added flexibility techniques used to make changes easily are described in this paper in addition to techniques for integrating the QUEST and IGRIP products. Many of these techniques are generic in nature and can be applied to any modeling endeavor.

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

    PubMed Central

    Sánchez-Ramón, Silvia; Faure, Florence

    2016-01-01

    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. PMID:26869886

  6. Development of a Human Head FE Model and Impact Simulation on the Focal Brain Injury

    NASA Astrophysics Data System (ADS)

    Watanabe, Dai; Yuge, Kohei; Nishimoto, Tetsuya; Murakami, Shigeyuki; Takao, Hiroyuki

    In this paper, a three-dimensional digital human-head model was developed and several dynamic analyses on the head trauma were conducted. This model was built up by the VOXEL approach using 433 slice CT images (512×512 pixels) and made of 1.22 million parallelepiped finite elements with 10 anatomical tissue properties such as scalp, CSF, skull, brain, dura mater and so on. The numerical analyses were conducted using a finite element code the authors have developed. The main features of the code are 1) it is based on the explicit time integration method and 2) it uses the one point integration method to evaluate the equivalent nodal forces with the hourglass control proposed by Flanagan and Belytschko(1) and 3) it utilizes the parallel computation system based on MPI. In order to verify the developed model, the head impact experiment for a cadaver by Nahum et al.(2) was simulated. The calculated results showed good agreement with the experimental ones. A front and rear impact analyses were also performed to discuss on the characteristic measure of the brain injury, in which the von-Mises stress was high in the frontal lobe in both of the analyses because of the large deformations of a frontal cranial base. This result suggests that the von-Mises stress can be a good measure of the brain injury since it is empirically well known that the frontal lobe tends to get injured regardless of the impact positions.

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Comparative Evaluation for Brain Structural Connectivity Approaches: Towards Integrative Neuroinformatics Tool for Epilepsy Clinical Research.

    PubMed

    Yang, Sheng; Tatsuoka, Curtis; Ghosh, Kaushik; Lacuey-Lecumberri, Nuria; Lhatoo, Samden D; Sahoo, Satya S

    2016-01-01

    Recent advances in brain fiber tractography algorithms and diffusion Magnetic Resonance Imaging (MRI) data collection techniques are providing new approaches to study brain white matter connectivity, which play an important role in complex neurological disorders such as epilepsy. Epilepsy affects approximately 50 million persons worldwide and it is often described as a disorder of the cortical network organization. There is growing recognition of the need to better understand the role of brain structural networks in the onset and propagation of seizures in epilepsy using high resolution non-invasive imaging technologies. In this paper, we perform a comparative evaluation of two techniques to compute structural connectivity, namely probabilistic fiber tractography and statistics derived from fractional anisotropy (FA), using diffusion MRI data from a patient with rare case of medically intractable insular epilepsy. The results of our evaluation demonstrate that probabilistic fiber tractography provides a more accurate map of structural connectivity and may help address inherent complexities of neural fiber layout in the brain, such as fiber crossings. This work provides an initial result towards building an integrative informatics tool for neuroscience that can be used to accurately characterize the role of fiber tract connectivity in neurological disorders such as epilepsy. PMID:27570685

  9. Comparative Evaluation for Brain Structural Connectivity Approaches: Towards Integrative Neuroinformatics Tool for Epilepsy Clinical Research

    PubMed Central

    Yang, Sheng; Tatsuoka, Curtis; Ghosh, Kaushik; Lacuey-Lecumberri, Nuria; Lhatoo, Samden D.; Sahoo, Satya S.

    2016-01-01

    Recent advances in brain fiber tractography algorithms and diffusion Magnetic Resonance Imaging (MRI) data collection techniques are providing new approaches to study brain white matter connectivity, which play an important role in complex neurological disorders such as epilepsy. Epilepsy affects approximately 50 million persons worldwide and it is often described as a disorder of the cortical network organization. There is growing recognition of the need to better understand the role of brain structural networks in the onset and propagation of seizures in epilepsy using high resolution non-invasive imaging technologies. In this paper, we perform a comparative evaluation of two techniques to compute structural connectivity, namely probabilistic fiber tractography and statistics derived from fractional anisotropy (FA), using diffusion MRI data from a patient with rare case of medically intractable insular epilepsy. The results of our evaluation demonstrate that probabilistic fiber tractography provides a more accurate map of structural connectivity and may help address inherent complexities of neural fiber layout in the brain, such as fiber crossings. This work provides an initial result towards building an integrative informatics tool for neuroscience that can be used to accurately characterize the role of fiber tract connectivity in neurological disorders such as epilepsy. PMID:27570685

  10. Neuroteratology and Animal Modeling of Brain Disorders.

    PubMed

    Archer, Trevor; Kostrzewa, Richard M

    2016-01-01

    Over the past 60 years, a large number of selective neurotoxins were discovered and developed, making it possible to animal-model a broad range of human neuropsychiatric and neurodevelopmental disorders. In this paper, we highlight those neurotoxins that are most commonly used as neuroteratologic agents, to either produce lifelong destruction of neurons of a particular phenotype, or a group of neurons linked by a specific class of transporter proteins (i.e., dopamine transporter) or body of receptors for a specific neurotransmitter (i.e., NMDA class of glutamate receptors). Actions of a range of neurotoxins are described: 6-hydroxydopamine (6-OHDA), 6-hydroxydopa, DSP-4, MPTP, methamphetamine, IgG-saporin, domoate, NMDA receptor antagonists, and valproate. Their neuroteratologic features are outlined, as well as those of nerve growth factor, epidermal growth factor, and that of stress. The value of each of these neurotoxins in animal modeling of human neurologic, neurodegenerative, and neuropsychiatric disorders is discussed in terms of the respective value as well as limitations of the derived animal model. Neuroteratologic agents have proven to be of immense importance for understanding how associated neural systems in human neural disorders may be better targeted by new therapeutic agents. PMID:26857462

  11. The cumulative effect of genetic polymorphisms on depression and brain structural integrity.

    PubMed

    Kostic, Milutin; Canu, Elisa; Agosta, Federica; Munjiza, Ana; Novakovic, Ivana; Dobricic, Valerija; Maria Ferraro, Pilar; Miler Jerkovic, Vera; Pekmezovic, Tatjana; Lecic Tosevski, Dusica; Filippi, Massimo

    2016-06-01

    In major depressive disorder (MDD), the need to study multiple-gene effect on brain structure is emerging. Our aim was to assess the effect of accumulation of specific SERT, BDNF and COMT gene functional polymorphisms on brain structure in MDD patients. Seventy-seven MDD patients and 66 controls underwent a clinical assessment, genetic testing and MRI scan. Compared with controls, patients were more BDNF-Val homozygotes, COMT-Met carriers and SERT-L' carriers. Thus, subjects were split into three groups: 1. High-frequency susceptibility polymorphism group (hfSP, subjects with all three SPs); 2. Intermediate-frequency SP group (ifSP, two SPs); and 3. Low-frequency SP group (lfSP, one/none SP). Cortical thickness, volumetry of hippocampus, amygdala and subcortical structures, and white matter (WM) tract integrity were assessed. Compared to controls, hfSP patients showed thinning of the middle frontal cortex bilaterally, left frontal pole, and right lateral occipital cortex, and smaller hippocampal volume bilaterally; and both hfSP and lfSP patient groups showed thinning of the left inferior parietal cortex and reduced WM integrity of the corpus callosum. Compared to patients, hfSP controls showed greater integrity of the fronto-occipital cortices and corpus callosum. We showed that cortical prefrontal and occipital damage of MDD patients is modulated by the SP accumulation, while damage to the parietal cortex and corpus callosum seem to be independent of genetic accumulation. HfSP controls may experience protective mechanisms leading to a preserved integrity of critical cortical and WM regions. Investigating the effect of multiple genes is promising to understand the pathological mechanisms underlying MDD. Hum Brain Mapp 37:2173-2184, 2016. © 2016 Wiley Periodicals, Inc. PMID:26956059

  12. CTBT integrated verification system evaluation model supplement

    SciTech Connect

    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.

  13. Data and Model Integration Promoting Interdisciplinarity

    NASA Astrophysics Data System (ADS)

    Koike, T.

    2014-12-01

    It is very difficult to reflect accumulated subsystem knowledge into holistic knowledge. Knowledge about a whole system can rarely be introduced into a targeted subsystem. In many cases, knowledge in one discipline is inapplicable to other disciplines. We are far from resolving cross-disciplinary issues. It is critically important to establish interdisciplinarity so that scientific knowledge can transcend disciplines. We need to share information and develop knowledge interlinkages by building models and exchanging tools. We need to tackle a large increase in the volume and diversity of data from observing the Earth. The volume of data stored has exponentially increased. Previously, almost all of the large-volume data came from satellites, but model outputs occupy the largest volume in general. To address the large diversity of data, we should develop an ontology system for technical and geographical terms in coupling with a metadata design according to international standards. In collaboration between Earth environment scientists and IT group, we should accelerate data archiving by including data loading, quality checking and metadata registration, and enrich data-searching capability. DIAS also enables us to perform integrated research and realize interdisciplinarity. For example, climate change should be addressed in collaboration between the climate models, integrated assessment models including energy, economy, agriculture, health, and the models of adaptation, vulnerability, and human settlement and infrastructure. These models identify water as central to these systems. If a water expert can develop an interrelated system including each component, the integrated crisis can be addressed by collaboration with various disciplines. To realize this purpose, we are developing a water-related data- and model-integration system called a water cycle integrator (WCI).

  14. Depression, Stress, and Anhedonia: Toward a Synthesis and Integrated Model

    PubMed Central

    Pizzagalli, Diego A.

    2014-01-01

    Depression is a significant public health problem, but its etiology and pathophysiology remain poorly understood. Such incomplete understanding likely arises from the fact that depression encompasses a heterogeneous set of disorders. To overcome these limitations, renewed interest in intermediate phenotypes (endophenotypes) has resurfaced, and anhedonia has emerged as one of the most promising endophenotypes of depression. Here, a heuristic model is presented postulating that anhedonia arises from dysfunctional interactions between stress and brain reward systems. To this end, we review and integrate three bodies of independent literature investigating the role of (1) anhedonia, (2) dopamine, and (3) stress in depression. In a fourth section, we summarize animal data indicating that stress negatively affect mesocorticolimbic dopaminergic pathways critically implicated in incentive motivation and reinforcement learning. In the last section, we provide a synthesis of these four literatures, present initial evidence consistent with our model, and discuss directions for future research. PMID:24471371

  15. Verbal Neuropsychological Functions in Aphasia: An Integrative Model.

    PubMed

    Vigliecca, Nora Silvana; Báez, Sandra

    2015-12-01

    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 Aphasia Evaluation was used. A sample of 65 patients with left cerebral lesions, and two supplementary samples comprising 35 patients with right cerebral lesions and 30 healthy participants were studied. A model encompassing an all inclusive verbal organizer and two successive organizers was validated. The two last organizers were: three factors of comprehension, expression and a "complementary" verbal factor which included praxia, attention, and memory; followed by the individual (and correlated) factors of auditory comprehension, repetition, naming, speech, reading, writing, and the "complementary" factor. By following this approach all the patients fall inside the classification system; consequently, theoretical improvement is guaranteed. PMID:25168953

  16. Self-Organized Criticality Model for Brain Plasticity

    NASA Astrophysics Data System (ADS)

    de Arcangelis, Lucilla; Perrone-Capano, Carla; Herrmann, Hans J.

    2006-01-01

    Networks of living neurons exhibit an avalanche mode of activity, experimentally found in organotypic cultures. Here we present a model that is based on self-organized criticality and takes into account brain plasticity, which is able to reproduce the spectrum of electroencephalograms (EEG). The model consists of an electrical network with threshold firing and activity-dependent synapse strengths. The system exhibits an avalanche activity in a power-law distribution. The analysis of the power spectra of the electrical signal reproduces very robustly the power-law behavior with the exponent 0.8, experimentally measured in EEG spectra. The same value of the exponent is found on small-world lattices and for leaky neurons, indicating that universality holds for a wide class of brain models.

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

    PubMed

    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. PMID:25725349

  18. Endocannabinoid Degradation Inhibition Improves Neurobehavioral Function, Blood–Brain Barrier Integrity, and Neuroinflammation following Mild Traumatic Brain Injury

    PubMed Central

    Katz, Paige S.; Sulzer, Jesse K.; Impastato, Renata A.; Teng, Sophie X.; Rogers, Emily K.

    2015-01-01

    Abstract Traumatic brain injury (TBI) is an increasingly frequent and poorly understood condition lacking effective therapeutic strategies. Inflammation and oxidative stress (OS) are critical components of injury, and targeted interventions to reduce their contribution to injury should improve neurobehavioral recovery and outcomes. Recent evidence reveals potential protective, yet short-lived, effects of the endocannabinoids (ECs), 2-arachidonoyl glycerol (2-AG) and N-arachidonoyl-ethanolamine (AEA), on neuroinflammatory and OS processes after TBI. The aim of this study was to determine whether EC degradation inhibition after TBI would improve neurobehavioral recovery by reducing inflammatory and oxidative damage. Adult male Sprague-Dawley rats underwent a 5-mm left lateral craniotomy, and TBI was induced by lateral fluid percussion. TBI produced apnea (17±5 sec) and a delayed righting reflex (479±21 sec). Thirty minutes post-TBI, rats were randomized to receive intraperitoneal injections of vehicle (alcohol, emulphor, and saline; 1:1:18) or a selective inhibitor of 2-AG (JZL184, 16 mg/kg) or AEA (URB597, 0.3 mg/kg) degradation. At 24 h post-TBI, animals showed significant neurological and -behavioral impairment as well as disruption of blood–brain barrier (BBB) integrity. Improved neurological and -behavioral function was observed in JZL184-treated animals. BBB integrity was protected in both JZL184- and URB597-treated animals. No significant differences in ipsilateral cortex messenger RNA expression of interleukin (IL)-1β, IL-6, chemokine (C-C motif) ligand 2, tumor necrosis factor alpha, cyclooxygenase 2 (COX2), or nicotinamide adenine dinucleotide phosphate oxidase (NOX2) and protein expression of COX2 or NOX2 were observed across experimental groups. Astrocyte and microglia activation was significantly increased post-TBI, and treatment with JZL184 or URB597 blocked activation of both cell types. These findings suggest that EC degradation

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

    PubMed

    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). PMID:26347228

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

    PubMed

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

    2011-01-01

    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

  1. Lateral Fluid Percussion: Model of Traumatic Brain Injury in Mice

    PubMed Central

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

    2011-01-01

    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 mass on the closed

  2. Quiver gauge theories and integrable lattice models

    NASA Astrophysics Data System (ADS)

    Yagi, Junya

    2015-10-01

    We discuss connections between certain classes of supersymmetric quiver gauge theories and integrable lattice models from the point of view of topological quantum field theories (TQFTs). The relevant classes include 4d N=1 theories known as brane box and brane tilling models, 3d N=2 and 2d N=(2,2) theories obtained from them by compactification, and 2d N=(0,2) theories closely related to these theories. We argue that their supersymmetric indices carry structures of TQFTs equipped with line operators, and as a consequence, are equal to the partition functions of lattice models. The integrability of these models follows from the existence of extra dimension in the TQFTs, which emerges after the theories are embedded in M-theory. The Yang-Baxter equation expresses the invariance of supersymmetric indices under Seiberg duality and its lower-dimensional analogs.

  3. Which coordinate system for modelling path integration?

    PubMed

    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. PMID:19962387

  4. Integration of Dynamic Models in Range Operations

    NASA Technical Reports Server (NTRS)

    Bardina, Jorge; Thirumalainambi, Rajkumar

    2004-01-01

    This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

  5. Fingernail Injuries and NASA's Integrated Medical Model

    NASA Technical Reports Server (NTRS)

    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!

  6. Rethinking School Bullying: Towards an Integrated Model

    ERIC Educational Resources Information Center

    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…

  7. International Summit on Integrated Environmental Modeling

    EPA Science Inventory

    This report describes the International Summit on Integrated Environmental Modeling (IEM), held in Washington, DC 7th-9th December 2010. The meeting brought together 57 scientists and managers from leading US and European government and non-governmental organizations, universitie...

  8. Mesh Smoothing Algorithm Applied to a Finite Element Model of the Brain for Improved Brain-Skull Interface.

    PubMed

    Kelley, Mireille E; Miller, Logan E; Urban, Jillian E; Stitzel, Joel D

    2015-01-01

    The brain-skull interface plays an important role in the strain and pressure response of the brain due to impact. In this study, a finite element (FE) model was developed from a brain atlas, representing an adult brain, by converting each 1mm isotropic voxel into a single element of the same size using a custom code developed in MATLAB. This model includes the brain (combined cerebrum and cerebellum), cerebrospinal fluid (CSF), ventricles, and a rigid skull. A voxel-based approach to develop a FE model causes the outer surface of each part to be stair-stepped, which may affect the stress and strain measurements at interfaces between parts. To improve the interaction between the skull, CSF, and brain surfaces, a previously developed mesh smoothing algorithm based on a Laplacian non-shrinking smoothing algorithm was applied to the FE model. This algorithm not only applies smoothing to the surface of the model, but also to the interfaces between the brain, CSF, and skull, while preserving volume and element quality. Warpage, jacobian, aspect ratio, and skew were evaluated and reveal that >99% of the elements retain good element quality. Future work includes implementation of contact definitions to accurately represent the brain-skull interface and to ultimately better understand and predict head injury. PMID:25996716

  9. Organization, Maturation, and Plasticity of Multisensory Integration: Insights from Computational Modeling Studies

    PubMed Central

    Cuppini, Cristiano; Magosso, Elisa; Ursino, Mauro

    2011-01-01

    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 modeling 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 behavioral 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. PMID:21687448

  10. EPA EXPOSURE MODELS LIBRARY AND INTEGRATED MODEL EVALUATION SYSTEM

    EPA Science Inventory

    The third edition of the U.S. Environmental Protection Agencys (EPA) EML/IMES (Exposure Models Library and Integrated Model Evaluation System) on CD-ROM is now available. The purpose of the disc is to provide a compact and efficient means to distribute exposure models, documentat...

  11. Normal brain ageing: models and mechanisms

    PubMed Central

    Toescu, Emil C

    2005-01-01

    Normal ageing is associated with a degree of decline in a number of cognitive functions. Apart from the issues raised by the current attempts to expand the lifespan, understanding the mechanisms and the detailed metabolic interactions involved in the process of normal neuronal ageing continues to be a challenge. One model, supported by a significant amount of experimental evidence, views the cellular ageing as a metabolic state characterized by an altered function of the metabolic triad: mitochondria–reactive oxygen species (ROS)–intracellular Ca2+. The perturbation in the relationship between the members of this metabolic triad generate a state of decreased homeostatic reserve, in which the aged neurons could maintain adequate function during normal activity, as demonstrated by the fact that normal ageing is not associated with widespread neuronal loss, but become increasingly vulnerable to the effects of excessive metabolic loads, usually associated with trauma, ischaemia or neurodegenerative processes. This review will concentrate on some of the evidence showing altered mitochondrial function with ageing and also discuss some of the functional consequences that would result from such events, such as alterations in mitochondrial Ca2+ homeostasis, ATP production and generation of ROS. PMID:16321805

  12. Associations between brain white matter integrity and disease severity in obstructive sleep apnea.

    PubMed

    Tummala, Sudhakar; Roy, Bhaswati; Park, Bumhee; Kang, Daniel W; Woo, Mary A; Harper, Ronald M; Kumar, Rajesh

    2016-10-01

    Obstructive sleep apnea (OSA) is characterized by recurrent upper airway blockage, with continued diaphragmatic efforts to breathe during sleep. Brain structural changes in OSA appear in various regions, including white matter sites that mediate autonomic, mood, cognitive, and respiratory control. However, the relationships between brain white matter changes and disease severity in OSA are unclear. This study examines associations between an index of tissue integrity, magnetization transfer (MT) ratio values (which show MT between free and proton pools associated with tissue membranes and macromolecules), and disease severity (apnea-hypopnea index [AHI]) in OSA subjects. We collected whole-brain MT imaging data from 19 newly diagnosed, treatment-naïve OSA subjects (50.4 ± 8.6 years of age, 13 males, AHI 39.7 ± 24.3 events/hr], using a 3.0-Tesla MRI scanner. With these data, whole-brain MT ratio maps were calculated, normalized to common space, smoothed, and correlated with AHI scores by using partial correlation analyses (covariates, age and gender; P < 0.005). Multiple brain sites in OSA subjects, including superior and inferior frontal regions, ventral medial prefrontal cortex and nearby white matter, midfrontal white matter, insula, cingulate and cingulum bundle, internal and external capsules, caudate nuclei and putamen, basal forebrain, hypothalamus, corpus callosum, and temporal regions, showed principally lateralized negative correlations (P < 0.005). These regions showed significant correlations even with correction for multiple comparisons (cluster-level, family-wise error, P < 0.05), except for a few superior frontal areas. Predominantly negative correlations emerged between local MT values and OSA disease severity, indicating potential usefulness of MT imaging for examining the OSA condition. These findings indicate that OSA severity plays a significant role in white matter injury. © 2016 Wiley Periodicals, Inc. PMID:27315771

  13. Toward "optimal" integration of terrestrial biosphere models

    NASA Astrophysics Data System (ADS)

    Schwalm, Christopher R.; Huntzinger, Deborah N.; Fisher, Joshua B.; Michalak, Anna M.; Bowman, Kevin; Ciais, Philippe; Cook, Robert; El-Masri, Bassil; Hayes, Daniel; Huang, Maoyi; Ito, Akihiko; Jain, Atul; King, Anthony W.; Lei, Huimin; Liu, Junjie; Lu, Chaoqun; Mao, Jiafu; Peng, Shushi; Poulter, Benjamin; Ricciuto, Daniel; Schaefer, Kevin; Shi, Xiaoying; Tao, Bo; Tian, Hanqin; Wang, Weile; Wei, Yaxing; Yang, Jia; Zeng, Ning

    2015-06-01

    Multimodel ensembles (MME) are commonplace in Earth system modeling. Here we perform MME integration using a 10-member ensemble of terrestrial biosphere models (TBMs) from the Multiscale synthesis and Terrestrial Model Intercomparison Project (MsTMIP). We contrast optimal (skill based for present-day carbon cycling) versus naïve ("one model-one vote") integration. MsTMIP optimal and naïve mean land sink strength estimates (-1.16 versus -1.15 Pg C per annum respectively) are statistically indistinguishable. This holds also for grid cell values and extends to gross uptake, biomass, and net ecosystem productivity. TBM skill is similarly indistinguishable. The added complexity of skill-based integration does not materially change MME values. This suggests that carbon metabolism has predictability limits and/or that all models and references are misspecified. Resolving this issue requires addressing specific uncertainty types (initial conditions, structure, and references) and a change in model development paradigms currently dominant in the TBM community.

  14. Controlled Cortical Impact Model for Traumatic Brain Injury

    PubMed Central

    Romine, Jennifer; Gao, Xiang; Chen, Jinhui

    2014-01-01

    Every year over a million Americans suffer a traumatic brain injury (TBI). Combined with the incidence of TBIs worldwide, the physical, emotional, social, and economical effects are staggering. Therefore, further research into the effects of TBI and effective treatments is necessary. The controlled cortical impact (CCI) model induces traumatic brain injuries ranging from mild to severe. This method uses a rigid impactor to deliver mechanical energy to an intact dura exposed following a craniectomy. Impact is made under precise parameters at a set velocity to achieve a pre-determined deformation depth. Although other TBI models, such as weight drop and fluid percussion, exist, CCI is more accurate, easier to control, and most importantly, produces traumatic brain injuries similar to those seen in humans. However, no TBI model is currently able to reproduce pathological changes identical to those seen in human patients. The CCI model allows investigation into the short-term and long-term effects of TBI, such as neuronal death, memory deficits, and cerebral edema, as well as potential therapeutic treatments for TBI. PMID:25145417

  15. Avoiding Boltzmann Brain domination in holographic dark energy models

    NASA Astrophysics Data System (ADS)

    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.

  16. Controlled cortical impact model for traumatic brain injury.

    PubMed

    Romine, Jennifer; Gao, Xiang; Chen, Jinhui

    2014-01-01

    Every year over a million Americans suffer a traumatic brain injury (TBI). Combined with the incidence of TBIs worldwide, the physical, emotional, social, and economical effects are staggering. Therefore, further research into the effects of TBI and effective treatments is necessary. The controlled cortical impact (CCI) model induces traumatic brain injuries ranging from mild to severe. This method uses a rigid impactor to deliver mechanical energy to an intact dura exposed following a craniectomy. Impact is made under precise parameters at a set velocity to achieve a pre-determined deformation depth. Although other TBI models, such as weight drop and fluid percussion, exist, CCI is more accurate, easier to control, and most importantly, produces traumatic brain injuries similar to those seen in humans. However, no TBI model is currently able to reproduce pathological changes identical to those seen in human patients. The CCI model allows investigation into the short-term and long-term effects of TBI, such as neuronal death, memory deficits, and cerebral edema, as well as potential therapeutic treatments for TBI. PMID:25145417

  17. A Novel Mouse Model of Penetrating Brain Injury

    PubMed Central

    Cernak, Ibolja; Wing, Ian D.; Davidsson, Johan; Plantman, Stefan

    2014-01-01

    Penetrating traumatic brain injury (pTBI) has been difficult to model in small laboratory animals, such as rats or mice. Previously, we have established a non-fatal, rat model for pTBI using a modified air-rifle that accelerates a pellet, which hits a small probe that then penetrates the experimental animal’s brain. Knockout and transgenic strains of mice offer attractive tools to study biological reactions induced by TBI. Hence, in the present study, we adapted and modified our model to be used with mice. The technical characterization of the impact device included depth and speed of impact, as well as dimensions of the temporary cavity formed in a brain surrogate material after impact. Biologically, we have focused on three distinct levels of severity (mild, moderate, and severe), and characterized the acute phase response to injury in terms of tissue destruction, neural degeneration, and gliosis. Functional outcome was assessed by measuring bodyweight and motor performance on rotarod. The results showed that this model is capable of reproducing major morphological and neurological changes of pTBI; as such, we recommend its utilization in research studies aiming to unravel the biological events underlying injury and regeneration after pTBI. PMID:25374559

  18. Integrating sensorimotor systems in a robot model of cricket behavior

    NASA Astrophysics Data System (ADS)

    Webb, Barbara H.; Harrison, Reid R.

    2000-10-01

    The mechanisms by which animals manage sensorimotor integration and coordination of different behaviors can be investigated in robot models. In previous work the first author has build a robot that localizes sound based on close modeling of the auditory and neural system in the cricket. It is known that the cricket combines its response to sound with other sensorimotor activities such as an optomotor reflex and reactions to mechanical stimulation for the antennae and cerci. Behavioral evidence suggests some ways these behaviors may be integrated. We have tested the addition of an optomotor response, using an analog VLSI circuit developed by the second author, to the sound localizing behavior and have shown that it can, as in the cricket, improve the directness of the robot's path to sound. In particular it substantially improves behavior when the robot is subject to a motor disturbance. Our aim is to better understand how the insect brain functions in controlling complex combinations of behavior, with the hope that this will also suggest novel mechanisms for sensory integration on robots.

  19. Relationship between the Whole Brain Creativity Model and Kolb's experiential learning model.

    PubMed

    Potgieter, E

    1999-12-01

    The aim of this article is to illustrate the relation between the cognitive styles in Kolb's experiential learning model and dominance in brain functioning. A descriptive analytical study of the literature on creativity and the development of creative thinking, explored various theories and definitions of creativity, and the nature of creative learning. Congruences between cognitive styles and the four quadrants of the Whole Brain Model were detected. This article focuses specifically on Kolb's cognitive styles in relation to the Whole Brain Model and the implications thereof for nursing education. PMID:11051927

  20. [Integrated model system for environmental policy analysis].

    PubMed

    Jiang, Lin

    2006-05-01

    An integrated model system for environmental policy analysis is built up with a Computable General Equilibrium (CGE) model as a core model, which is linked with an environmental model, air dispersion model, and health effect model (exposure-response functions) in an explicit way, therefore the model system is capable of evaluating the effects of policies on environment, health and economy and their interactions comprehensively. This method is used to analyze the effects of Beijing presumptive (energy) taxes on air quality, health, welfare and economic growth, and the conclusion is that sole presumptive taxes may slow down the economic growth, but the presumptive taxes with green tax reform can promote Beijing sustainable development. PMID:16850855

  1. Animal Models and Integrated Nested Laplace Approximations

    PubMed Central

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

    2013-01-01

    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. PMID:23708299

  2. Self-organization in a simple brain model

    SciTech Connect

    Stassinopoulos, D.; Bak, P.; Alstroem, P.

    1994-03-10

    Simulations on a simple model of the brain are presented. The model consists of a set of randomly connected neurons. Inputs and outputs are also connected randomly to a subset of neurons. For each input there is a set of output neurons which must fire in order to achieve success. A signal giving information as to whether or not the action was successful is fed back to the brain from the environment. The connections between firing neurons are strengthened or weakened according to whether or not the action was successful. The system learns, through a self-organization process, to react intelligently to input signals, i.e. it learns to quickly select the correct output for each input. If part of the network is damaged, the system relearns the correct response after a training period.

  3. Neurocomputational models of the remote effects of focal brain damage.

    PubMed

    Reggia, James A

    2004-11-01

    Sudden localized brain damage, such as occurs in stroke, produces neurological deficits directly attributable to the damaged site. In addition, other clinical deficits occur due to secondary "remote" effects that functionally impair the remaining intact brain regions (e.g., due to their sudden disconnection from the damaged area), a phenomenon known as diaschisis. The underlying mechanisms of these remote effects, particularly those involving interactions between the left and right cerebral hemispheres, have proven somewhat difficult to understand in the context of current theories of hemispheric specialization. This article describes some recent neurocomputational models done in the author's research group that try to explain diaschisis qualitatively. These studies show that both specialization and diaschisis can be accounted for with a single model of hemispheric interactions. Further, the results suggest that left-right subcortical influences may be much more important in influencing hemispheric specialization than is generally recognized. PMID:15564108

  4. Developing better and more valid animal models of brain disorders.

    PubMed

    Stewart, Adam Michael; Kalueff, Allan V

    2015-01-01

    Valid sensitive animal models are crucial for understanding the pathobiology of complex human disorders, such as anxiety, autism, depression and schizophrenia, which all have the 'spectrum' nature. Discussing new important strategic directions of research in this field, here we focus i) on cross-species validation of animal models, ii) ensuring their population (external) validity, and iii) the need to target the interplay between multiple disordered domains. We note that optimal animal models of brain disorders should target evolutionary conserved 'core' traits/domains and specifically mimic the clinically relevant inter-relationships between these domains. PMID:24384129

  5. Brain Arteriovenous Malformation Modeling, Pathogenesis and Novel Therapeutic Targets

    PubMed Central

    Chen, Wanqiu; Choi, Eun-Jung; McDougall, Cameron M.; Su, Hua

    2014-01-01

    Patients harboring brain arteriovenous malformation (bAVM) are at life-threatening risk of rupture and intracranial hemorrhage (ICH). The pathogenesis of bAVM has not been completely understood. Current treatment options are invasive and ≈ 20% of patients are not offered interventional therapy because of excessive treatment risk. There are no specific medical therapies to treat bAVMs. The lack of validated animal models has been an obstacle for testing hypotheses of bAVM pathogenesis and testing new therapies. In this review, we summarize bAVM model development; and bAVM pathogenesis and potential therapeutic targets that have been identified during model development. PMID:24723256

  6. Integrated assessment models of global climate change

    SciTech Connect

    Parson, E.A.; Fisher-Vanden, K.

    1997-12-31

    The authors review recent work in the integrated assessment modeling of global climate change. This field has grown rapidly since 1990. Integrated assessment models seek to combine knowledge from multiple disciplines in formal integrated representations; inform policy-making, structure knowledge, and prioritize key uncertainties; and advance knowledge of broad system linkages and feedbacks, particularly between socio-economic and bio-physical processes. They may combine simplified representations of the socio-economic determinants of greenhouse gas emissions, the atmosphere and oceans, impacts on human activities and ecosystems, and potential policies and responses. The authors summarize current projects, grouping them according to whether they emphasize the dynamics of emissions control and optimal policy-making, uncertainty, or spatial detail. They review the few significant insights that have been claimed from work to date and identify important challenges for integrated assessment modeling in its relationships to disciplinary knowledge and to broader assessment seeking to inform policy- and decision-making. 192 refs., 2 figs.

  7. Subsurface integration with Shared Earth Models

    SciTech Connect

    Gawith, D.; Gutteridge, P.

    1995-08-01

    The seismic response of a reservoir is a function of rock type, geometry and pore fluids; 3D seismic data therefore contains information on the nature of reservoir rocks, the geometry of flow units, and the distribution of gas, oil and water. Proper integration of seismic interpretation and modelling with static reservoir description and flow simulation will make the most of the information available and will lead to optimal prediction of reservoir performance. One approach to this integration is through the construction of detailed numerical models of reservoir geology and properties; if the models are sufficiently accurate then both seismic response and dynamic behaviour calculated from them will match closely the behaviour of the actual reservoir. This means that the reservoir engineer`s interpretation of dynamic data can be made in a geological context and that both static and dynamic models can be kept fully consistent with the information held in seismic data. These detailed models, combining geology, geophysics and reservoir properties, are known as Shared Earth Models. We show examples of detailed geological modelling made to honour geophysical observations, and of the use of seismic modelling to support reservoir engineering.

  8. Explicit stress integration of complex soil models

    NASA Astrophysics Data System (ADS)

    Zhao, Jidong; Sheng, Daichao; Rouainia, M.; Sloan, Scott W.

    2005-10-01

    In this paper, two complex critical-state models are implemented in a displacement finite element code. The two models are used for structured clays and sands, and are characterized by multiple yield surfaces, plastic yielding within the yield surface, and complex kinematic and isotropic hardening laws. The consistent tangent operators - which lead to a quadratic convergence when used in a fully implicit algorithm - are difficult to derive or may even not exist. The stress integration scheme used in this paper is based on the explicit Euler method with automatic substepping and error control. This scheme employs the classical elastoplastic stiffness matrix and requires only the first derivatives of the yield function and plastic potential. This explicit scheme is used to integrate the two complex critical-state models - the sub/super-loading surfaces model (SSLSM) and the kinematic hardening structure model (KHSM). Various boundary-value problems are then analysed. The results for the two models are compared with each other, as well with those from standard Cam-clay models. Accuracy and efficiency of the scheme used for the complex models are also investigated. Copyright

  9. Fast associative memory + slow neural circuitry = the computational model of the brain.

    NASA Astrophysics Data System (ADS)

    Berkovich, Simon; Berkovich, Efraim; Lapir, Gennady

    1997-08-01

    We propose a computational model of the brain based on a fast associative memory and relatively slow neural processors. In this model, processing time is expensive but memory access is not, and therefore most algorithmic tasks would be accomplished by using large look-up tables as opposed to calculating. The essential feature of an associative memory in this context (characteristic for a holographic type memory) is that it works without an explicit mechanism for resolution of multiple responses. As a result, the slow neuronal processing elements, overwhelmed by the flow of information, operate as a set of templates for ranking of the retrieved information. This structure addresses the primary controversy in the brain architecture: distributed organization of memory vs. localization of processing centers. This computational model offers an intriguing explanation of many of the paradoxical features in the brain architecture, such as integration of sensors (through DMA mechanism), subliminal perception, universality of software, interrupts, fault-tolerance, certain bizarre possibilities for rapid arithmetics etc. In conventional computer science the presented type of a computational model did not attract attention as it goes against the technological grain by using a working memory faster than processing elements.

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

    PubMed

    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; Brodin, Birger

    2016-05-01

    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

  11. Optimizing experimental design for comparing models of brain function.

    PubMed

    Daunizeau, Jean; Preuschoff, Kerstin; Friston, Karl; Stephan, Klaas

    2011-11-01

    This article presents the first attempt to formalize the optimization of experimental design with the aim of comparing models of brain function based on neuroimaging data. We demonstrate our approach in the context of Dynamic Causal Modelling (DCM), which relates experimental manipulations to observed network dynamics (via hidden neuronal states) and provides an inference framework for selecting among candidate models. Here, we show how to optimize the sensitivity of model selection by choosing among experimental designs according to their respective model selection accuracy. Using Bayesian decision theory, we (i) derive the Laplace-Chernoff risk for model selection, (ii) disclose its relationship with classical design optimality criteria and (iii) assess its sensitivity to basic modelling assumptions. We then evaluate the approach when identifying brain networks using DCM. Monte-Carlo simulations and empirical analyses of fMRI data from a simple bimanual motor task in humans serve to demonstrate the relationship between network identification and the optimal experimental design. For example, we show that deciding whether there is a feedback connection requires shorter epoch durations, relative to asking whether there is experimentally induced change in a connection that is known to be present. Finally, we discuss limitations and potential extensions of this work. PMID:22125485

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

    PubMed Central

    Oliveira, Gonçalo A.; Oliveira, Rui F.

    2014-01-01

    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 behavior 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 behavior requires its analysis at both proximate (physiology, ontogeny) and ultimate (ecology, evolution) levels. PMID:25100938

  13. Combined Neurotrauma Models: Experimental Models Combining Traumatic Brain Injury and Secondary Insults.

    PubMed

    Simon, Dennis W; Vagni, Vincent M; Kochanek, Patrick M; Clark, Robert S B

    2016-01-01

    Patients with severe traumatic brain injury (TBI) frequently present with concomitant injuries that may cause secondary brain injury and impact outcomes. Animal models have been developed that combine contemporary models of TBI with a secondary neurologic insult such as hypoxia, shock, long bone fracture, and radiation exposure. Combined injury models may be particularly useful when modeling treatment strategies and in efforts to map basic research to a heterogeneous patient population. Here, we review these models and their collective contribution to the literature on TBI. In addition, we provide protocols and notes for two well-characterized models of TBI plus hemorrhagic shock. PMID:27604730

  14. CTBT Integrated Verification System Evaluation Model

    SciTech Connect

    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.

  15. Early Shifts of Brain Metabolism by Caloric Restriction Preserve White Matter Integrity and Long-Term Memory in Aging Mice

    PubMed Central

    Guo, Janet; Bakshi, Vikas; Lin, Ai-Ling

    2015-01-01

    Preservation of brain integrity with age is highly associated with lifespan determination. Caloric restriction (CR) has been shown to increase longevity and healthspan in various species; however, its effects on preserving living brain functions in aging remain largely unexplored. In the study, we used multimodal, non-invasive neuroimaging (PET/MRI/MRS) to determine in vivo brain glucose metabolism, energy metabolites, and white matter structural integrity in young and old mice fed with either control or 40% CR diet. In addition, we determined the animals’ memory and learning ability with behavioral assessments. Blood glucose, blood ketone bodies, and body weight were also measured. We found distinct patterns between normal aging and CR aging on brain functions – normal aging showed reductions in brain glucose metabolism, white matter integrity, and long-term memory, resembling human brain aging. CR aging, in contrast, displayed an early shift from glucose to ketone bodies metabolism, which was associated with preservations of brain energy production, white matter integrity, and long-term memory in aging mice. Among all the mice, we found a positive correlation between blood glucose level and body weight, but an inverse association between blood glucose level and lifespan. Our findings suggest that CR could slow down brain aging, in part due to the early shift of energy metabolism caused by lower caloric intake, and we were able to identify the age-dependent effects of CR non-invasively using neuroimaging. These results provide a rationale for CR-induced sustenance of brain health with extended longevity. PMID:26617514

  16. [A research on healthcare integrating model of medical information system].

    PubMed

    Lü, Xudong; Duan, Huilong

    2005-02-01

    System integration is inevitable since there are lots of heterogeneous medical information systems in the complicated medical environment. The current medical communication standards often focus on one aspect of the integration and do not provide a general scheme. Based on the analysis of the application of medical integration, the medical integration model HIM (Healthcare integrating model) is put forward, and the dataflow integration framework, function integration framework and interface integration framework in the HIM are designed subsequently. HIM provides a 3-D scheme for the integration of medical information systems, which not only contains the three aspects of integration application vertically, but covers the whole medical area horizontally. PMID:15762128

  17. The Effects of a High-Energy Diet on Hippocampal Function and Blood-Brain Barrier Integrity in the Rat

    PubMed Central

    Kanoski, Scott E.; Zhang, Yanshu; Zheng, Wei; Davidson, Terry L.

    2016-01-01

    Cognitive impairment and Alzheimer’s Disease are linked with intake of a Western Diet, characterized by high levels of saturated fats and simple carbohydrates. In rats, these dietary components have been shown to disrupt hippocampal-dependent learning and memory processes, particularly those involving spatial memory. Using a rat model, the present research assessed the degree to which consumption of a high-energy (HE) diet, similar to those found in modern Western cultures, produces a selective impairment in hippocampal function as opposed to a more global cognitive disruption. Learning and memory performance was examined following 90-days consumption of an HE-diet in three nonspatial discrimination learning problems that differed with respect to their dependence on the integrity of the hippocampus. The results showed that consumption of the HE-diet impaired performance in a hippocampal-dependent feature negative discrimination problem relative to chow-fed controls, whereas performance was spared on two discrimination problems that do not rely on the hippocampus. To explore the mechanism whereby consuming HE-diets impairs cognitive function, we investigated the effect of HE-diets on the integrity of the blood-brain barrier (BBB). We found that HE-diet consumption produced a decrease in mRNA expression of tight junction proteins, particularly Claudin-5 and -12, in the choroid plexus and the BBB. Consequently, an increased blood-to-brain permeability of sodium fluorescein was observed in the hippocampus, but not in the striatum and prefrontal cortex following HE-diet access. There results indicate that hippocampal function may be particularly vulnerable to disruption by HE-diets, and this disruption may be related to impaired BBB integrity. PMID:20413889

  18. Immediate, but Not Delayed, Microsurgical Skull Reconstruction Exacerbates Brain Damage in Experimental Traumatic Brain Injury Model

    PubMed Central

    Lau, Tsz; Kaneko, Yuji; van Loveren, Harry; Borlongan, Cesario V.

    2012-01-01

    Moderate to severe traumatic brain injury (TBI) often results in malformations to the skull. Aesthetic surgical maneuvers may offer normalized skull structure, but inconsistent surgical closure of the skull area accompanies TBI. We examined whether wound closure by replacement of skull flap and bone wax would allow aesthetic reconstruction of the TBI-induced skull damage without causing any detrimental effects to the cortical tissue. Adult male Sprague-Dawley rats were subjected to TBI using the controlled cortical impact (CCI) injury model. Immediately after the TBI surgery, animals were randomly assigned to skull flap replacement with or without bone wax or no bone reconstruction, then were euthanized at five days post-TBI for pathological analyses. The skull reconstruction provided normalized gross bone architecture, but 2,3,5-triphenyltetrazolium chloride and hematoxylin and eosin staining results revealed larger cortical damage in these animals compared to those that underwent no surgical maneuver at all. Brain swelling accompanied TBI, especially the severe model, that could have relieved the intracranial pressure in those animals with no skull reconstruction. In contrast, the immediate skull reconstruction produced an upregulation of the edema marker aquaporin-4 staining, which likely prevented the therapeutic benefits of brain swelling and resulted in larger cortical infarcts. Interestingly, TBI animals introduced to a delay in skull reconstruction (i.e., 2 days post-TBI) showed significantly reduced edema and infarcts compared to those exposed to immediate skull reconstruction. That immediate, but not delayed, skull reconstruction may exacerbate TBI-induced cortical tissue damage warrants a careful consideration of aesthetic repair of the skull in TBI. PMID:22438975

  19. Statistical shape model-based segmentation of brain MRI images.

    PubMed

    Bailleul, Jonathan; Ruan, Su; Constans, Jean-Marc

    2007-01-01

    We propose a segmentation method that automatically delineates structures contours from 3D brain MRI images using a statistical shape model. We automatically build this 3D Point Distribution Model (PDM) in applying a Minimum Description Length (MDL) annotation to a training set of shapes, obtained by registration of a 3D anatomical atlas over a set of patients brain MRIs. Delineation of any structure from a new MRI image is first initialized by such registration. Then, delineation is achieved in iterating two consecutive steps until the 3D contour reaches idempotence. The first step consists in applying an intensity model to the latest shape position so as to formulate a closer guess: our model requires far less priors than standard model in aiming at direct interpretation rather than compliance to learned contexts. The second step consists in enforcing shape constraints onto previous guess so as to remove all bias induced by artifacts or low contrast on current MRI. For this, we infer the closest shape instance from the PDM shape space using a new estimation method which accuracy is significantly improved by a huge increase in the model resolution and by a depth-search in the parameter space. The delineation results we obtained are very encouraging and show the interest of the proposed framework. PMID:18003193

  20. Whole Brain Radiotherapy With Hippocampal Avoidance and Simultaneous Integrated Boost for 1-3 Brain Metastases: A Feasibility Study Using Volumetric Modulated Arc Therapy

    SciTech Connect

    Hsu, Fred; Carolan, Hannah; Nichol, Alan; Cao, Fred; Nuraney, Nimet; Lee, Richard; Gete, Ermias; Wong, Frances; Schmuland, Moira; Heran, Manraj; Otto, Karl

    2010-04-15

    Purpose: To evaluate the feasibility of using volumetric modulated arc therapy (VMAT) to deliver whole brain radiotherapy (WBRT) with hippocampal avoidance and a simultaneous integrated boost (SIB) for one to three brain metastases. Methods and Materials: Ten patients previously treated with stereotactic radiosurgery for one to three brain metastases underwent repeat planning using VMAT. The whole brain prescription dose was 32.25 Gy in 15 fractions, and SIB doses to brain metastases were 63 Gy to lesions >=2.0 cm and 70.8 Gy to lesions <2.0 cm in diameter. The mean dose to the hippocampus was kept at <6 Gy{sub 2}. Plans were optimized for conformity and target coverage while minimizing hippocampal and ocular doses. Plans were evaluated on target coverage, prescription isodose to target volume ratio, conformity number, homogeneity index, and maximum dose to prescription dose ratio. Results: Ten patients had 18 metastases. Mean values for the brain metastases were as follows: conformity number = 0.73 +- 0.10, target coverage = 0.98 +- 0.01, prescription isodose to target volume = 1.34 +- 0.19, maximum dose to prescription dose ratio = 1.09 +- 0.02, and homogeneity index = 0.07 +- 0.02. For the whole brain, the mean target coverage and homogeneity index were 0.960 +- 0.002 and 0.39 +- 0.06, respectively. The mean hippocampal dose was 5.23 +- 0.39 Gy{sub 2}. The mean treatment delivery time was 3.6 min (range, 3.3-4.1 min). Conclusions: VMAT was able to achieve adequate whole brain coverage with conformal hippocampal avoidance and radiosurgical quality dose distributions for one to three brain metastases. The mean delivery time was under 4 min.

  1. Oligodendrocyte Precursor Cells Support Blood-Brain Barrier Integrity via TGF-β Signaling

    PubMed Central

    Maeda, Mitsuyo; Miyamoto, Nobukazu; Liang, Anna C.; Hayakawa, Kazuhide; Pham, Loc-Duyen D.; Suwa, Fumihiko; Taguchi, Akihiko; Matsuyama, Tomohiro; Ihara, Masafumi; Kim, Kyu-Won; Lo, Eng H.; Arai, Ken

    2014-01-01

    Trophic coupling between cerebral endothelium and their neighboring cells is required for the development and maintenance of blood-brain barrier (BBB) function. Here we report that oligodendrocyte precursor cells (OPCs) secrete soluble factor TGF-β1 to support BBB integrity. Firstly, we prepared conditioned media from OPC cultures and added them to cerebral endothelial cultures. Our pharmacological experiments showed that OPC-conditioned media increased expressions of tight-junction proteins and decreased in vitro BBB permeability by activating TGB-β-receptor-MEK/ERK signaling pathway. Secondly, our immuno-electron microscopic observation revealed that in neonatal mouse brains, OPCs attach to cerebral endothelial cells via basal lamina. And finally, we developed a novel transgenic mouse line that TGF-β1 is knocked down specifically in OPCs. Neonates of these OPC-specific TGF-β1 deficient mice (OPC-specific TGF-β1 partial KO mice: PdgfraCre/Tgfb1flox/wt mice or OPC-specific TGF-β1 total KO mice: PdgfraCre/Tgfb1flox/flox mice) exhibited cerebral hemorrhage and loss of BBB function. Taken together, our current study demonstrates that OPCs increase BBB tightness by upregulating tight junction proteins via TGF-β signaling. Although astrocytes and pericytes are well-known regulators of BBB maturation and maintenance, these findings indicate that OPCs also play a pivotal role in promoting BBB integrity. PMID:25078775

  2. Integrating brain, behavior, and phylogeny to understand the evolution of sensory systems in birds.

    PubMed

    Wylie, Douglas R; Gutiérrez-Ibáñez, Cristian; Iwaniuk, Andrew N

    2015-01-01

    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 behavior are intimately tied to phylogenetic history, requiring studies to integrate neuroanatomy with behavior 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, behavior, 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. PMID:26321905

  3. JUMPg: An Integrative Proteogenomics Pipeline Identifying Unannotated Proteins in Human Brain and Cancer Cells.

    PubMed

    Li, Yuxin; Wang, Xusheng; Cho, Ji-Hoon; Shaw, Timothy I; Wu, Zhiping; Bai, Bing; Wang, Hong; Zhou, Suiping; Beach, Thomas G; Wu, Gang; Zhang, Jinghui; Peng, Junmin

    2016-07-01

    Proteogenomics is an emerging approach to improve gene annotation and interpretation of proteomics data. Here we present JUMPg, an integrative proteogenomics pipeline including customized database construction, tag-based database search, peptide-spectrum match filtering, and data visualization. JUMPg creates multiple databases of DNA polymorphisms, mutations, splice junctions, partially trypticity, as well as protein fragments translated from the whole transcriptome in all six frames upon RNA-seq de novo assembly. We use a multistage strategy to search these databases sequentially, in which the performance is optimized by re-searching only unmatched high-quality spectra and reusing amino acid tags generated by the JUMP search engine. The identified peptides/proteins are displayed with gene loci using the UCSC genome browser. Then, the JUMPg program is applied to process a label-free mass spectrometry data set of Alzheimer's disease postmortem brain, uncovering 496 new peptides of amino acid substitutions, alternative splicing, frame shift, and "non-coding gene" translation. The novel protein PNMA6BL specifically expressed in the brain is highlighted. We also tested JUMPg to analyze a stable-isotope labeled data set of multiple myeloma cells, revealing 991 sample-specific peptides that include protein sequences in the immunoglobulin light chain variable region. Thus, the JUMPg program is an effective proteogenomics tool for multiomics data integration. PMID:27225868

  4. Integrating brain, behavior, and phylogeny to understand the evolution of sensory systems in birds

    PubMed Central

    Wylie, Douglas R.; Gutiérrez-Ibáñez, Cristian; Iwaniuk, Andrew N.

    2015-01-01

    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 behavior are intimately tied to phylogenetic history, requiring studies to integrate neuroanatomy with behavior 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, behavior, 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. PMID:26321905

  5. Blood-Brain Barrier Impairment in an Animal Model of MPS III B

    PubMed Central

    Garbuzova-Davis, Svitlana; Louis, Michael K.; Haller, Edward M.; Derasari, Hiranya M.; Rawls, Ashley E.; Sanberg, Paul R.

    2011-01-01

    Background Sanfilippo syndrome type B (MPS III B) is caused by a deficiency of α-N-acetylglucosaminidase enzyme, leading to accumulation of heparan sulfate within lysosomes and eventual progressive cerebral and systemic multiple organ abnormalities. However, little is known about the competence of the blood-brain barrier (BBB) in MPS III B. BBB dysfunction in this devastating disorder could contribute to neuropathological disease manifestations. Methodology/Principal Findings In the present study, we investigated structural (electron microscope) and functional (vascular leakage) integrity of the BBB in a mouse model of MPS III B at different stages of disease, focusing on brain structures known to experience neuropathological changes. Major findings of our study were: (1) endothelial cell damage in capillary ultrastructure, compromising the BBB and resulting in vascular leakage, (2) formation of numerous large vacuoles in endothelial cells and perivascular cells (pericytes and perivascular macrophages) in the large majority of vessels, (3) edematous space around microvessels, (4) microaneurysm adjacent to a ruptured endothelium, (6) Evans Blue and albumin microvascular leakage in various brain structures, (7) GM3 ganglioside accumulation in endothelium of the brain microvasculature. Conclusions/Significance These new findings of BBB structural and function impairment in MPS III B mice even at early disease stage may have implications for disease pathogenesis and should be considered in current and future development of treatments for MPS III B. PMID:21408219

  6. Functional integration changes in regional brain glucose metabolism from childhood to adulthood.

    PubMed

    Trotta, Nicola; Archambaud, Frédérique; Goldman, Serge; Baete, Kristof; Van Laere, Koen; Wens, Vincent; Van Bogaert, Patrick; Chiron, Catherine; De Tiège, Xavier

    2016-08-01

    The aim of this study was to investigate the age-related changes in resting-state neurometabolic connectivity from childhood to adulthood (6-50 years old). Fifty-four healthy adult subjects and twenty-three pseudo-healthy children underwent [(18) F]-fluorodeoxyglucose positron emission tomography at rest. Using statistical parametric mapping (SPM8), age and age squared were first used as covariate of interest to identify linear and non-linear age effects on the regional distribution of glucose metabolism throughout the brain. Then, by selecting voxels of interest (VOI) within the regions showing significant age-related metabolic changes, a psychophysiological interaction (PPI) analysis was used to search for age-induced changes in the contribution of VOIs to the metabolic activity in other brain areas. Significant linear or non-linear age-related changes in regional glucose metabolism were found in prefrontal cortices (DMPFC/ACC), cerebellar lobules, and thalamo-hippocampal areas bilaterally. Decreases were found in the contribution of thalamic, hippocampal, and cerebellar regions to DMPFC/ACC metabolic activity as well as in the contribution of hippocampi to preSMA and right IFG metabolic activities. Increases were found in the contribution of the right hippocampus to insular cortex and of the cerebellar lobule IX to superior parietal cortex metabolic activities. This study evidences significant linear or non-linear age-related changes in regional glucose metabolism of mesial prefrontal, thalamic, mesiotemporal, and cerebellar areas, associated with significant modifications in neurometabolic connectivity involving fronto-thalamic, fronto-hippocampal, and fronto-cerebellar networks. These changes in functional brain integration likely represent a metabolic correlate of age-dependent effects on sensory, motor, and high-level cognitive functional networks. Hum Brain Mapp 37:3017-3030, 2016. © 2016 Wiley Periodicals, Inc. PMID:27133021

  7. Modeling the dynamical effects of anesthesia on brain circuits.

    PubMed

    Ching, Shinung; Brown, Emery N

    2014-04-01

    General anesthesia is a neurophysiological state that consists of unconsciousness, amnesia, analgesia, and immobility along with maintenance of physiological stability. General anesthesia has been used in the United States for more than 167 years. Now, using systems neuroscience paradigms how anesthetics act in the brain and central nervous system to create the states of general anesthesia is being understood. Propofol is one of the most widely used and the most widely studied anesthetics. When administered for general anesthesia or sedation, the electroencephalogram (EEG) under propofol shows highly structured, rhythmic activity that is strongly associated with changes in the patient's level of arousal. These highly structured oscillations lend themselves readily to mathematical descriptions using dynamical systems models. We review recent model descriptions of the commonly observed EEG patterns associated with propofol: paradoxical excitation, strong frontal alpha oscillations, anteriorization and burst suppression. Our analysis suggests that propofol's actions at GABAergic networks in the cortex, thalamus and brainstem induce profound brain dynamics that are one of the likely mechanisms through which this anesthetic induces altered arousal states from sedation to unconsciousness. Because these dynamical effects are readily observed in the EEG, the mathematical descriptions of how propofol's EEG signatures relate to its mechanisms of action in neural circuits provide anesthesiologists with a neurophysiologically based approach to monitoring the brain states of patients receiving anesthesia care. PMID:24457211

  8. Experimental Models Combining Traumatic Brain Injury and Hypoxia.

    PubMed

    Thelin, Eric P

    2016-01-01

    Traumatic brain injury (TBI) is one of the most common causes of death and disability, and cerebral hypoxia is a frequently occurring harmful secondary event in TBI patients. The hypoxic conditions that occur on the scene of accident, where the airways are often obstructed or breathing is in other ways impaired, could be reproduced using animal TBI models where oxygen delivery is strictly controlled throughout the entire experimental procedure. Monitoring physiological parameters of the animal is of utmost importance in order to maintain an adequate quality of the experiment. Peripheral oxygen saturation, O2 pressure (pO2) in the blood, or fraction of inhaled O2 (FiO2) could be used as goals to validate the hypoxic conditions. Different models of traumatic brain injury could be used to inflict desired injury type, whereas effects then could be studied using radiological, physiological and functional tests. In order to confirm that the brain has been affected by a hypoxic injury, appropriate substances in the affected cerebral tissue, cerebrospinal fluid, or serum should be analyzed. PMID:27604734

  9. The Integrated Airport Competition Model, 1998

    NASA Technical Reports Server (NTRS)

    Veldhuis, J.; Essers, I.; Bakker, D.; Cohn, N.; Kroes, E.

    1999-01-01

    This paper addresses recent model development by the Directorate General of Civil Aviation (DGCA) and Hague Consulting Group (HCG) concerning long-distance travel, Long-distance travel demand is growing very quickly and raising a great deal of economic and policy issues. There is increasing competition among the main Western European airports, and smaller, regional airports are fighting for market share. New modes of transport, such as high speed rail, arc also coming into the picture and affect the mode split for medium distance transport within Europe. Developments such as these are demanding the attention of policy makers and a tool is required for their analysis. For DGCA, Hague Consulting Group has developed a model system to provide answers to the policy questions posed by these expected trends, and to identify areas where policy makers can influence the traveller choices. The development of this model system, the Integrated Airport Competition Model/Integral Luchthaven Competitive Model (ILCM), began in 1992. Since that time the sub-models, input data and user interface have been expanded, updated and improved. HCG and DGCA have transformed the ILCM from a prototype into an operational forecasting tool.

  10. Ontological Modeling for Integrated Spacecraft Analysis

    NASA Technical Reports Server (NTRS)

    Wicks, Erica

    2011-01-01

    Current spacecraft work as a cooperative group of a number of subsystems. Each of these requiresmodeling software for development, testing, and prediction. It is the goal of my team to create anoverarching software architecture called the Integrated Spacecraft Analysis (ISCA) to aid in deploying the discrete subsystems' models. Such a plan has been attempted in the past, and has failed due to the excessive scope of the project. Our goal in this version of ISCA is to use new resources to reduce the scope of the project, including using ontological models to help link the internal interfaces of subsystems' models with the ISCA architecture.I have created an ontology of functions specific to the modeling system of the navigation system of a spacecraft. The resulting ontology not only links, at an architectural level, language specificinstantiations of the modeling system's code, but also is web-viewable and can act as a documentation standard. This ontology is proof of the concept that ontological modeling can aid in the integration necessary for ISCA to work, and can act as the prototype for future ISCA ontologies.

  11. Integrated modeling of advanced optical systems

    NASA Astrophysics Data System (ADS)

    Briggs, Hugh C.; Needels, Laura; Levine, B. Martin

    1993-02-01

    This poster session paper describes an integrated modeling and analysis capability being developed at JPL under funding provided by the JPL Director's Discretionary Fund and the JPL Control/Structure Interaction Program (CSI). The posters briefly summarize the program capabilities and illustrate them with an example problem. The computer programs developed under this effort will provide an unprecedented capability for integrated modeling and design of high performance optical spacecraft. The engineering disciplines supported include structural dynamics, controls, optics and thermodynamics. Such tools are needed in order to evaluate the end-to-end system performance of spacecraft such as OSI, POINTS, and SMMM. This paper illustrates the proof-of-concept tools that have been developed to establish the technology requirements and demonstrate the new features of integrated modeling and design. The current program also includes implementation of a prototype tool based upon the CAESY environment being developed under the NASA Guidance and Control Research and Technology Computational Controls Program. This prototype will be available late in FY-92. The development plan proposes a major software production effort to fabricate, deliver, support and maintain a national-class tool from FY-93 through FY-95.

  12. Integrated engineering modeling for air breathing rockets

    NASA Astrophysics Data System (ADS)

    Chitilappilly, Lazar T.; Subramanyam, J. D. A.

    An innovative aerodynamic-propulsion-flight integrated modeling is carried out for airbreathing rockets, the propulsion of which has primary dependence on flight conditions. The integrated modeling is highly beneficial for design and analysis of accelerating air breathing rockets characterized by continuously varying flight conditions. The details of the modeling is described; the force accounting, trajectory analysis, solving the flow in the sub-systems (air intake, primary rocket, secondary combustion chamber and secondary nozzle), matching the subsystem flow fields and determining the mode of operation. Operational features are listed of the computer software developed, air breathing integrated design and analysis engineering software. It gives all the propulsion and flight parameters from take-off of the rocket to end of flight and has been instrumental in the design of the research air breathing rocket ABR-200(I). The hundreds of flight performance analyses required for design is possible by the engineering approach adopted for solving the propulsor flow field. The software results are compared with ejector mode and connected pipe mode static tests. The overall validation of the software is achieved by flight tests; the performance predictions have matched exactly with that measured during thee first and second flights of the ABR-200(I).

  13. Generalized Gibbs ensemble in integrable lattice models

    NASA Astrophysics Data System (ADS)

    Vidmar, Lev; Rigol, Marcos

    2016-06-01

    The generalized Gibbs ensemble (GGE) was introduced ten years ago to describe observables in isolated integrable quantum systems after equilibration. Since then, the GGE has been demonstrated to be a powerful tool to predict the outcome of the relaxation dynamics of few-body observables in a variety of integrable models, a process we call generalized thermalization. This review discusses several fundamental aspects of the GGE and generalized thermalization in integrable systems. In particular, we focus on questions such as: which observables equilibrate to the GGE predictions and who should play the role of the bath; what conserved quantities can be used to construct the GGE; what are the differences between generalized thermalization in noninteracting systems and in interacting systems mappable to noninteracting ones; why is it that the GGE works when traditional ensembles of statistical mechanics fail. Despite a lot of interest in these questions in recent years, no definite answers have been given. We review results for the XX model and for the transverse field Ising model. For the latter model, we also report original results and show that the GGE describes spin–spin correlations over the entire system. This makes apparent that there is no need to trace out a part of the system in real space for equilibration to occur and for the GGE to apply. In the past, a spectral decomposition of the weights of various statistical ensembles revealed that generalized eigenstate thermalization occurs in the XX model (hard-core bosons). Namely, eigenstates of the Hamiltonian with similar distributions of conserved quantities have similar expectation values of few-spin observables. Here we show that generalized eigenstate thermalization also occurs in the transverse field Ising model.

  14. Drosophila melanogaster as a Model Organism of Brain Diseases

    PubMed Central

    Jeibmann, Astrid; Paulus, Werner

    2009-01-01

    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. PMID:19333415

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

    PubMed

    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

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

    PubMed Central

    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

  17. An integrated neuromechanical model of insect locomotion

    NASA Astrophysics Data System (ADS)

    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

  18. Systematic Review of Traumatic Brain Injury Animal Models.

    PubMed

    Phipps, Helen W

    2016-01-01

    The goals of this chapter are to provide an introduction into the variety of animal models available for studying traumatic brain injury (TBI) and to provide a concise systematic review of the general materials and methods involved in each model. Materials and methods were obtained from a literature search of relevant peer-reviewed articles. Strengths and weaknesses of each animal choice were presented to include relative cost, anatomical and physiological features, and mechanism of injury desired. Further, a variety of homologous, isomorphic/induced, and predictive animal models were defined, described, and compared with respect to their relative ease of use, characteristics, range, adjustability (e.g., amplitude, duration, mass/size, velocity, and pressure), and rough order of magnitude cost. Just as the primary mechanism of action of TBI is limitless, so are the animal models available to study TBI. With such a wide variety of available animals, types of injury models, along with the research needs, there exists no single "gold standard" model of TBI rendering cross-comparison of data extremely difficult. Therefore, this chapter reflects a representative sampling of the TBI animal models available and is not an exhaustive comparison of every possible model and associated parameters. Throughout this chapter, special considerations for animal choice and TBI animal model classification are discussed. Criteria central to choosing appropriate animal models of TBI include ethics, funding, complexity (ease of use, safety, and controlled access requirements), type of model, model characteristics, and range of control (scope). PMID:27604713

  19. A comparison of hyperelastic constitutive models applicable to brain and fat tissues

    PubMed Central

    Mihai, L. Angela; Chin, LiKang; Janmey, Paul A.; Goriely, Alain

    2015-01-01

    In some soft biological structures such as brain and fat tissues, strong experimental evidence suggests that the shear modulus increases significantly under increasing compressive strain, but not under tensile strain, whereas the apparent Young's elastic modulus increases or remains almost constant when compressive strain increases. These tissues also exhibit a predominantly isotropic, incompressible behaviour. Our aim is to capture these seemingly contradictory mechanical behaviours, both qualitatively and quantitatively, within the framework of finite elasticity, by modelling a soft tissue as a homogeneous, isotropic, incompressible, hyperelastic material and comparing our results with available experimental data. Our analysis reveals that the Fung and Gent models, which are typically used to model soft tissues, are inadequate for the modelling of brain or fat under combined stretch and shear, and so are the classical neo-Hookean and Mooney–Rivlin models used for elastomers. However, a subclass of Ogden hyperelastic models are found to be in excellent agreement with the experiments. Our findings provide explicit models suitable for integration in large-scale finite-element computations. PMID:26354826

  20. Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

    PubMed

    Siettos, Constantinos; Starke, Jens

    2016-09-01

    The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website. PMID:27340949

  1. A comparison of hyperelastic constitutive models applicable to brain and fat tissues.

    PubMed

    Mihai, L Angela; Chin, LiKang; Janmey, Paul A; Goriely, Alain

    2015-09-01

    In some soft biological structures such as brain and fat tissues, strong experimental evidence suggests that the shear modulus increases significantly under increasing compressive strain, but not under tensile strain, whereas the apparent Young's elastic modulus increases or remains almost constant when compressive strain increases. These tissues also exhibit a predominantly isotropic, incompressible behaviour. Our aim is to capture these seemingly contradictory mechanical behaviours, both qualitatively and quantitatively, within the framework of finite elasticity, by modelling a soft tissue as a homogeneous, isotropic, incompressible, hyperelastic material and comparing our results with available experimental data. Our analysis reveals that the Fung and Gent models, which are typically used to model soft tissues, are inadequate for the modelling of brain or fat under combined stretch and shear, and so are the classical neo-Hookean and Mooney-Rivlin models used for elastomers. However, a subclass of Ogden hyperelastic models are found to be in excellent agreement with the experiments. Our findings provide explicit models suitable for integration in large-scale finite-element computations. PMID:26354826

  2. Integrated Model for E-Learning Acceptance

    NASA Astrophysics Data System (ADS)

    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.

  3. High-strain-rate brain injury model using submerged acute rat brain tissue slices.

    PubMed

    Sarntinoranont, Malisa; Lee, Sung J; Hong, Yu; King, Michael A; Subhash, Ghatu; Kwon, Jiwoon; Moore, David F

    2012-01-20

    Blast-induced traumatic brain injury (bTBI) has received increasing attention in recent years due to ongoing military operations in Iraq and Afghanistan. Sudden impacts or explosive blasts generate stress and pressure waves that propagate at high velocities and affect sensitive neurological tissues. The immediate soft tissue response to these stress waves is difficult to assess using current in vivo imaging technologies. However, these stress waves and resultant stretching and shearing of tissue within the nano- to microsecond time scale of blast and impact are likely to cause initial injury. To visualize the effects of stress wave loading, we have developed a new ex vivo model in which living tissue slices from rat brain, attached to a ballistic gelatin substrate, were subjected to high-strain-rate loads using a polymer split Hopkinson pressure bar (PSHPB) with real-time high-speed imaging. In this study, average peak fluid pressure within the test chamber reached a value of 1584±63.3 psi. Cavitation due to a trailing underpressure wave was also observed. Time-resolved images of tissue deformation were collected and large maximum eigenstrains (0.03-0.42), minimum eigenstrains (-0.33 to -0.03), maximum shear strains (0.09-0.45), and strain rates (8.4×10³/sec) were estimated using digital image correlation (DIC). Injury at 4 and 6 h was quantified using Fluoro-Jade C. Neuronal injury due to PSHPB testing was found to be significantly greater than injury associated with the tissue slice paradigm alone. While large pressures and strains were encountered for these tests, this system provides a controllable test environment to study injury to submerged brain slices over a range of strain rate, pressure, and strain loads. PMID:21970544

  4. Integrated Nanozymes with Nanoscale Proximity for in Vivo Neurochemical Monitoring in Living Brains.

    PubMed

    Cheng, Hanjun; Zhang, Lei; He, Jian; Guo, Wenjing; Zhou, Zhengyang; Zhang, Xuejin; Nie, Shuming; Wei, Hui

    2016-05-17

    Nanozymes, the nanostructures with enzymatic activities, have attracted considerable attention because, in comparison with natural enzymes, they offer the possibility of lowered cost, improved stability, and excellent recyclability. However, the specificity and catalytic activity of current nanozymes are still far lower than that of their natural counterparts, which in turn has limited their use such as in bioanalysis. To address these challenges, herein we report the design and development of integrated nanozymes (INAzymes) by simultaneously embedding two cascade catalysts (i.e., a molecular catalyst hemin and a natural enzyme glucose oxidase, GOx) inside zeolitic imidazolate framework (ZIF-8) nanostructures. Such integrated design endowed the INAzymes with major advantage in improved catalytic efficiency as the first enzymatic reaction occurred in close (nanoscale) proximity to the second enzyme, so products of the first reaction can be used immediately as substrates for the second reaction, thus overcoming the problems of diffusion-limited kinetics and product instability. The considerable high catalytic activity and stability enabled the INAzymes to efficiently draw a colorimetric detection of glucose with good sensitivity and selectivity. When facilitated with in vivo microdialysis, the INAzyme was successfully used for facile colorimetric visualization of cerebral glucose in the brain of living rats. Moreover, when further combined with microfluidic technology, an integrative INAzyme-based online in vivo analytical platform was constructed. The promising application of the platform was successfully illustrated by continuously monitoring the dynamic changes of striatum glucose in living rats' brain following ischemia/reperfusion. This study developed a useful approach to not only functional nanomaterial design but also advanced platforms developments for diverse targets monitoring. PMID:27067749

  5. Towards an integrative model of sociality in caviomorph rodents

    PubMed Central

    Hayes, Loren D.; Burger, Joseph Robert; Soto-Gamboa, Mauricio; Sobrero, Raúl; Ebensperger, Luis A

    2012-01-01

    In the late 1990s and early 2000s it was recognized that behavioral ecologists needed to study the sociality of caviomorph rodents (New World hystricognaths) before generalizations about rodent sociality could be made. Researchers identified specific problems facing individuals interested in caviomorph sociality, including a lack of information on the proximate mechanisms of sociality, role of social environment in development, and geographical or intraspecific variation in social systems. Since then researchers have described the social systems of many previously understudied species, including some with broad geographical ranges. Researchers have done a good job of determining the role of social environments in development and identifying the costs and benefits of social living. However, relatively little is known about the proximate mechanisms of social behavior and fitness consequences, limiting progress toward the development of integrative (evolutionary-mechanistic) models for sociality. To develop integrative models behavioral ecologists studying caviomorph rodents must generate information on the fitness consequences of different types of social organization, brain mechanisms, and endocrine substrates of sociality. We review our current understanding and future directions for research in these conceptual areas. A greater understanding of disease ecology, particularly in species carrying Old World parasites, is needed before we can identify potential links between social phenotypes, mechanism, and fitness. PMID:22328791

  6. Experimental Models of Anxiety for Drug Discovery and Brain Research.

    PubMed

    Hart, Peter C; Bergner, Carisa L; Smolinsky, Amanda N; Dufour, Brett D; Egan, Rupert J; LaPorte, Justin L; Kalueff, Allan V

    2016-01-01

    Animal models have been vital to recent advances in experimental neuroscience, including the modeling of common human brain disorders such as anxiety, depression, and schizophrenia. As mice express robust anxiety-like behaviors when exposed to stressors (e.g., novelty, bright light, or social confrontation), these phenotypes have clear utility in testing the effects of psychotropic drugs. Of specific interest is the extent to which mouse models can be used for the screening of new anxiolytic drugs and verification of their possible applications in humans. To address this problem, the present chapter will review different experimental models of mouse anxiety and discuss their utility for testing anxiolytic and anxiogenic drugs. Detailed protocols will be provided for these paradigms, and possible confounds will be addressed accordingly. PMID:27150096

  7. A variational Bayes spatiotemporal model for electromagnetic brain mapping.

    PubMed

    Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

    2014-03-01

    In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. PMID:24354514

  8. Integrated finite element model of composite materials

    NASA Astrophysics Data System (ADS)

    Teply, Jan L.; Herbein, William C.

    1989-05-01

    Two problems traditionally addressed in the area of micromechanics of composite materials can be briefly summarized as follows: (1) for a macroscopically uniform volume of composite material, which is subjected to macroscopically uniform boundary tractions, displacements or heat influx, find overall thermomechanical properties in terms of the thermomechanical properties of the individual constituents; and (2) for the same material volume and boundary conditions as above, find the local stress, strain, and temperature fields in the constituents and on the interfaces. Two different types of micromechanical models are usually applied to the solutions of these two types of problems. For linear elastic materials, the micromechanical models to solve problem (1) offer simple solutions of overall thermomechanical properties either in terms of bound which are derived from periodic or random microstructures, or in terms of single estimates, which are derived from a solution of an isolated inclusion. The finite element variational approaches are applied to integrate the solutions of problems (1) and (2) into one model. The application of displacement and equilibrium variational approaches to the calculation of overall elastic-plastic properties, are extended to the solution of the second problem. The integrated model is then applied to calculate the overall properties and local stress and strain fields of boron-aluminum composites subjected to transverse tension, in-plane shear and bending.

  9. A rodent model of mild traumatic brain blast injury.

    PubMed

    Perez-Polo, J R; Rea, H C; Johnson, K M; Parsley, M A; Unabia, G C; Xu, G-Y; Prough, D; DeWitt, D S; Spratt, H; Hulsebosch, C E

    2015-04-01

    One of the criteria defining mild traumatic brain injury (mTBI) in humans is a loss of consciousness lasting for less than 30 min. mTBI can result in long-term impairment of cognition and behavior. In rats, the length of time it takes a rat to right itself after injury is considered to be an analog for human return to consciousness. This study characterized a rat mild brain blast injury (mBBI) model defined by a righting response reflex time (RRRT) of more than 4 min but less than 10 min. Assessments of motor coordination relying on beam-balance and foot-fault assays and reference memory showed significant impairment in animals exposed to mBBI. This study's hypothesis is that there are inflammatory outcomes to mTBI over time that cause its deleterious effects. For example, mBBI significantly increased brain levels of interleukin (IL)-1β and tumor necrosis factor-α (TNFα) protein. There were significant inflammatory responses in the cortex, hippocampus, thalamus, and amygdala 6 hr after mBBI, as evidenced by increased levels of the inflammatory markers associated with activation of microglia and macrophages, ionized calcium binding adaptor 1 (IBA1), impairment of the blood-brain barrier, and significant neuronal losses. There were significant increases in phosphorylated Tau (p-Tau) levels, a putative precursor to the development of neuroencephalopathy, as early as 6 hr after mBBI in the cortex and the hippocampus but not in the thalamus or the amygdala. There was an apparent correlation between RRRTs and p-Tau protein levels but not IBA1. These results suggest potential therapies for mild blast injuries via blockade of the IL-1β and TNFα receptors. PMID:25410497

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

    PubMed

    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. PMID:25928681

  11. Performance of an INTEGRAL spectrometer model

    NASA Technical Reports Server (NTRS)

    Jean, P.; Naya, J. E.; vonBallmoos, P.; Vedrenne, G.; Teegarden, B.

    1997-01-01

    Model calculations for the INTEGRAL spectrometer (SPI) onboard the future INTErnational Gamma Ray Astrophysics Laboratory (INTEGAL) are presented, where the sensitivity for narrow lines is based on estimates of the background level and the detection efficiency. The instrumental background rates are explained as the sum of various components that depend on the cosmic ray intensity and the spectrometer characteristics, such as the mass distribution around the Ge detectors, the passive material, the characteristics of the detector system and the background reduction techniques. Extended background calculations were performed with Monte Carlo simulations and using semi-empirical and calculated neutron and proton cross sections. In order to improve the INTEGRAL spectrometer sensitivity, several designs and background reduction techniques were compared for an instrument with a fixed detector volume.

  12. An integrated approach to reservoir modeling

    SciTech Connect

    Donaldson, K. )

    1993-08-01

    The purpose of this research is to evaluate the usefulness of the following procedural and analytical methods in investigating the heterogeneity of the oil reserve for the Mississipian Big Injun Sandstone of the Granny Creek field, Clay and Roane counties, West Virginia: (1) relational database, (2) two-dimensional cross sections, (3) true three-dimensional modeling, (4) geohistory analysis, (5) a rule-based expert system, and (6) geographical information systems. The large data set could not be effectively integrated and interpreted without this approach. A relational database was designed to fully integrate three- and four-dimensional data. The database provides an effective means for maintaining and manipulating the data. A two-dimensional cross section program was designed to correlate stratigraphy, depositional environments, porosity, permeability, and petrographic data. This flexible design allows for additional four-dimensional data. Dynamic Graphics[sup [trademark

  13. A watershed model to integrate EO data

    NASA Astrophysics Data System (ADS)

    Jauch, Eduardo; Chambel-Leitao, Pedro; Carina, Almeida; Brito, David; Cherif, Ines; Alexandridis, Thomas; Neves, Ramiro

    2013-04-01

    MOHID LAND is a open source watershed model developed by MARETEC and is part of the MOHID Framework. It integrates four mediums (or compartments): porous media, surface, rivers and atmosphere. The movement of water between these mediums are based on mass and momentum balance equations. The atmosphere medium is not explicity simulated. Instead, it's used as boundary condition to the model through meteorological properties: precipitation, solar radiation, wind speed/direction, relative humidity and air temperature. The surface medium includes the overland runoff and vegetation growth processes and is simulated using a 2D grid. The porous media includes both the unsaturated (soil) and saturated zones (aquifer) and is simulated using a 3D grid. The river flow is simulated through a 1D drainage network. All these mediums are linked through evapotranspiration and flow exchanges (infiltration, river-soil growndwater flow, surface-river overland flow). Besides the water movement, it is also possible to simulate water quality processes and solute/sediment transport. Model setup include the definition of the geometry and the properties of each one of its compartments. After the setup of the model, the only continuous input data that MOHID LAND requires are the atmosphere properties (boundary conditions) that can be provided as timeseries or spacial data. MOHID LAND has been adapted the last 4 years under FP7 and ESA projects to integrate Earth Observation (EO) data, both variable in time and in space. EO data can be used to calibrate/validate or as input/assimilation data to the model. The currently EO data used include LULC (Land Use Land Cover) maps, LAI (Leaf Area Index) maps, EVTP (Evapotranspiration) maps and SWC (Soil Water Content) maps. Model results are improved by the EO data, but the advantage of this integration is that the model can still run without the EO data. This means that model do not stop due to unavailability of EO data and can run on a forecast mode

  14. Brain glucose metabolism in an animal model of depression.

    PubMed

    Detka, J; Kurek, A; Kucharczyk, M; Głombik, K; Basta-Kaim, A; Kubera, M; Lasoń, W; Budziszewska, B

    2015-06-01

    An increasing number of data support the involvement of disturbances in glucose metabolism in the pathogenesis of depression. We previously reported that glucose and glycogen concentrations in brain structures important for depression are higher in a prenatal stress model of depression when compared with control animals. A marked rise in the concentrations of these carbohydrates and glucose transporters were evident in prenatally stressed animals subjected to acute stress and glucose loading in adulthood. To determine whether elevated levels of brain glucose are associated with a change in its metabolism in this model, we assessed key glycolytic enzymes (hexokinase, phosphofructokinase and pyruvate kinase), products of glycolysis, i.e., pyruvate and lactate, and two selected enzymes of the tricarboxylic acid cycle (pyruvate dehydrogenase and α-ketoglutarate dehydrogenase) in the hippocampus and frontal cortex. Additionally, we assessed glucose-6-phosphate dehydrogenase activity, a key enzyme in the pentose phosphate pathway (PPP). Prenatal stress increased the levels of phosphofructokinase, an important glycolytic enzyme, in the hippocampus and frontal cortex. However, prenatal stress had no effect on hexokinase or pyruvate kinase levels. The lactate concentration was elevated in prenatally stressed rats in the frontal cortex, and pyruvate levels remained unchanged. Among the tricarboxylic acid cycle enzymes, prenatal stress decreased the level of pyruvate dehydrogenase in the hippocampus, but it had no effect on α-ketoglutarate dehydrogenase. Like in the case of glucose and its transporters, also in the present study, differences in markers of glucose metabolism between control animals and those subjected to prenatal stress were not observed under basal conditions but in rats subjected to acute stress and glucose load in adulthood. Glucose-6-phosphate dehydrogenase activity was not reduced by prenatal stress but was found to be even higher in animals exposed to

  15. Space Station Freedom integrated fault model

    NASA Technical Reports Server (NTRS)

    Becker, Fred J.

    1989-01-01

    A demonstration of an integrated fault propagation model for Space Station Freedom is described. The demonstration uses a HyperCard graphical interface to show how failures can propagate from one component to another, both within a system and between systems. It also shows how hardware failures can impact certain defined functions like reboost, atmosphere maintenance or collision avoidance. The demonstration enables the user to view block diagrams for the various space station systems using an overview screen, and interactively choose a component and see what single or dual failure combinations can cause it to fail. It also allows the user to directly view the fault model, which is a collection of drawing and text listings accessible from a guide screen. Fault modeling provides a useful technique for analyzing individual systems and also interactions between systems in the presence of multiple failures so that a complete picture of failure tolerance and component criticality can be achieved.

  16. Integrated modeling of the Euro50

    NASA Astrophysics Data System (ADS)

    Andersen, Torben E.; Browne, Michael T.; Enmark, Anita; Moraru, Dan; Owner-Petersen, Mette; Riewaldt, Holger

    2004-07-01

    The Euro50 is a proposed 50 m optical and infrared telescope. It will have thousands of control loops to keep the optics aligned under influence of wind, gravity and thermal loads. Cross-disciplinary integrated modeling is used to study the overall performance of the Euro50. A sub-model of the mechanical structure originates from finite element modeling. The optical performance is determined using ray tracing, both non-linear and linearized. The primary mirror segment alignment control system is modeled with the 618 segments taken as rigid bodies. Adaptive optics is included using a layered model of the atmosphere and sub-models of the wavefront sensor, reconstructor and controller. The deformable mirror is, so far, described by a simple influence function and a second order dynamical transfer function but more detailed work is in progress. The model has been implemented using Matlab/Simulink on individual computers but it will shortly be implemented on a Beowulf cluster within a trusted network. Communication routines between Matlab on the cluster processors have been written and are being benchmarked. Representative results from the simulations are shown.

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

    NASA Astrophysics Data System (ADS)

    Peyrounette, M.; Sylvie, L.; Davit, Y.; Quintard, M.

    2014-12-01

    We have previously demonstrated [1] that the vascular system of the healthy human brain cortex is a superposition of two structural components, each corresponding to a different spatial scale. At small-scale, the vascular network has a capillary structure, which is homogeneous and space-filling over a cut-off length. At larger scale, veins and arteries conform to a quasi-fractal branched structure. This structural duality is consistent with the functional duality of the vasculature, i.e. distribution and exchange. From a modeling perspective, this can be viewed as the superposition of: (a) a continuum model describing slow transport in the small-scale capillary network, characterized by a representative elementary volume and effective properties; and (b) a discrete network approach [2] describing fast transport in the arterial and venous network, which cannot be homogenized because of its fractal nature. This problematic is analogous to modeling problems encountered in geological media, e.g, in petroleum engineering, where fast conducting channels (wells or fractures) are embedded in a porous medium (reservoir rock). An efficient method to reduce the computational cost of fractures/continuum simulations is to use relatively large grid blocks for the continuum model. However, this also makes it difficult to accurately couple both structural components. In this work, we solve this issue by adapting the "well model" concept used in petroleum engineering [3] to brain specific 3-D situations. We obtain a unique linear system of equations describing the discrete network, the continuum and the well model coupling. Results are presented for realistic geometries and compared with a non-homogenized small-scale network model of an idealized periodic capillary network of known permeability. [1] Lorthois & Cassot, J. Theor. Biol. 262, 614-633, 2010. [2] Lorthois et al., Neuroimage 54 : 1031-1042, 2011. [3] Peaceman, SPE J. 18, 183-194, 1978.

  18. Experimental models of perinatal hypoxic-ischemic brain damage.

    PubMed

    Vannucci, R C

    1993-01-01

    Animal research has provided important information on the pathogenesis of and neuropathologic responses to perinatal cerebral hypoxia-ischemia. In experimental animals, structural brain damage from hypoxia-ischemia has been produced in immature rats, rabbits, guinea pigs, sheep and monkeys (18, 20, 24, 25, 38). Of the several available animal models, the fetal and newborn rhesus monkey and immature rat have been studied most extensively because of their similarities to humans in respect to the physiology of reproduction and their neuroanatomy at or shortly following birth. Given the frequency of occurrence of human perinatal hypoxic-ischemic brain damage and the multiple, often severe neurologic handicaps which ensue in infants and children, it is not surprising that the above described animal models have been developed. These models have provided the basis for investigations to clarify not only physiologic and biochemical mechanisms of tissue injury but also the efficacy of specific management strategies. Hopefully, such animal research will continue to provide important information regarding how best to prevent or minimize the devastating consequences of perinatal cerebral hypoxia-ischemia. PMID:8311995

  19. Melanoma Cells Homing to the Brain: An In Vitro Model

    PubMed Central

    Rizzo, A.; Vasco, C.; Girgenti, V.; Fugnanesi, V.; Calatozzolo, C.; Canazza, A.; Salmaggi, A.; Rivoltini, L.; Morbin, M.; Ciusani, E.

    2015-01-01

    We developed an in vitro contact through-feet blood brain barrier (BBB) model built using type IV collagen, rat astrocytes, and human umbilical vein endothelial cells (HUVECs) cocultured through Transwell porous polycarbonate membrane. The contact between astrocytes and HUVECs was demonstrated by electron microscopy: astrocytes endfeet pass through the 8.0 μm pores inducing HUVECs to assume a cerebral phenotype. Using this model we evaluated transmigration of melanoma cells from two different patients (M1 and M2) selected among seven melanoma primary cultures. M2 cells showed a statistically significant higher capability to pass across the in vitro BBB model, compared to M1. Expression of adhesion molecules was evaluated by flow cytometry: a statistically significant increased expression of MCAM, αvβ3, and CD49b was detected in M1. PCR array data showed that M2 had a higher expression of several matrix metalloproteinase proteins (MMPs) compared to M1. Specifically, data suggest that MMP2 and MMP9 could be directly involved in BBB permeability and that brain invasion by melanoma cells could be related to the overexpression of many MMPs. Future studies will be necessary to deepen the mechanisms of central nervous system invasion. PMID:25692137

  20. A simulation model for analysing brain structure deformations

    NASA Astrophysics Data System (ADS)

    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.

  1. Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

    PubMed

    Vakhtin, Andrei A; Ryman, Sephira G; Flores, Ranee A; Jung, Rex E

    2014-12-01

    The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence. PMID:25284305

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

    NASA Astrophysics Data System (ADS)

    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

  3. Human immunodeficiency virus infection of human astrocytes disrupts blood-brain barrier integrity by a gap junction-dependent mechanism.

    PubMed

    Eugenin, Eliseo A; Clements, Janice E; Zink, M Christine; Berman, Joan W

    2011-06-29

    HIV infection of the CNS is an early event after primary infection, resulting in neurological complications in a significant number of individuals despite antiretroviral therapy (ART). The main cells infected with HIV within the CNS are macrophages/microglia and a small fraction of astrocytes. The role of these few infected astrocytes in the pathogenesis of neuroAIDS has not been examined extensively. Here, we demonstrate that few HIV-infected astrocytes (4.7 ± 2.8% in vitro and 8.2 ± 3.9% in vivo) compromise blood-brain barrier (BBB) integrity. This BBB disruption is due to endothelial apoptosis, misguided astrocyte end feet, and dysregulation of lipoxygenase/cyclooxygenase, BK(Ca) channels, and ATP receptor activation within astrocytes. All of these alterations in BBB integrity induced by a few HIV-infected astrocytes were gap junction dependent, as blocking these channels protected the BBB from HIV-infected astrocyte-mediated compromise. We also demonstrated apoptosis in vivo of BBB cells in contact with infected astrocytes using brain tissue sections from simian immunodeficiency virus-infected macaques as a model of neuroAIDS, suggesting an important role for these few infected astrocytes in the CNS damage seen with HIV infection. Our findings describe a novel mechanism of bystander BBB toxicity mediated by low numbers of HIV-infected astrocytes and amplified by gap junctions. This mechanism of toxicity contributes to understanding how CNS damage is spread even in the current ART era and how minimal or controlled HIV infection still results in cognitive impairment in a large population of infected individuals. PMID:21715610

  4. Integrated pollutant removal: modeling and experimentation

    SciTech Connect

    Ochs, Thomas L.; Oryshchyn, Danylo B.; Summers, Cathy A.

    2005-01-01

    Experimental and computational work at the Albany Research Center, USDOE is investigating an integrated pollutant removal (IPR) process which removes all pollutants from flue gas, including SOX, NOX, particulates, CO2, and Hg. In combination with flue gas recirculation, heat recovery, and oxy-fuel combustion, the process produces solid, gas, and liquid waste streams. The gas exhaust stream comprises O2 and N2. Liquid streams contain H2O, SOX, NOX, and CO2. Computer modeling and low to moderate pressure experimentation are defining system chemistry with respect to SOX and H2O as well as heat and mass transfer for the IPR process.

  5. Brain Death and Human Organismal Integration: A Symposium on the Definition of Death.

    PubMed

    Moschella, Melissa

    2016-06-01

    Does the ability of some brain dead bodies to maintain homeostasis with the help of artificial life support actually imply that those bodies are living human organisms? Or might it be possible that a brain dead body on life support is a mere collection of still-living cells, organs and tissues which can coordinate with one another, but which lack the genuine integration that is the hallmark of a unified human organism as a whole? To foster further study of these difficult and timely questions, a Symposium on the Definition of Death was held at The Catholic University of America in June 2014. The Symposium brought together scholars from a variety of disciplines-law, medicine, biology, philosophy and theology-who all share a commitment to the dead donor rule and to a biological definition of death, but who have differing opinions regarding the validity of neurological criteria for human death. The papers found in this special issue are among the fruits of this Symposium. PMID:27107428

  6. Integrating Neuropsychology and Brain Imaging for a Referral of Possible Pseudodementia: A Case Report.

    PubMed

    Tanner, J J; Mellott, E; Dunne, E M; Price, C C

    2015-01-01

    The study aimed to highlight the importance of interdisciplinary collaboration and the value for combining normative neuropsychological and neuroradiological measures for clinical purposes. We present the case of "CL," a 65-year-old, right-handed, Caucasian female referred for a neuropsychological evaluation of memory difficulties and depression with the rule-out of pseudodementia. A brain magnetic resonance imaging (MRI) scan was conducted within 24 hours of the neuropsychology exam. Mood measures showed elevated depression and apathy symptoms. The neuropsychological profile showed variable effort, intact comprehension but compromised confrontation naming and verbal memory deficits. Using normative references from 20 female age- and education-matched healthy control peers, CL showed significantly reduced temporal cortex thickness with reduced bilateral hippocampal, right amygdala, and right caudate volumes. Combined data were supportive of a diagnosis of semantic dementia. Examining neuropsychological profiles in combination with neuroimaging standardized metrics relative to peers improved case conceptualization. Standard measures of effort and malingering examined alone and without MRI for the diagnosis of pseudodementia have questionable validity and rationale. We additionally discuss the advantages and limitations/challenges for integrating neuropsychological assessments with normative based MRI brain metrics. PMID:25658577

  7. Buffered receptor, avionics integration network (BRAIN) - A concept proposed for memory managed avionics

    NASA Astrophysics Data System (ADS)

    Hawkins, R. D.

    A concept is presented herein in which an advanced memory module is proposed as a medium to interface between the aircraft crew and its operational systems in such a manner as to synergistically integrate crew and aircraft into a more effective weapon system. The acronym chosen for the device is intended to be indicative of its function - in essence, the 'BRAIN' is meant to serve as an instrument of control, directly responsive to the needs and wishes of the aircrew, and completely competent to manage every function of the aircraft on a continuous basis. Therefore, by relieving the crew of the stress and tensions of monitoring such things as aircraft altitude, velocity, and heading; and by managing such functions as navigation, weapons delivery, damage assessment, etc., the combination of aircraft and crew will display a measure of performance considered unattainable beforehand. The BRAIN should be a standard device, applicable to all class and make of aircraft. It would perform all mission and maintenance oriented functions, as well as serving as an archival store. Its installation and removal for maintenance and replacement would be easily facilitated. It would be an asset without parallel in any aircraft weapons system.

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

    PubMed

    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. PMID:25617423

  9. Brain white matter integrity and cortisol in older men: the Lothian Birth Cohort 1936☆

    PubMed Central

    Cox, Simon R.; Bastin, Mark E.; Ferguson, Karen J.; Maniega, Susana Muñoz; MacPherson, Sarah E.; Deary, Ian J.; Wardlaw, Joanna M.; MacLullich, Alasdair M.J.

    2015-01-01

    Elevated glucocorticoid (GC) levels are hypothesized to be deleterious to some brain regions, including white matter (WM). Older age is accompanied by increased between-participant variation in GC levels, yet relationships between WM integrity and cortisol levels in older humans are underexplored. Moreover, it is unclear whether GC-WM associations might be general or pathway specific. We analyzed relationships between salivary cortisol (diurnal and reactive) and general measures of brain WM hyperintensity (WMH) volume, fractional anisotropy (gFA), and mean diffusivity (gMD) in 90 males, aged 73 years. Significant associations were predominantly found between cortisol measures and WMHs and gMD but not gFA. Higher cortisol at the start of a mild cognitive stressor was associated with higher WMH and gMD. Higher cortisol at the end was associated with greater WMHs. A constant or increasing cortisol level during cognitive testing was associated with lower gMD. Tract-specific bases of these associations implicated anterior thalamic radiation, uncinate, and arcuate and inferior longitudinal fasciculi. The cognitive sequelae of these relationships, above other covariates, are a priority for future study. PMID:25066239

  10. Integrated Modeling of Complex Optomechanical Systems

    NASA Astrophysics Data System (ADS)

    Andersen, Torben; Enmark, Anita

    2011-09-01

    Mathematical modeling and performance simulation are playing an increasing role in large, high-technology projects. There are two reasons; first, projects are now larger than they were before, and the high cost calls for detailed performance prediction before construction. Second, in particular for space-related designs, it is often difficult to test systems under realistic conditions beforehand, and mathematical modeling is then needed to verify in advance that a system will work as planned. Computers have become much more powerful, permitting calculations that were not possible before. At the same time mathematical tools have been further developed and found acceptance in the community. Particular progress has been made in the fields of structural mechanics, optics and control engineering, where new methods have gained importance over the last few decades. Also, methods for combining optical, structural and control system models into global models have found widespread use. Such combined models are usually called integrated models and were the subject of this symposium. The objective was to bring together people working in the fields of groundbased optical telescopes, ground-based radio telescopes, and space telescopes. We succeeded in doing so and had 39 interesting presentations and many fruitful discussions during coffee and lunch breaks and social arrangements. We are grateful that so many top ranked specialists found their way to Kiruna and we believe that these proceedings will prove valuable during much future work.

  11. A Population Model of Integrative Cardiovascular Physiology

    PubMed Central

    Pruett, William A.; Husband, Leland D.; Husband, Graham; Dakhlalla, Muhammad; Bellamy, Kyle; Coleman, Thomas G.; Hester, Robert L.

    2013-01-01

    We present a small integrative model of human cardiovascular physiology. The model is population-based; rather than using best fit parameter values, we used a variant of the Metropolis algorithm to produce distributions for the parameters most associated with model sensitivity. The population is built by sampling from these distributions to create the model coefficients. The resulting models were then subjected to a hemorrhage. The population was separated into those that lost less than 15 mmHg arterial pressure (compensators), and those that lost more (decompensators). The populations were parametrically analyzed to determine baseline conditions correlating with compensation and decompensation. Analysis included single variable correlation, graphical time series analysis, and support vector machine (SVM) classification. Most variables were seen to correlate with propensity for circulatory collapse, but not sufficiently to effect reasonable classification by any single variable. Time series analysis indicated a single significant measure, the stressed blood volume, as predicting collapse in situ, but measurement of this quantity is clinically impossible. SVM uncovered a collection of variables and parameters that, when taken together, provided useful rubrics for classification. Due to the probabilistic origins of the method, multiple classifications were attempted, resulting in an average of 3.5 variables necessary to construct classification. The most common variables used were systemic compliance, baseline baroreceptor signal strength and total peripheral resistance, providing predictive ability exceeding 90%. The methods presented are suitable for use in any deterministic mathematical model. PMID:24058546

  12. A population model of integrative cardiovascular physiology.

    PubMed

    Pruett, William A; Husband, Leland D; Husband, Graham; Dakhlalla, Muhammad; Bellamy, Kyle; Coleman, Thomas G; Hester, Robert L

    2013-01-01

    We present a small integrative model of human cardiovascular physiology. The model is population-based; rather than using best fit parameter values, we used a variant of the Metropolis algorithm to produce distributions for the parameters most associated with model sensitivity. The population is built by sampling from these distributions to create the model coefficients. The resulting models were then subjected to a hemorrhage. The population was separated into those that lost less than 15 mmHg arterial pressure (compensators), and those that lost more (decompensators). The populations were parametrically analyzed to determine baseline conditions correlating with compensation and decompensation. Analysis included single variable correlation, graphical time series analysis, and support vector machine (SVM) classification. Most variables were seen to correlate with propensity for circulatory collapse, but not sufficiently to effect reasonable classification by any single variable. Time series analysis indicated a single significant measure, the stressed blood volume, as predicting collapse in situ, but measurement of this quantity is clinically impossible. SVM uncovered a collection of variables and parameters that, when taken together, provided useful rubrics for classification. Due to the probabilistic origins of the method, multiple classifications were attempted, resulting in an average of 3.5 variables necessary to construct classification. The most common variables used were systemic compliance, baseline baroreceptor signal strength and total peripheral resistance, providing predictive ability exceeding 90%. The methods presented are suitable for use in any deterministic mathematical model. PMID:24058546

  13. The Integrated Airport Competition Model, 1998

    NASA Technical Reports Server (NTRS)

    Veldhuis, J.; Essers, I.; Bakker, D.; Cohn, N.; Kroes, E.

    1999-01-01

    This paper addresses recent model development by the Directorate General of Civil Aviation (DGCA) and Hague Consulting Group (HCG) concerning long-distance travel. Long-distance travel demand is growing very quickly and raising a great deal of economic and policy issues. There is increasing competition among the main Western European airports, and smaller, regional airports are fighting for market share. New modes of transport, such as high speed rail, are also coming into the picture and affect the mode split for medium distance transport within Europe. Developments such as these are demanding the attention of policy makers and a tool is required for their analysis. For DGCA, Hague Consulting Group has developed a model system to provide answers to the policy questions posed by these expected trends, and to identify areas where policy makers can influence the traveller choices. The development of this model system, the Integrated Airport Competition Model/integraal Luchthaven Competitie Model (ILCM), began in 1992. Since that time the sub-models, input data and user interface have been expanded, updated and improved. HCG and DGCA have transformed the ILCM from a prototype into an operational forecasting tool.

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

    PubMed Central

    Cavrini, Francesco; 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. PMID:26819595

  15. Multimodal sensory integration in insects--towards insect brain control architectures.

    PubMed

    Wessnitzer, Jan; Webb, Barbara

    2006-09-01

    Although a variety of basic insect behaviours have inspired successful robot implementations, more complex capabilities in these 'simple' animals are often overlooked. By reviewing the general architecture of their nervous systems, we gain insight into how they are able to integrate behaviours, perform pattern recognition, context-dependent learning, and combine many sensory inputs in tasks such as navigation. We review in particular what is known about two specific 'higher' areas in the insect brain, the mushroom bodies and the central complex, and how they are involved in controlling an insect's behaviour. While much of the functional interpretation of this information is still speculative, it nevertheless suggests some promising new approaches to obtaining adaptive behaviour in robots. PMID:17671308

  16. Parkin-independent mitophagy requires Drp1 and maintains the integrity of mammalian heart and brain

    PubMed Central

    Kageyama, Yusuke; Hoshijima, Masahiko; Seo, Kinya; Bedja, Djahida; Sysa-Shah, Polina; Andrabi, Shaida A; Chen, Weiran; Höke, Ahmet; Dawson, Valina L; Dawson, Ted M; Gabrielson, Kathleen; Kass, David A; Iijima, Miho; Sesaki, Hiromi

    2014-01-01

    Mitochondrial dynamics and mitophagy have been linked to cardiovascular and neurodegenerative diseases. Here, we demonstrate that the mitochondrial division dynamin Drp1 and the Parkinson's disease-associated E3 ubiquitin ligase parkin synergistically maintain the integrity of mitochondrial structure and function in mouse heart and brain. Mice lacking cardiac Drp1 exhibited lethal heart defects. In Drp1KO cardiomyocytes, mitochondria increased their connectivity, accumulated ubiquitinated proteins, and decreased their respiration. In contrast to the current views of the role of parkin in ubiquitination of mitochondrial proteins, mitochondrial ubiquitination was independent of parkin in Drp1KO hearts, and simultaneous loss of Drp1 and parkin worsened cardiac defects. Drp1 and parkin also play synergistic roles in neuronal mitochondrial homeostasis and survival. Mitochondrial degradation was further decreased by combination of Drp1 and parkin deficiency, compared with their single loss. Thus, the physiological importance of parkin in mitochondrial homeostasis is revealed in the absence of mitochondrial division in mammals. PMID:25349190

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

    PubMed

    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. PMID:26819595

  18. Diffusion tensor imaging reveals adolescent binge ethanol-induced brain structural integrity alterations in adult rats that correlate with behavioral dysfunction.

    PubMed

    Vetreno, Ryan P; Yaxley, Richard; Paniagua, Beatriz; Crews, Fulton T

    2016-07-01

    Adolescence is characterized by considerable brain maturation that coincides with the development of adult behavior. Binge drinking is common during adolescence and can have deleterious effects on brain maturation because of the heightened neuroplasticity of the adolescent brain. Using an animal model of adolescent intermittent ethanol [AIE; 5.0 g/kg, intragastric, 20 percent EtOH w/v; 2 days on/2 days off from postnatal day (P)25 to P55], we assessed the adult brain structural volumes and integrity on P80 and P220 using diffusion tensor imaging (DTI). While we did not observe a long-term effect of AIE on structural volumes, AIE did reduce axial diffusivity (AD) in the cerebellum, hippocampus and neocortex. Radial diffusivity (RD) was reduced in the hippocampus and neocortex of AIE-treated animals. Prior AIE treatment did not affect fractional anisotropy (FA), but did lead to long-term reductions of mean diffusivity (MD) in both the cerebellum and corpus callosum. AIE resulted in increased anxiety-like behavior and diminished object recognition memory, the latter of which was positively correlated with DTI measures. Across aging, whole brain volumes increased, as did volumes of the corpus callosum and neocortex. This was accompanied by age-associated AD reductions in the cerebellum and neocortex as well as RD and MD reductions in the cerebellum. Further, we found that FA increased in both the cerebellum and corpus callosum as rats aged from P80 to P220. Thus, both age and AIE treatment caused long-term changes to brain structural integrity that could contribute to cognitive dysfunction. PMID:25678360

  19. Perinatal programming of emotional brain circuits: an integrative view from systems to molecules

    PubMed Central

    Bock, Jörg; Rether, Kathy; Gröger, Nicole; Xie, Lan; Braun, Katharina

    2014-01-01

    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 ELS 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. PMID:24550772

  20. Integrated research in constitutive modelling at elevated temperatures, part 1

    NASA Technical Reports Server (NTRS)

    Haisler, W. E.; Allen, D. H.

    1986-01-01

    Topics covered include: numerical integration techniques; thermodynamics and internal state variables; experimental lab development; comparison of models at room temperature; comparison of models at elevated temperature; and integrated software development.

  1. TOWARD EFFICIENT RIPARIAN RESTORATION: INTEGRATING ECONOMIC, PHYSICAL, AND BIOLOGICAL MODELS

    EPA Science Inventory

    This paper integrates economic, biological, and physical models to determine the efficient combination and spatial allocation of conservation efforts for water quality protection and salmonid habitat enhancement in the Grande Ronde basin, Oregon. The integrated modeling system co...

  2. Developing Metrics in Systems Integration (ISS Program COTS Integration Model)

    NASA Technical Reports Server (NTRS)

    Lueders, Kathryn

    2007-01-01

    This viewgraph presentation reviews some of the complications in developing metrics for systems integration. Specifically it reviews a case study of how two programs within NASA try to develop and measure performance while meeting the encompassing organizational goals.

  3. White matter hyperintensities and normal-appearing white matter integrity in the aging brain.

    PubMed

    Maniega, Susana Muñoz; Valdés Hernández, Maria C; Clayden, Jonathan D; Royle, Natalie A; Murray, Catherine; Morris, Zoe; Aribisala, Benjamin S; Gow, Alan J; Starr, John M; Bastin, Mark E; Deary, Ian J; Wardlaw, Joanna M

    2015-02-01

    White matter hyperintensities (WMH) of presumed vascular origin are a common finding in brain magnetic resonance imaging of older individuals and contribute to cognitive and functional decline. It is unknown how WMH form, although white matter degeneration is characterized pathologically by demyelination, axonal loss, and rarefaction, often attributed to ischemia. Changes within normal-appearing white matter (NAWM) in subjects with WMH have also been reported but have not yet been fully characterized. Here, we describe the in vivo imaging signatures of both NAWM and WMH in a large group of community-dwelling older people of similar age using biomarkers derived from magnetic resonance imaging that collectively reflect white matter integrity, myelination, and brain water content. Fractional anisotropy (FA) and magnetization transfer ratio (MTR) were significantly lower, whereas mean diffusivity (MD) and longitudinal relaxation time (T1) were significantly higher, in WMH than NAWM (p < 0.0001), with MD providing the largest difference between NAWM and WMH. Receiver operating characteristic analysis on each biomarker showed that MD differentiated best between NAWM and WMH, identifying 94.6% of the lesions using a threshold of 0.747 × 10(-9) m(2)s(-1) (area under curve, 0.982; 95% CI, 0.975-0.989). Furthermore, the level of deterioration of NAWM was strongly associated with the severity of WMH, with MD and T1 increasing and FA and MTR decreasing in NAWM with increasing WMH score, a relationship that was sustained regardless of distance from the WMH. These multimodal imaging data indicate that WMH have reduced structural integrity compared with surrounding NAWM, and MD provides the best discriminator between the 2 tissue classes even within the mild range of WMH severity, whereas FA, MTR, and T1 only start reflecting significant changes in tissue microstructure as WMH become more severe. PMID:25457555

  4. Cluster imaging of multi-brain networks (CIMBN): a general framework for hyperscanning and modeling a group of interacting brains

    PubMed Central

    Duan, Lian; Dai, Rui-Na; Xiao, Xiang; Sun, Pei-Pei; Li, Zheng; Zhu, Chao-Zhe

    2015-01-01

    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. PMID:26283906

  5. Cluster imaging of multi-brain networks (CIMBN): a general framework for hyperscanning and modeling a group of interacting brains.

    PubMed

    Duan, Lian; Dai, Rui-Na; Xiao, Xiang; Sun, Pei-Pei; Li, Zheng; Zhu, Chao-Zhe

    2015-01-01

    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. PMID:26283906

  6. MicroCT and microMRI imaging of a prenatal mouse model of increased brain size

    NASA Astrophysics Data System (ADS)

    López, Elisabeth K. N.; Stock, Stuart R.; Taketo, Makoto M.; Chenn, Anjen; Ravosa, Matthew J.

    2008-08-01

    There are surprisingly few experimental models of neural growth and cranial integration. This and the dearth of information regarding fetal brain development detract from a mechanistic understanding of cranial integration and its relevance to the patterning of skull form, specifically the role of encephalization on basicranial flexion. To address this shortcoming, our research uses transgenic mice expressing a stabilized form of β-catenin to isolate the effects of relative brain size on craniofacial development. These mice develop highly enlarged brains due to an increase in neural precursors, and differences between transgenic and wild-type mice are predicted to result solely from variation in brain size. Comparisons of wild-type and transgenic mice at several prenatal ages were performed using microCT (Scanco Medical MicroCT 40) and microMRI (Avance 600 WB MR spectrometer). Statistical analyses show that the larger brain of the transgenic mice is associated with a larger neurocranium and an altered basicranial morphology. However, body size and postcranial ossification do not seem to be affected by the transgene. Comparisons of the rate of postcranial and cranial ossification using microCT also point to an unexpected effect of neural growth on skull development: increased fetal encephalization may result in a compensatory decrease in the level of cranial ossification. Therefore, if other life history factors are held constant, the ontogeny of a metabolically costly structure such as a brain may occur at the expense of other cranial structures. These analyses indicate the benefits of a multifactorial approach to cranial integration using a mouse model.

  7. Coastal Ecosystem Integrated Compartment Model (ICM): Modeling Framework

    NASA Astrophysics Data System (ADS)

    Meselhe, E. A.; White, E. D.; Reed, D.

    2015-12-01

    The Integrated Compartment Model (ICM) was developed as part of the 2017 Coastal Master Plan modeling effort. It is a comprehensive and numerical hydrodynamic model coupled to various geophysical process models. Simplifying assumptions related to some of the flow dynamics are applied to increase the computational efficiency of the model. The model can be used to provide insights about coastal ecosystems and evaluate restoration strategies. It builds on existing tools where possible and incorporates newly developed tools where necessary. It can perform decadal simulations (~ 50 years) across the entire Louisiana coast. It includes several improvements over the approach used to support the 2012 Master Plan, such as: additional processes in the hydrology, vegetation, wetland and barrier island morphology subroutines, increased spatial resolution, and integration of previously disparate models into a single modeling framework. The ICM includes habitat suitability indices (HSIs) to predict broad spatial patterns of habitat change, and it provides an additional integration to a dynamic fish and shellfish community model which quantitatively predicts potential changes in important fishery resources. It can be used to estimate the individual and cumulative effects of restoration and protection projects on the landscape, including a general estimate of water levels associated with flooding. The ICM is also used to examine possible impacts of climate change and future environmental scenarios (e.g. precipitation, Eustatic sea level rise, subsidence, tropical storms, etc.) on the landscape and on the effectiveness of restoration projects. The ICM code is publically accessible, and coastal restoration and protection groups interested in planning-level modeling are encouraged to explore its utility as a computationally efficient tool to examine ecosystem response to future physical or ecological changes, including the implementation of restoration and protection strategies.

  8. A mouse model of human repetitive mild traumatic brain injury

    PubMed Central

    Kane, Michael J.; Pérez, Mariana Angoa; Briggs, Denise I.; Viano, David C.; Kreipke, Christian W.; Kuhn, Donald M.

    2011-01-01

    A novel method for the study of repetitive mild traumatic brain injury (rmTBI) that models the most common form of head injury in humans is presented. Existing animal models of TBI impart focal, severe damage unlike that seen in repeated and mild concussive injuries, and few are configured for repetitive application. Our model is a modification of the Marmarou weight drop method and allows repeated head impacts to lightly anesthetized mice. A key facet of this method is the delivery of an impact to the cranium of an unrestrained subject allowing rapid acceleration of the free-moving head and torso, an essential characteristic known to be important for concussive injury in humans, and a factor that is missing from existing animal models of TBI. Our method does not require scalp incision, emplacement of protective skull helmets or surgery and the procedure can be completed in 1-2 minutes. Mice spontaneously recover the righting reflex and show no evidence of seizures, paralysis or impaired behavior. Skull fractures and intracranial bleeding are very rare. Minor deficits in motor coordination and locomotor hyperactivity recover over time. Histological analyses reveal mild astrocytic reactivity (increased expression of GFAP) and increased phospho-tau but a lack of blood-brain-barrier disruption, edema and microglial activation. This new animal model is simple and cost-effective and will facilitate characterization of the neurobiological and behavioral consequences of rmTBI. It is also ideal for high throughput screening of potential new therapies for mild concussive injuries as experienced by athletes and military personnel. PMID:21930157

  9. Endorsement of formal leaders: an integrative model.

    PubMed

    Michener, H A; Lawler, E J

    1975-02-01

    This experiment develops an integrative, path-analytic model for the endorsement accorded formal leaders. The model contains four independent variables reflecting aspects of group structure (i.e., group success-failure, the payoff distribution, the degree of support by others members for the leader, and the vulnerability of the leader). Also included are two intervening variables reflecting perceptual processes (attributed competence and attributed fairness), and one dependent variable endorsement). The results indicate that endorsement is greater when the group's success is high, when the payoff distribution is flat rather than hierarchial, and when the leader is not vulnerable to removal from office. Other support had no significant impact on endorsement. Analyses further demonstrate that the effect of success-failure on endorsement is mediated by attributed competence, while the effect of the payoff distributed is mediated by attributed fairness. These results suggest that moral and task evaluations are distinct bases of endorsement. PMID:1123712

  10. Learning models for multi-source integration

    SciTech Connect

    Tejada, S.; Knoblock, C.A.; Minton, S.

    1996-12-31

    Because of the growing number of information sources available through the internet there are many cases in which information needed to solve a problem or answer a question is spread across several information sources. For example, when given two sources, one about comic books and the other about super heroes, you might want to ask the question {open_quotes}Is Spiderman a Marvel Super Hero?{close_quotes} This query accesses both sources; therefore, it is necessary to have information about the relationships of the data within each source and between sources to properly access and integrate the data retrieved. The SIMS information broker captures this type of information in the form of a model. All the information sources map into the model providing the user a single interface to multiple sources.

  11. Performance of an integrated network model

    PubMed Central

    Lehmann, François; Dunn, David; Beaulieu, Marie-Dominique; Brophy, James

    2016-01-01

    Objective To evaluate the changes in accessibility, patients’ care experiences, and quality-of-care indicators following a clinic’s transformation into a fully integrated network clinic. Design Mixed-methods study. Setting Verdun, Que. Participants Data on all patient visits were used, in addition to 2 distinct patient cohorts: 134 patients with chronic illness (ie, diabetes, arteriosclerotic heart disease, or both); and 450 women between the ages of 20 and 70 years. Main outcome measures Accessibility was measured by the number of walk-in visits, scheduled visits, and new patient enrolments. With the first cohort, patients’ care experiences were measured using validated serial questionnaires; and quality-of-care indicators were measured using biologic data. With the second cohort, quality of preventive care was measured using the number of Papanicolaou tests performed as a surrogate marker. Results Despite a negligible increase in the number of physicians, there was an increase in accessibility after the clinic’s transition to an integrated network model. During the first 4 years of operation, the number of scheduled visits more than doubled, nonscheduled visits (walk-in visits) increased by 29%, and enrolment of vulnerable patients (those with chronic illnesses) at the clinic remained high. Patient satisfaction with doctors was rated very highly at all points of time that were evaluated. While the number of Pap tests done did not increase with time, the proportion of patients meeting hemoglobin A1c and low-density lipoprotein guideline target levels increased, as did the number of patients tested for microalbuminuria. Conclusion Transformation to an integrated network model of care led to increased efficiency and enhanced accessibility with no negative effects on the doctor-patient relationship. Improvements in biologic data also suggested better quality of care. PMID:27521410

  12. Building integral projection models: a user's guide

    PubMed Central

    Rees, Mark; Childs, Dylan Z; Ellner, Stephen P; Coulson, Tim

    2014-01-01

    In order to understand how changes in individual performance (growth, survival or reproduction) influence population dynamics and evolution, ecologists are increasingly using parameterized mathematical models. For continuously structured populations, where some continuous measure of individual state influences growth, survival or reproduction, integral projection models (IPMs) are commonly used. We provide a detailed description of the steps involved in constructing an IPM, explaining how to: (i) translate your study system into an IPM; (ii) implement your IPM; and (iii) diagnose potential problems with your IPM. We emphasize how the study organism's life cycle, and the timing of censuses, together determine the structure of the IPM kernel and important aspects of the statistical analysis used to parameterize an IPM using data on marked individuals. An IPM based on population studies of Soay sheep is used to illustrate the complete process of constructing, implementing and evaluating an IPM fitted to sample data. We then look at very general approaches to parameterizing an IPM, using a wide range of statistical techniques (e.g. maximum likelihood methods, generalized additive models, nonparametric kernel density estimators). Methods for selecting models for parameterizing IPMs are briefly discussed. We conclude with key recommendations and a brief overview of applications that extend the basic model. The online Supporting Information provides commented R code for all our analyses. PMID:24219157

  13. Describing Ecosystem Complexity through Integrated Catchment Modeling

    NASA Astrophysics Data System (ADS)

    Shope, C. L.; Tenhunen, J. D.; Peiffer, S.

    2011-12-01

    Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.

  14. Search of novel model for integrative medicine.

    PubMed

    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. PMID:24615209

  15. Impact Acceleration Model of Diffuse Traumatic Brain Injury.

    PubMed

    Hellewell, Sarah C; Ziebell, Jenna M; Lifshitz, Jonathan; Morganti-Kossmann, M Cristina

    2016-01-01

    The impact acceleration (I/A) model of traumatic brain injury (TBI) was developed to reliably induce diffuse traumatic axonal injury in rats in the absence of skull fractures and parenchymal focal lesions. This model replicates a pathophysiology that is commonly observed in humans with diffuse axonal injury (DAI) caused by acceleration-deceleration forces. Such injuries are typical consequences of motor vehicle accidents and falls, which do not necessarily require a direct impact to the closed skull. There are several desirable characteristics of the I/A model, including the extensive axonal injury produced in the absence of a focal contusion, the suitability for secondary insult modeling, and the adaptability for mild/moderate injury through alteration of height and/or weight. Furthermore, the trauma device is inexpensive and readily manufactured in any laboratory, and the induction of injury is rapid (~45 min per animal from weighing to post-injury recovery) allowing multiple animal experiments per day. In this chapter, we describe in detail the methodology and materials required to produce the rat model of I/A in the laboratory. We also review current adaptations to the model to alter injury severity, discuss frequent complications and technical issues encountered using this model, and provide recommendations to ensure technically sound injury induction. PMID:27604723

  16. Physical Exercise Keeps the Brain Connected: Biking Increases White Matter Integrity in Patients With Schizophrenia and Healthy Controls.

    PubMed

    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. PMID:25829377

  17. Physical Exercise Keeps the Brain Connected: Biking Increases White Matter Integrity in Patients With Schizophrenia and Healthy Controls

    PubMed Central

    Svatkova, Alena; Mandl, René C.W.; Scheewe, Thomas W.; Cahn, Wiepke; Kahn, René S.; Hulshoff Pol, Hilleke E.

    2015-01-01

    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. PMID:25829377

  18. Planarian brain regeneration as a model system for developmental neurotoxicology

    PubMed Central

    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

  19. Rodent Models of Traumatic Brain Injury: Methods and Challenges.

    PubMed

    Marklund, Niklas

    2016-01-01

    Traumatic brain injury (TBI) has been named the most complex disease in the most complex organ of the body. It is the most common cause of death and disability in the Western world in people <40 years old and survivors commonly suffer from persisting cognitive deficits, impaired motor function, depression and personality changes. TBI may vary in severity from uniformly fatal to mild injuries with rapidly resolving symptoms and without doubt, it is a markedly heterogeneous disease. Its different subtypes differs in their pathophysiology, treatment options and long-term consequences and to date, there are no pharmacological treatments with proven clinical benefit available to TBI patients. To enable development of novel treatment options for TBI, clinically relevant animal models are needed. Due to their availability and low costs, numerous rodent models have been developed which have substantially contributed to our current understanding of the pathophysiology of TBI. The most common animal models used in laboratories worldwide are likely the controlled cortical impact (CCI) model, the central and lateral fluid percussion injury (FPI) models, and weight drop/impact acceleration (I/A) models. Each of these models has inherent advantages and disadvantages; these need to be thoroughly considered when selecting the rodent TBI model according to the hypothesis and design of the study. Since TBI is not one disease, refined animal models must take into account the clinical features and complexity of human TBI. To enhance the possibility of establishing preclinical efficacy of a novel treatment, the preclinical use of several different experimental models is encouraged as well as varying the species, gender, and age of the animal. In this chapter, the methods, limitations, and challenges of the CCI and FPI models of TBI used in rodents are described. PMID:27604711

  20. Advances in NLTE modeling for integrated simulations

    NASA Astrophysics Data System (ADS)

    Scott, H. A.; Hansen, S. B.

    2010-01-01

    The last few years have seen significant progress in constructing the atomic models required for non-local thermodynamic equilibrium (NLTE) simulations. Along with this has come an increased understanding of the requirements for accurately modeling the ionization balance, energy content and radiative properties of different atomic species for a wide range of densities and temperatures. Much of this progress is the result of a series of workshops dedicated to comparing the results from different codes and computational approaches applied to a series of test problems. The results of these workshops emphasized the importance of atomic model completeness, especially in doubly-excited states and autoionization transitions, to calculating ionization balance, and the importance of accurate, detailed atomic data to producing reliable spectra. We describe a simple screened-hydrogenic model that calculates NLTE ionization balance with sufficient accuracy, at a low enough computational cost for routine use in radiation-hydrodynamics codes. The model incorporates term splitting, Δ n = 0 transitions, and approximate UTA widths for spectral calculations, with results comparable to those of much more detailed codes. Simulations done with this model have been increasingly successful at matching experimental data for laser-driven systems and hohlraums. Accurate and efficient atomic models are just one requirement for integrated NLTE simulations. Coupling the atomic kinetics to hydrodynamics and radiation transport constrains both discretizations and algorithms to retain energy conservation, accuracy and stability. In particular, the strong coupling between radiation and populations can require either very short time steps or significantly modified radiation transport algorithms to account for NLTE material response. Considerations such as these continue to provide challenges for NLTE simulations.

  1. Dendrimer Brain Uptake and Targeted Therapy for Brain Injury in a Large Animal Model of Hypothermic Circulatory Arrest

    PubMed Central

    2015-01-01

    Treatment of brain injury following circulatory arrest is a challenging health issue with no viable therapeutic options. Based on studies in a clinically relevant large animal (canine) model of hypothermic circulatory arrest (HCA)-induced brain injury, neuroinflammation and excitotoxicity have been identified as key players in mediating the brain injury after HCA. Therapy with large doses of valproic acid (VPA) showed some neuroprotection but was associated with adverse side effects. For the first time in a large animal model, we explored whether systemically administered polyamidoamine (PAMAM) dendrimers could be effective in reaching target cells in the brain and deliver therapeutics. We showed that, upon systemic administration, hydroxyl-terminated PAMAM dendrimers are taken up in the brain of injured animals and selectively localize in the injured neurons and microglia in the brain. The biodistribution in other major organs was similar to that seen in small animal models. We studied systemic dendrimer–drug combination therapy with two clinically approved drugs, N-acetyl cysteine (NAC) (attenuating neuroinflammation) and valproic acid (attenuating excitotoxicity), building on positive outcomes in a rabbit model of perinatal brain injury. We prepared and characterized dendrimer-NAC (D-NAC) and dendrimer-VPA (D-VPA) conjugates in multigram quantities. A glutathione-sensitive linker to enable for fast intracellular release. In preliminary efficacy studies, combination therapy with D-NAC and D-VPA showed promise in this large animal model, producing 24 h neurological deficit score improvements comparable to high dose combination therapy with VPA and NAC, or free VPA, but at one-tenth the dose, while significantly reducing the adverse side effects. Since adverse side effects of drugs are exaggerated in HCA, the reduced side effects with dendrimer conjugates and suggestions of neuroprotection offer promise for these nanoscale drug delivery systems. PMID:24499315

  2. Multistability in Large Scale Models of Brain Activity.

    PubMed

    Golos, Mathieu; Jirsa, Viktor; Daucé, Emmanuel

    2015-12-01

    Noise driven exploration of a brain network's dynamic repertoire has been hypothesized to be causally involved in cognitive function, aging and neurodegeneration. The dynamic repertoire crucially depends on the network's capacity to store patterns, as well as their stability. Here we systematically explore the capacity of networks derived from human connectomes to store attractor states, as well as various network mechanisms to control the brain's dynamic repertoire. Using a deterministic graded response Hopfield model with connectome-based interactions, we reconstruct the system's attractor space through a uniform sampling of the initial conditions. Large fixed-point attractor sets are obtained in the low temperature condition, with a bigger number of attractors than ever reported so far. Different variants of the initial model, including (i) a uniform activation threshold or (ii) a global negative feedback, produce a similarly robust multistability in a limited parameter range. A numerical analysis of the distribution of the attractors identifies spatially-segregated components, with a centro-medial core and several well-delineated regional patches. Those different modes share similarity with the fMRI independent components observed in the "resting state" condition. We demonstrate non-stationary behavior in noise-driven generalizations of the models, with different meta-stable attractors visited along the same time course. Only the model with a global dynamic density control is found to display robust and long-lasting non-stationarity with no tendency toward either overactivity or extinction. The best fit with empirical signals is observed at the edge of multistability, a parameter region that also corresponds to the highest entropy of the attractors. PMID:26709852

  3. Language Model Applications to Spelling with Brain-Computer Interfaces

    PubMed Central

    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

  4. The Bee as a Model to Investigate Brain and Behavioural Asymmetries

    PubMed Central

    Frasnelli, Elisa; Haase, Albrecht; Rigosi, Elisa; Anfora, Gianfranco; Rogers, Lesley J.; Vallortigara, Giorgio

    2014-01-01

    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. PMID:26462583

  5. The Bee as a Model to Investigate Brain and Behavioural Asymmetries.

    PubMed

    Frasnelli, Elisa; Haase, Albrecht; Rigosi, Elisa; Anfora, Gianfranco; Rogers, Lesley J; Vallortigara, Giorgio

    2014-01-01

    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. PMID:26462583

  6. An implantable integrated low-power amplifier-microelectrode array for Brain-Machine Interfaces.

    PubMed

    Patrick, Erin; Sankar, Viswanath; Rowe, William; Sanchez, Justin C; Nishida, Toshikazu

    2010-01-01

    One of the important challenges in designing Brain-Machine Interfaces (BMI) is to build implantable systems that have the ability to reliably process the activity of large ensembles of cortical neurons. In this paper, we report the design, fabrication, and testing of a polyimide-based microelectrode array integrated with a low-power amplifier as part of the Florida Wireless Integrated Recording Electrode (FWIRE) project at the University of Florida developing a fully implantable neural recording system for BMI applications. The electrode array was fabricated using planar micromachining MEMS processes and hybrid packaged with the amplifier die using a flip-chip bonding technique. The system was tested both on bench and in-vivo. Acute and chronic neural recordings were obtained from a rodent for a period of 42 days. The electrode-amplifier performance was analyzed over the chronic recording period with the observation of a noise floor of 4.5 microVrms, and an average signal-to-noise ratio of 3.8. PMID:21095940

  7. Hearing facial identities: brain correlates of face--voice integration in person identification.

    PubMed

    Schweinberger, Stefan R; Kloth, Nadine; Robertson, David M C

    2011-10-01

    Audiovisual integration (AVI) is a well-known aspect of speech perception, but integration of facial and vocal information is also important for speaker recognition. We recently demonstrated AVI in the recognition of familiar (but not unfamiliar) speakers. Specifically, systematic behavioural benefits and costs in recognizing a familiar voice occur when the voice is combined with a time-synchronised articulating face of corresponding or noncorresponding speaker identity, respectively (Schweinberger et al., 2007; Robertson and Schweinberger, 2010). Here we report an experiment assessing event-related brain potentials (ERPs) in this novel paradigm, while participants recognized familiar speakers presented in (1) Voice only, (2) voice with identity-corresponding and (3) noncorresponding time-synchronised speaking faces, as well as (4) Face only conditions. Audiovisual speaker identity correspondence influenced only later ERPs around 250-600 msec, with increased negativity for noncorresponding identities at central electrodes. Strikingly, when compared with the ERPs from both unimodal conditions, both audiovisual conditions led to a much earlier onset of frontocentral negativity, with maximal differences around 50-80 msec. Moreover, audiovisual stimuli elicited larger N170 responses than Face only stimuli. These findings suggest that the perception of a voice and a time-synchronised articulating face triggers remarkably early and mandatory mechanisms of audiovisual processing, although the correspondence or discrepancy in audiovisual speaker identity may only be computed ∼200msec later. PMID:21208611

  8. Integrating Visualizations into Modeling NEST Simulations

    PubMed Central

    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

  9. Regional brain metabolism in a murine systemic lupus erythematosus model.

    PubMed

    Vo, An; Volpe, Bruce T; Tang, Chris C; Schiffer, Wynne K; Kowal, Czeslawa; Huerta, Patricio T; Uluğ, Aziz M; Dewey, Stephen L; Eidelberg, David; Diamond, Betty

    2014-08-01

    Systemic lupus erythematosus (SLE) is characterized by multiorgan inflammation, neuropsychiatric disorders (NPSLE), and anti-nuclear antibodies. We previously identified a subset of anti-DNA antibodies (DNRAb) cross-reactive with the N-methyl-D-aspartate receptor, present in 30% to 40% of patients, able to enhance excitatory post-synaptic potentials and trigger neuronal apoptosis. DNRAb+ mice exhibit memory impairment or altered fear response, depending on whether the antibody penetrates the hippocampus or amygdala. Here, we used 18F-fluorodeoxyglucose (FDG) microPET to plot changes in brain metabolism after regional blood-brain barrier (BBB) breach. In DNRAb+ mice, metabolism declined at the site of BBB breach in the first 2 weeks and increased over the next 2 weeks. In contrast, DNRAb- mice exhibited metabolic increases in these regions over the 4 weeks after the insult. Memory impairment was present in DNRAb+ animals with hippocampal BBB breach and altered fear conditioning in DNRAb+ mice with amygdala BBB breach. In DNRAb+ mice, we observed an inverse relationship between neuron number and regional metabolism, while a positive correlation was observed in DNRAb- mice. These findings suggest that local metabolic alterations in this model take place through different mechanisms with distinct time courses, with important implications for the interpretation of imaging data in SLE subjects. PMID:24824914

  10. Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture

    PubMed Central

    Arbib, Michael; Ganesh, Varsha; Gasser, Brad

    2014-01-01

    The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape. PMID:24778382

  11. On the appropriateness of modelling brain parenchyma as a biphasic continuum.

    PubMed

    Tavner, A C R; Roy, T Dutta; Hor, K W W; Majimbi, M; Joldes, G R; Wittek, A; Bunt, S; Miller, K

    2016-08-01

    Computational methods originally developed for analysis in engineering have been applied to the analysis of biological materials for many years. One particular application of these engineering tools is the brain, allowing researchers to predict the behaviour of brain tissue in various traumatic, surgical and medical scenarios. Typically two different approaches have been used to model deformation of brain tissue: single-phase models which treat the brain as a viscoelastic material, and biphasic models which treat the brain as a porous deformable medium through which liquid can move. In order to model the brain as a biphasic continuum, the hydraulic conductivity of the solid phase is required; there are many theoretical values for this conductivity in the literature, with variations of up to three orders of magnitude. We carried out a series of simple experiments using lamb and sheep brain tissue to establish the rate at which cerebrospinal fluid moves through the brain parenchyma. Mindful of possible variations in hydraulic conductivity with tissue deformation, our intention was to carry out our experiments on brain tissue subjected to minimal deformation. This has enabled us to compare the rate of flow with values predicted by some of the theoretical values of hydraulic conductivity from the literature. Our results indicate that the hydraulic conductivity of the brain parenchyma is consistent with the lowest theoretical published values. These extremely low hydraulic conductivities lead to such low rates of CSF flow through the brain tissue that in effect the material behaves as a single-phase deformable solid. PMID:27136087

  12. Computational modeling of pedunculopontine nucleus deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Zitella, Laura M.; Mohsenian, Kevin; Pahwa, Mrinal; Gloeckner, Cory; Johnson, Matthew D.

    2013-08-01

    Objective. Deep brain stimulation (DBS) near the pedunculopontine nucleus (PPN) has been posited to improve medication-intractable gait and balance problems in patients with Parkinson's disease. However, clinical studies evaluating this DBS target have not demonstrated consistent therapeutic effects, with several studies reporting the emergence of paresthesia and oculomotor side effects. The spatial and pathway-specific extent to which brainstem regions are modulated during PPN-DBS is not well understood. Approach. Here, we describe two computational models that estimate the direct effects of DBS in the PPN region for human and translational non-human primate (NHP) studies. The three-dimensional models were constructed from segmented histological images from each species, multi-compartment neuron models and inhomogeneous finite element models of the voltage distribution in the brainstem during DBS. Main Results. The computational models predicted that: (1) the majority of PPN neurons are activated with -3 V monopolar cathodic stimulation; (2) surgical targeting errors of as little as 1 mm in both species decrement activation selectivity; (3) specifically, monopolar stimulation in caudal, medial, or anterior PPN activates a significant proportion of the superior cerebellar peduncle (up to 60% in the human model and 90% in the NHP model at -3 V) (4) monopolar stimulation in rostral, lateral or anterior PPN activates a large percentage of medial lemniscus fibers (up to 33% in the human model and 40% in the NHP model at -3 V) and (5) the current clinical cylindrical electrode design is suboptimal for isolating the modulatory effects to PPN neurons. Significance. We show that a DBS lead design with radially-segmented electrodes may yield improved functional outcome for PPN-DBS.

  13. A model for traumatic brain injury using laser induced shockwaves

    NASA Astrophysics Data System (ADS)

    Selfridge, A.; Preece, D.; Gomez, V.; Shi, L. Z.; Berns, M. W.

    2015-08-01

    Traumatic brain injury (TBI) represents a major treatment challenge in both civilian and military medicine; on the cellular level, its mechanisms are poorly understood. As a method to study the dysfunctional repair mechanisms following injury, laser induced shock waves (LIS) are a useful way to create highly precise, well characterized mechanical forces. We present a simple model for TBI using laser induced shock waves as a model for damage. Our objective is to develop an understanding of the processes responsible for neuronal death, the ways in which we can manipulate these processes to improve cell survival and repair, and the importance of these processes at different levels of biological organization. The physics of shock wave creation has been modeled and can be used to calculate forces acting on individual neurons. By ensuring that the impulse is in the same regime as that occurring in practical TBI, the LIS model can ensure that in vitro conditions and damage are similar to those experienced in TBI. This model will allow for the study of the biochemical response of neurons to mechanical stresses, and can be combined with microfluidic systems for cell growth in order to better isolate areas of damage.

  14. Prioritizing the development of mouse models for childhood brain disorders.

    PubMed

    Ogden, Kevin K; Ozkan, Emin D; Rumbaugh, Gavin

    2016-01-01

    Mutations in hundreds of genes contribute to cognitive and behavioral dysfunction associated with developmental brain disorders (DBDs). Due to the sheer number of risk factors available for study combined with the cost of developing new animal models, it remains an open question how genes should be prioritized for in-depth neurobiological investigations. Recent reviews have argued that priority should be given to frequently mutated genes commonly found in sporadic DBD patients. Intrigued by this idea, we explored to what extent "high priority" risk factors have been studied in animals in an effort to assess their potential for generating valuable preclinical models capable of advancing the neurobiological understanding of DBDs. We found that in-depth whole animal studies are lacking for many high priority genes, with relatively few neurobiological studies performed in construct valid animal models aimed at understanding the pathological substrates associated with disease phenotypes. However, some high priority risk factors have been extensively studied in animal models and they have generated novel insights into DBD patho-neurobiology while also advancing early pre-clinical therapeutic treatment strategies. We suggest that prioritizing model development toward genes frequently mutated in non-specific DBD populations will accelerate the understanding of DBD patho-neurobiology and drive novel therapeutic strategies. This article is part of the Special Issue entitled 'Synaptopathy--from Biology to Therapy'. PMID:26231830

  15. Classification of integrable discrete Klein-Gordon models

    NASA Astrophysics Data System (ADS)

    Habibullin, Ismagil T.; Gudkova, Elena V.

    2011-04-01

    The Lie algebraic integrability test is applied to the problem of classification of integrable Klein-Gordon-type equations on quad graphs. The list of equations passing the test is presented, containing several well-known integrable models. A new integrable example is found; its higher symmetry is presented.

  16. Pharmacokinetic Modeling of Non-Linear Brain Distribution of Fluvoxamine in the Rat

    PubMed Central

    Geldof, Marian; Freijer, Jan; van Beijsterveldt, Ludy

    2007-01-01

    Introduction A pharmacokinetic (PK) model is proposed for estimation of total and free brain concentrations of fluvoxamine. Materials and methods Rats with arterial and venous cannulas and a microdialysis probe in the frontal cortex received intravenous infusions of 1, 3.7 or 7.3 mg.kg−1 of fluvoxamine. Analysis With increasing dose a disproportional increase in brain concentrations was observed. The kinetics of brain distribution was estimated by simultaneous analysis of plasma, free brain ECF and total brain tissue concentrations. The PK model consists of three compartments for fluvoxamine concentrations in plasma in combination with a catenary two compartment model for distribution into the brain. In this catenary model, the mass exchange between a shallow perfusion-limited and a deep brain compartment is described by a passive diffusion term and a saturable active efflux term. Results The model resulted in precise estimates of the parameters describing passive influx into (kin) of 0.16 min−1 and efflux from the shallow brain compartment (kout) of 0.019 min−1 and the fluvoxamine concentration at which 50% of the maximum active efflux (C50) is reached of 710 ng.ml−1. The proposed brain distribution model constitutes a basis for precise characterization of the PK–PD correlation of fluvoxamine by taking into account the non-linearity in brain distribution. PMID:17710515

  17. Build-a-Brain Project: Students Design and Model the Brain of an Imaginary Animal

    ERIC Educational Resources Information Center

    Demetrikopoulos, Melissa K.; Pecore, John; Rose, Jordan D.; Fobbs, Archibald J., Jr.; Johnson, John I.; Carruth, Laura L.

    2006-01-01

    The brain is a truly fascinating structure! It controls the body and allows everyone to think, learn, speak, move, feel, remember, and experience emotions. Although the brain is a single organ, it is very complex and has several regions, each having a specific function. These functionally diverse regions work together to allow for coordination of…

  18. Transcending Right Brain/Left Brain Boundaries: The Teacher as Model.

    ERIC Educational Resources Information Center

    Bump, Jerome

    One of the deepest and most debilitating schisms in the university classroom, as in life, is that between the left and right sides of the brain, reason and emotion, the head and the heart. More and more college English teachers have become aware of the value of addressing the whole brain, the whole person. Teachers set up goals and communicate…

  19. Chapter 3 animal models of traumatic brain injury: is there an optimal model that parallels human brain injury?

    PubMed

    Briones, Teresita L

    2015-01-01

    Traumatic brain injury (TBI) is the leading cause of mortality and morbidity in the younger population worldwide. Survivors of TBI often experience long-term disability in the form of cognitive, sensorimotor, and affective impairments. Despite the high prevalence in, and cost of TBI to, both individuals and society, some of its underlying pathophysiology is not completely understood. Animal models have been developed over the past few decades to closely replicate the different facets of TBI in humans to better understand the underlying pathophysiology and behavioral impairments and assess potential therapies that can promote neuroprotection. However, no effective treatment for TBI has been established to date in the clinical setting, despite promising results generated in preclinical studies in the use of neuroprotective strategies. The failure to translate results from preclinical studies to the clinical setting underscores a compelling need to revisit the current state of knowledge in the use of animal models in TBI. PMID:25946383

  20. Knowledge Modeling for the Outcome of Brain Stereotactic Radiosurgery

    NASA Astrophysics Data System (ADS)

    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

  1. Integrating histology and MRI in the first digital brain of common squirrel monkey, Saimiri sciureus

    PubMed Central

    Sun, Peizhen; Parvathaneni, Prasanna; Schilling, Kurt G.; Gao, Yurui; Janve, Vaibhav; Anderson, Adam; Landman, Bennett A.

    2015-01-01

    This effort is a continuation of development of a digital brain atlas of the common squirrel monkey, Saimiri sciureus, a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. Here, we present the integration of histology with multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. The central concept of this work is to use block face photography to establish an intermediate common space in coordinate system which preserves the high resolution in-plane resolution of histology while enabling 3-D correspondence with MRI. In vivo MRI acquisitions include high resolution T2 structural imaging (300 µm isotropic) and low resolution diffusion tensor imaging (600 um isotropic). Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging (both 300 µm isotropic). Cortical regions were manually annotated on the co-registered volumes based on published histological sections in-plane. We describe mapping of histology and MRI based data of the common squirrel monkey and construction of a viewing tool that enable online viewing of these datasets. The previously descried atlas MRI is used for its deformation to provide accurate conformation to the MRI, thus adding information at the histological level to the MRI volume. This paper presents the mapping of single 2D image slice in block face as a proof of concept and this can be extended to map the atlas space in 3D coordinate system as part of the future work and can be loaded to an XNAT system for further use. PMID:25914510

  2. Integrating histology and MRI in the first digital brain of common squirrel monkey, Saimiri sciureus

    NASA Astrophysics Data System (ADS)

    Sun, Peizhen; Parvathaneni, Prasanna; Schilling, Kurt G.; Gao, Yurui; Janve, Vaibhav; Anderson, Adam; Landman, Bennett A.

    2015-03-01

    This effort is a continuation of development of a digital brain atlas of the common squirrel monkey, Saimiri sciureus, a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. Here, we present the integration of histology with multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. The central concept of this work is to use block face photography to establish an intermediate common space in coordinate system which preserves the high resolution in-plane resolution of histology while enabling 3-D correspondence with MRI. In vivo MRI acquisitions include high resolution T2 structural imaging (300 μm isotropic) and low resolution diffusion tensor imaging (600 um isotropic). Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging (both 300 μm isotropic). Cortical regions were manually annotated on the co-registered volumes based on published histological sections in-plane. We describe mapping of histology and MRI based data of the common squirrel monkey and construction of a viewing tool that enable online viewing of these datasets. The previously descried atlas MRI is used for its deformation to provide accurate conformation to the MRI, thus adding information at the histological level to the MRI volume. This paper presents the mapping of single 2D image slice in block face as a proof of concept and this can be extended to map the atlas space in 3D coordinate system as part of the future work and can be loaded to an XNAT system for further use.

  3. HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity.

    PubMed

    Niso, Guiomar; Bruña, Ricardo; Pereda, Ernesto; Gutiérrez, Ricardo; Bajo, Ricardo; Maestú, Fernando; del-Pozo, Francisco

    2013-10-01

    The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the 'traditional' set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality.This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox.Here we present HERMES ( http://hermes.ctb.upm.es ), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis. PMID:23812847

  4. Colloids as Mobile Substrates for the Implantation and Integration of Differentiated Neurons into the Mammalian Brain

    PubMed Central

    Jgamadze, Dennis; Bergen, Jamie; Stone, Daniel; Jang, Jae-Hyung; Schaffer, David V.; Isacoff, Ehud Y.; Pautot, Sophie

    2012-01-01

    Neuronal degeneration and the deterioration of neuronal communication lie at the origin of many neuronal disorders, and there have been major efforts to develop cell replacement therapies for treating such diseases. One challenge, however, is that differentiated cells are challenging to transplant due to their sensitivity both to being uprooted from their cell culture growth support and to shear forces inherent in the implantation process. Here, we describe an approach to address these problems. We demonstrate that rat hippocampal neurons can be grown on colloidal particles or beads, matured and even transfected in vitro, and subsequently transplanted while adhered to the beads into the young adult rat hippocampus. The transplanted cells have a 76% cell survival rate one week post-surgery. At this time, most transplanted neurons have left their beads and elaborated long processes, similar to the host neurons. Additionally, the transplanted cells distribute uniformly across the host hippocampus. Expression of a fluorescent protein and the light-gated glutamate receptor in the transplanted neurons enabled them to be driven to fire by remote optical control. At 1-2 weeks after transplantation, calcium imaging of host brain slice shows that optical excitation of the transplanted neurons elicits activity in nearby host neurons, indicating the formation of functional transplant-host synaptic connections. After 6 months, the transplanted cell survival and overall cell distribution remained unchanged, suggesting that cells are functionally integrated. This approach, which could be extended to other cell classes such as neural stem cells and other regions of the brain, offers promising prospects for neuronal circuit repair via transplantation of in vitro differentiated, genetically engineered neurons. PMID:22295079

  5. Tracer kinetic modelling for DCE-MRI quantification of subtle blood–brain barrier permeability

    PubMed Central

    Heye, Anna K.; Thrippleton, Michael J.; Armitage, Paul A.; Valdés Hernández, Maria del C.; Makin, Stephen D.; Glatz, Andreas; Sakka, Eleni; Wardlaw, Joanna M.

    2016-01-01

    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 KTrans 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

  6. Mapping Metabolic Brain Activity in Three Models of Hepatic Encephalopathy

    PubMed Central

    Méndez, Marta; Fidalgo, Camino; Aller, María Ángeles; Arias, Jaime; Arias, Jorge L.

    2013-01-01

    Cirrhosis is a common disease in Western countries. Liver failure, hyperammonemia, and portal hypertension are the main factors that contribute to human cirrhosis that frequently leads to a neuropsychiatric disorder known as hepatic encephalopathy (HE). In this study, we examined the differential contribution of these leading factors to the oxidative metabolism of diverse brain limbic system regions frequently involved in memory process by histochemical labelling of cytochrome oxidase (COx). We have analyzed cortical structures such as the infralimbic and prelimbic cotices, subcortical structures such as hippocampus and ventral striatum, at thalamic level like the anterodorsal, anteroventral, and mediodorsal thalamus, and, finally, the hypothalamus, where the mammillary nuclei (medial and lateral) were measured. The severest alteration is found in the model that mimics intoxication by ammonia, followed by the thioacetamide-treated group and the portal hypertension group. No changes were found at the mammillary bodies for any of the experimental groups. PMID:23573412

  7. Informing Pedagogy Through the Brain-Targeted Teaching Model

    PubMed Central

    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. PMID:23653775

  8. Brain/MINDS: brain-mapping project in Japan

    PubMed Central

    Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

    2015-01-01

    There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas. PMID:25823872

  9. Modeling fluctuations in default-mode brain network using a spiking neural network.

    PubMed

    Yamanishi, Teruya; Liu, Jian-Qin; Nishimura, Haruhiko

    2012-08-01

    Recently, numerous attempts have been made to understand the dynamic behavior of complex brain systems using neural network models. The fluctuations in blood-oxygen-level-dependent (BOLD) brain signals at less than 0.1 Hz have been observed by functional magnetic resonance imaging (fMRI) for subjects in a resting state. This phenomenon is referred to as a "default-mode brain network." In this study, we model the default-mode brain network by functionally connecting neural communities composed of spiking neurons in a complex network. Through computational simulations of the model, including transmission delays and complex connectivity, the network dynamics of the neural system and its behavior are discussed. The results show that the power spectrum of the modeled fluctuations in the neuron firing patterns is consistent with the default-mode brain network's BOLD signals when transmission delays, a characteristic property of the brain, have finite values in a given range. PMID:22830966

  10. Toward an autonomous brain machine interface: integrating sensorimotor reward modulation and reinforcement learning.

    PubMed

    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. PMID:25972167

  11. Integrating Polarities: A Model for Growth.

    ERIC Educational Resources Information Center

    Long, Vonda Olson

    1984-01-01

    Suggests that the learning of sex roles is based on a bipolar dichotomy of gender-appropriate behaviors. Response alternatives are discussed including the single polarity, bipolar acceptance, and integration of polarities. Contends that integration is essential for growth. (JAC)

  12. Cell proliferation and apoptosis in optic nerve and brain integration centers of adult trout Oncorhynchus mykiss after optic nerve injury

    PubMed Central

    Pushchina, Evgeniya V.; Shukla, Sachin; Varaksin, Anatoly A.; Obukhov, Dmitry K.

    2016-01-01

    Fishes have remarkable ability to effectively rebuild the structure of nerve cells and nerve fibers after central nervous system injury. However, the underlying mechanism is poorly understood. In order to address this issue, we investigated the proliferation and apoptosis of cells in contralateral and ipsilateral optic nerves, after stab wound injury to the eye of an adult trout Oncorhynchus mykiss. Heterogenous population of proliferating cells was investigated at 1 week after injury. TUNEL labeling gave a qualitative and quantitative assessment of apoptosis in the cells of optic nerve of trout 2 days after injury. After optic nerve injury, apoptotic response was investigated, and mass patterns of cell migration were found. The maximal concentration of apoptotic bodies was detected in the areas of mass clumps of cells. It is probably indicative of massive cell death in the area of high phagocytic activity of macrophages/microglia. At 1 week after optic nerve injury, we observed nerve cell proliferation in the trout brain integration centers: the cerebellum and the optic tectum. In the optic tectum, proliferating cell nuclear antigen (PCNA)-immunopositive radial glia-like cells were identified. Proliferative activity of nerve cells was detected in the dorsal proliferative (matrix) area of the cerebellum and in parenchymal cells of the molecular and granular layers whereas local clusters of undifferentiated cells which formed neurogenic niches were observed in both the optic tectum and cerebellum after optic nerve injury. In vitro analysis of brain cells of trout showed that suspension cells compared with monolayer cells retain higher proliferative activity, as evidenced by PCNA immunolabeling. Phase contrast observation showed mitosis in individual cells and the formation of neurospheres which gradually increased during 1–4 days of culture. The present findings suggest that trout can be used as a novel model for studying neuronal regeneration. PMID:27212918

  13. Cell proliferation and apoptosis in optic nerve and brain integration centers of adult trout Oncorhynchus mykiss after optic nerve injury.

    PubMed

    Pushchina, Evgeniya V; Shukla, Sachin; Varaksin, Anatoly A; Obukhov, Dmitry K

    2016-04-01

    Fishes have remarkable ability to effectively rebuild the structure of nerve cells and nerve fibers after central nervous system injury. However, the underlying mechanism is poorly understood. In order to address this issue, we investigated the proliferation and apoptosis of cells in contralateral and ipsilateral optic nerves, after stab wound injury to the eye of an adult trout Oncorhynchus mykiss. Heterogenous population of proliferating cells was investigated at 1 week after injury. TUNEL labeling gave a qualitative and quantitative assessment of apoptosis in the cells of optic nerve of trout 2 days after injury. After optic nerve injury, apoptotic response was investigated, and mass patterns of cell migration were found. The maximal concentration of apoptotic bodies was detected in the areas of mass clumps of cells. It is probably indicative of massive cell death in the area of high phagocytic activity of macrophages/microglia. At 1 week after optic nerve injury, we observed nerve cell proliferation in the trout brain integration centers: the cerebellum and the optic tectum. In the optic tectum, proliferating cell nuclear antigen (PCNA)-immunopositive radial glia-like cells were identified. Proliferative activity of nerve cells was detected in the dorsal proliferative (matrix) area of the cerebellum and in parenchymal cells of the molecular and granular layers whereas local clusters of undifferentiated cells which formed neurogenic niches were observed in both the optic tectum and cerebellum after optic nerve injury. In vitro analysis of brain cells of trout showed that suspension cells compared with monolayer cells retain higher proliferative activity, as evidenced by PCNA immunolabeling. Phase contrast observation showed mitosis in individual cells and the formation of neurospheres which gradually increased during 1-4 days of culture. The present findings suggest that trout can be used as a novel model for studying neuronal regeneration. PMID:27212918

  14. Integrated Environmental Modelling: human decisions, human challenges

    USGS Publications Warehouse

    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.

  15. Identification of an essential endogenous regulator of blood–brain barrier integrity, and its pathological and therapeutic implications

    PubMed Central

    Cristante, Enrico; McArthur, Simon; Mauro, Claudio; Maggioli, Elisa; Romero, Ignacio A.; Wylezinska-Arridge, Marzena; Couraud, Pierre O.; Lopez-Tremoleda, Jordi; Christian, Helen C.; Weksler, Babette B.; Malaspina, Andrea; Solito, Egle

    2013-01-01

    The blood–brain barrier (BBB), a critical guardian of communication between the periphery and the brain, is frequently compromised in neurological diseases such as multiple sclerosis (MS), resulting in the inappropriate passage of molecules and leukocytes into the brain. Here we show that the glucocorticoid anti-inflammatory messenger annexin A1 (ANXA1) is expressed in brain microvascular endothelial cells, where it regulates BBB integrity. In particular, ANXA1−/− mice exhibit significantly increased BBB permeability as a result of disrupted interendothelial cell tight junctions, essentially related to changes in the actin cytoskeleton, which stabilizes tight and adherens junctions. This situation is reminiscent of early MS pathology, a relationship confirmed by our detection of a selective loss of ANXA1 in the plasma and cerebrovascular endothelium of patients with MS. Importantly, this loss is swiftly restored by i.v. administration of human recombinant ANXA1. Analysis in vitro confirms that treatment of cerebrovascular endothelial cells with recombinant ANXA1 restores cell polarity, cytoskeleton integrity, and paracellular permeability through inhibition of the small G protein RhoA. We thus propose ANXA1 as a critical physiological regulator of BBB integrity and suggest it may have utility in the treatment of MS, correcting BBB function and hence ameliorating disease. PMID:23277546

  16. Prenatal Exposure of Guinea Pigs to the Organophosphorus Pesticide Chlorpyrifos Disrupts the Structural and Functional Integrity of the Brain

    PubMed Central

    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

  17. Life-Span Development of Brain Network Integration Assessed with Phase Lag Index Connectivity and Minimum Spanning Tree Graphs.

    PubMed

    Smit, Dirk J A; de Geus, Eco J C; Boersma, Maria; Boomsma, Dorret I; Stam, Cornelis J

    2016-05-01

    Graph analysis of electroencephalography (EEG) has previously revealed developmental increases in connectivity between distant brain areas and a decrease in randomness and increased integration in the brain network with concurrent increased modularity. Comparisons of graph parameters across age groups, however, may be confounded with network degree distributions. In this study, we analyzed graph parameters from minimum spanning tree (MST) graphs and compared their developmental trajectories to those of graph parameters based on full graphs published previously. MST graphs are constructed by selecting only the strongest available connections avoiding loops, resulting in a backbone graph that is thought to reflect the major qualitative properties of the network, while allowing a better comparison across age groups by avoiding the degree of distribution confound. EEG was recorded in a large (n = 1500) population-based sample aged 5-71 years. Connectivity was assessed using phase lag index to reduce effects of volume conduction. Connectivity in the MST graph increased significantly from childhood to adolescence, continuing to grow nonsignificantly into adulthood, and decreasing significantly about 57 years of age. Leaf number, degree, degree correlation, and maximum centrality from the MST graph indicated a pattern of increased integration and decreased randomness from childhood into early adulthood. The observed development in network topology suggested that maturation at the neuronal level is aimed to increase connectivity as well as increase integration of the brain network. We confirm that brain network connectivity shows quantitative changes across the life span and additionally demonstrate parallel qualitative changes in the connectivity pattern. PMID:26885699

  18. Alternative field representations and integral equations for modeling inhomogeneous dielectrics

    NASA Technical Reports Server (NTRS)

    Volakis, John L.

    1992-01-01

    New volume and volume-surface integral equations are presented for modeling inhomogeneous dielectric regions. The presented integral equations result in more efficient numerical implementations and should, therefore, be useful in a variety of electromagnetic applications.

  19. Integrated Meteorology and Chemistry Modeling: Evaluation and Research Needs

    EPA Science Inventory

    Over the past decade several online integrated atmospheric chemical-transport and meteorology modeling systems with varying levels of interactions among different atmospheric processes have been developed. A variety of approaches to meteorology-chemistry integration with differe...

  20. The Exercising Brain: Changes in Functional Connectivity Induced by an Integrated Multimodal Cognitive and Whole-Body Coordination Training

    PubMed Central

    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. PMID:26819776

  1. Integrated pain and palliative medicine model.

    PubMed

    Bhatnagar, Sushma; Gupta, Mayank

    2016-07-01

    Pain is one of the most common, distressing and feared symptom among cancer and other patients in need of palliative care. An estimated 25% of cancer patients and 25 million people die in pain each year. Effective pain and symptom management are the core elements of palliative care which aims at reducing suffering and improving quality of life (QOL) throughout the course of illness starting from diagnosis, in sync with curative treatments and at end of life. There is a prevailing shortage of manpower apt to deal with pain and providing cost-effective palliative care and with the rise of cancer, other chronic diseases and explosion of new life-prolonging therapeutic modalities, this 'Patient-pain and palliative physician' discrepancy is only going to increase, more so in developing countries. The need of the hour is to train all healthcare physicians and nurses especially those working in the field of chronic pain in principles of effective pain and symptom palliation, to integrate cancer pain and symptom management into existing pain management fellowships and to introduce a holistic pain and palliative care model at all levels of healthcare system. Simultaneously, of equal importance is to conduct research, evidence building and formulate policies and guidelines for meticulous symptom management among the diverse category of patients and diseases so as to have a personalized and individualistic approach to patient management. In this comprehensive review, we have pondered upon the need, advantages, barriers and recommendations to achieve ideal 'Integrated pain and palliative medicine' services, their equitable implementation and delivery to 'whomsoever in need of them'. PMID:27334349

  2. Traumatic Brain Injury – Modeling Neuropsychiatric Symptoms in Rodents

    PubMed Central

    Malkesman, Oz; Tucker, Laura B.; Ozl, Jessica; McCabe, Joseph T.

    2013-01-01

    Each year in the US, ∼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. PMID:24109476

  3. Integrated Free Energy Model (IFEM) for microemulsions.

    PubMed

    Boza Troncoso, Américo; Acosta, Edgar

    2016-03-15

    The Integrated Free Energy Model (IFEM) is a platform used to predict the solubilization of nonpolar oils in nonionic alkyl-polyethylene oxide (C(X)EO(Y)) micelles starting from a free energy balance of costs and gains when surfactants from empty micelles and oil from a continuous oil phase assemble to form an oil-swollen micelle. IFEM considers lipophilic interactions between surfactant tails and oil solubilized in the core of micelles, and the interaction between surfactant tails and the oil solubilized in the surfactant tail domain, as well as oil-oil and surfactant-surfactant tail interactions. Expressions to calculate these lipophilic interactions from van der Waals (VDW) interaction potential were introduced in a previous publication. In this article, two new surfactant-water interactions are considered, surfactant headgroup dehydration during solubilization, and surfactant tail group dehydration. These six interaction terms, in addition to two entropy of mixing contributions (in the lipophilic and in the hydrophilic domains) make up the eight terms of the IFEM platform. Of these terms, only the headgroup dehydration requires a calibrated parameter. After calibrating this parameter, the model is capable of predicting experimental solubilization data, and the experimental trends reflected by a semi-empirical model, the Hydrophilic-Lipophilic-Difference+Net-Average-Curvature (HLD-NAC). Although there are numerous approaches to predict the surfactant-oil-water (SOW) phase behavior, the IFEM platform is the only one, to the knowledge of the authors that produces an explicit connection between molecular interactions and experimental data for real SOW systems. The IFEM platform can be programmed in a personal computer using relatively inexpensive software and its explicit nature opens the possibility to introduce additional interaction terms for more complex SOW systems. PMID:26759991

  4. Evaluating integrated health care: a model for measurement

    PubMed Central

    Ahgren, Bengt; Axelsson, Runo

    2005-01-01

    Abstract Purpose In the development of integrated care, there is an increasing need for knowledge about the actual degree of integration between different providers of health services. The purpose of this article is to describe the conceptualisation and validation of a practical model for measurement, which can be used by managers to implement and sustain integrated care. Theory The model is based on a continuum of integration, extending from full segregation through intermediate forms of linkage, coordination and cooperation to full integration. Methods The continuum was operationalised into a ratio scale of functional clinical integration. This scale was used in an explorative study of a local health authority in Sweden. Data on integration were collected in self-assessment forms together with estimated ranks of optimum integration between the different units of the health authority. The data were processed with statistical methods and the results were discussed with the managers concerned. Results Judging from this explorative study, it seems that the model of measurement collects reliable and valid data of functional clinical integration in local health care. The model was also regarded as a useful instrument for managers of integrated care. Discussion One of the main advantages with the model is that it includes optimum ranks of integration beside actual ranks. The optimum integration rank between two units is depending on the needs of both differentiation and integration. PMID:16773158

  5. "Neuro-semeiotics" and "free-energy minimization" suggest a unified perspective for integrative brain actions: focus on receptor heteromers and Roamer type of volume transmission.

    PubMed

    Agnati, Luigi F; Guidolin, Diego; Marcoli, Manuela; Genedani, Susanna; Borroto-Escuela, Dasiel; Maura, Guido; Fuxe, Kjell

    2014-01-01

    Two far-reaching theoretical approaches, namely "Neuro-semeiotics" (NS) and "Free-energy Minimization" (FEM), have been recently proposed as frames within which to put forward heuristic hypotheses on integrative brain actions. In the present paper these two theoretical approaches are briefly discussed in the perspective of a recent model of brain architecture and information handling based on what we suggest calling Jacob's tinkering principle, whereby "to create is to recombine!". The NS and FEM theoretical approaches will be discussed from the perspective both of the Roamer-Type Volume Transmission (especially exosome-mediated) of intercellular communication and of the impact of receptor oligomers and Receptor-Receptor Interactions (RRIs) on signal recognition/decoding processes. In particular, the Bio-semeiotics concept of "adaptor" will be used to analyze RRIs as an important feature of NS. Furthermore, the concept of phenotypic plasticity of cells will be introduced in view of the demonstration of the possible transfer of receptors (i.e., adaptors) into a computational network via exosomes (see also Appendix). Thus, Jacob's tinkering principle will be proposed as a theoretical basis for some learning processes both at the network level (Turing-like type of machine) and at the molecular level as a consequence of both the plastic changes in the adaptors caused by the allosteric interactions in the receptor oligomers and the intercellular transfer of receptors. Finally, on the basis of NS and FEM theories, a unified perspective for integrative brain actions will be proposed. PMID:25175453

  6. The influence of surrogate blood vessels on the impact response of a physical model of the brain.

    PubMed

    Parnaik, Yednesh; Beillas, Philippe; Demetropoulos, Constantine K; Hardy, Warren N; Yang, King H; King, Albert I

    2004-11-01

    Cerebral blood vessels are an integral part of the brain and may play a role in the response of the brain to impact. The purpose of this study was to quantify the effects of surrogate vessels on the deformation patterns of a physical model of the brain under various impact conditions. Silicone gel and tubing were used as surrogates for brain tissue and blood vessels, respectively. Two aluminum cylinders representing a coronal section of the brain were constructed. One cylinder was filled with silicone gel only, and the other was filled with silicone gel and silicone tubing arranged in the radial direction in the peripheral region. An array of markers was embedded in the gel in both cylinders to facilitate strain calculation via high-speed video analysis. Both cylinders were simultaneously subjected to a combination of linear and angular acceleration using a two-segment pendulum. Marker motion was tracked, and maximum shear strain (MSS) and maximum principal strain (MPS) were calculated using markers clustered in groups of three. Four test series were conducted. Peak angular acceleration varied from 2,600 to 26,000 rad/s2, and peak angular speed varied from 17 to 29 rad/s. For a given impact condition, the test-to-test variation of these values was less than 5.5%. For all clusters, the peak MSS and peak MPS for both physical models were less than 26% and 32%, respectively. For 90% of the cluster locations, the absolute value of the difference in peak MSS and peak MPS between the physical models was 4% and 6%, respectively. In the physical model with tubing, strain tended to decrease in the periphery (near to the tubing), while it tended to increase toward the center (away from the tubing). Strain amplitudes were found to be sensitive to the peak angular speeds. In general, this study suggests that the vasculature could influence the deformation response of the brain. PMID:17230270

  7. Stretch in Brain Microvascular Endothelial Cells (cEND) as an In Vitro Traumatic Brain Injury Model of the Blood Brain Barrier

    PubMed Central

    Salvador, Ellaine; Neuhaus, Winfried; Foerster, Carola

    2013-01-01

    Due to the high mortality incident brought about by traumatic brain injury (TBI), methods that would enable one to better understand the underlying mechanisms involved in it are useful for treatment. There are both in vivo and in vitro methods available for this purpose. In vivo models can mimic actual head injury as it occurs during TBI. However, in vivo techniques may not be exploited for studies at the cell physiology level. Hence, in vitro methods are more advantageous for this purpose since they provide easier access to the cells and the extracellular environment for manipulation. Our protocol presents an in vitro model of TBI using stretch injury in brain microvascular endothelial cells. It utilizes pressure applied to the cells cultured in flexible-bottomed wells. The pressure applied may easily be controlled and can produce injury that ranges from low to severe. The murine brain microvascular endothelial cells (cEND) generated in our laboratory is a well-suited model for the blood brain barrier (BBB) thus providing an advantage to other systems that employ a similar technique. In addition, due to the simplicity of the method, experimental set-ups are easily duplicated. Thus, this model can be used in studying the cellular and molecular mechanisms involved in TBI at the BBB. PMID:24193450

  8. Design of a component-based integrated environmental modeling framework

    EPA Science Inventory

    Integrated environmental modeling (IEM) includes interdependent science-based components (e.g., models, databases, viewers, assessment protocols) that comprise an appropriate software modeling system. The science-based components are responsible for consuming and producing inform...

  9. Integrated Medical Model Verification, Validation, and Credibility

    NASA Technical Reports Server (NTRS)

    Walton, Marlei; Kerstman, Eric; Foy, Millennia; Shah, Ronak; Saile, Lynn; Boley, Lynn; Butler, Doug; Myers, Jerry

    2014-01-01

    The Integrated Medical Model (IMM) was designed to forecast relative changes for a specified set of crew health and mission success risk metrics by using a probabilistic (stochastic process) model based on historical data, cohort data, and subject matter expert opinion. A probabilistic approach is taken since exact (deterministic) results would not appropriately reflect the uncertainty in the IMM inputs. Once the IMM was conceptualized, a plan was needed to rigorously assess input information, framework and code, and output results of the IMM, and ensure that end user requests and requirements were considered during all stages of model development and implementation. METHODS: In 2008, the IMM team developed a comprehensive verification and validation (VV) plan, which specified internal and external review criteria encompassing 1) verification of data and IMM structure to ensure proper implementation of the IMM, 2) several validation techniques to confirm that the simulation capability of the IMM appropriately represents occurrences and consequences of medical conditions during space missions, and 3) credibility processes to develop user confidence in the information derived from the IMM. When the NASA-STD-7009 (7009) was published, the IMM team updated their verification, validation, and credibility (VVC) project plan to meet 7009 requirements and include 7009 tools in reporting VVC status of the IMM. RESULTS: IMM VVC updates are compiled recurrently and include 7009 Compliance and Credibility matrices, IMM VV Plan status, and a synopsis of any changes or updates to the IMM during the reporting period. Reporting tools have evolved over the lifetime of the IMM project to better communicate VVC status. This has included refining original 7009 methodology with augmentation from the NASA-STD-7009 Guidance Document. End user requests and requirements are being satisfied as evidenced by ISS Program acceptance of IMM risk forecasts, transition to an operational model and

  10. Assessment of Cognitive Function in the Water Maze Task: Maximizing Data Collection and Analysis in Animal Models of Brain Injury.

    PubMed

    Whiting, Mark D; Kokiko-Cochran, Olga N

    2016-01-01

    Animal models play a critical role in understanding the biomechanical, pathophysiological, and behavioral consequences of traumatic brain injury (TBI). In preclinical studies, cognitive impairment induced by TBI is often assessed using the Morris water maze (MWM). Frequently described as a hippocampally dependent spatial navigation task, the MWM is a highly integrative behavioral task that requires intact functioning in numerous brain regions and involves an interdependent set of mnemonic and non-mnemonic processes. In this chapter, we review the special considerations involved in using the MWM in animal models of TBI, with an emphasis on maximizing the degree of information extracted from performance data. We include a theoretical framework for examining deficits in discrete stages of cognitive function and offer suggestions for how to make inferences regarding the specific nature of TBI-induced cognitive impairment. The ultimate goal is more precise modeling of the animal equivalents of the cognitive deficits seen in human TBI. PMID:27604738

  11. Integrated Space Asset Management Database and Modeling

    NASA Technical Reports Server (NTRS)

    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

  12. Reactive actuators and sensors integrated in one device: mimicking brain-muscles feedback communication

    NASA Astrophysics Data System (ADS)

    Otero, Toribio F.; Martinez, Jose G.

    2013-04-01

    Artificial muscles based on carbon derivative molecular structures are chemical (electro-chemo-mechanical) actuators. The electrochemical reaction drives the film volume variation and the actuation. The applied current controls the movement rate and the charge controls the amplitude of the displacement (Faraday' motors). Any working or surrounding variable influencing the reaction rate will be sensed by the muscle potential, or by the consumed electrical energy, evolution during actuation. Experimental results and full theoretical description of the basic reactive material and of any dual electrochemical sensing-actuator will be presented. During current flow the muscle potential and the consumed electrical energy evolution are influenced by the working variables: temperature, electrolyte concentration, driving current, film volume variation (external pressure, applied strain, hanged masses, obstacles in its way). The working muscle becomes an electrochemical sensor. Only two connecting wires contain actuating (current) and sensing (potential) signals read and controlled, at any time from the computer-generator. One device integrates several sensing and actuating tools working simultaneously mimicking muscles/brain feedback communication.

  13. Multi-scale, multi-resolution brain cancer modeling.

    PubMed

    Zhang, Le; Chen, L Leon; Deisboeck, Thomas S

    2009-03-01

    In advancing discrete-based computational cancer models towards clinical applications, one faces the dilemma of how to deal with an ever growing amount of biomedical data that ought to be incorporated eventually in one form or another. Model scalability becomes of paramount interest. In an effort to start addressing this critical issue, here, we present a novel multi-scale and multi-resolution agent-based in silico glioma model. While 'multi-scale' refers to employing an epidermal growth factor receptor (EGFR)-driven molecular network to process cellular phenotypic decisions within the micro-macroscopic environment, 'multi-resolution' is achieved through algorithms that classify cells to either active or inactive spatial clusters, which determine the resolution they are simulated at. The aim is to assign computational resources where and when they matter most for maintaining or improving the predictive power of the algorithm, onto specific tumor areas and at particular times. Using a previously described 2D brain tumor model, we have developed four different computational methods for achieving the multi-resolution scheme, three of which are designed to dynamically train on the high-resolution simulation that serves as control. To quantify the algorithms' performance, we rank them by weighing the distinct computational time savings of the simulation runs versus the methods' ability to accurately reproduce the high-resolution results of the control. Finally, to demonstrate the flexibility of the underlying concept, we show the added value of combining the two highest-ranked methods. The main finding of this work is that by pursuing a multi-resolution approach, one can reduce the computation time of a discrete-based model substantially while still maintaining a comparably high predictive power. This hints at even more computational savings in the more realistic 3D setting over time, and thus appears to outline a possible path to achieve scalability for the all

  14. Melatonin promotes blood-brain barrier integrity in methamphetamine-induced inflammation in primary rat brain microvascular endothelial cells.

    PubMed

    Jumnongprakhon, Pichaya; Govitrapong, Piyarat; Tocharus, Chainarong; Tocharus, Jiraporn

    2016-09-01

    Melatonin is a neurohormone and has high potent of antioxidant that is widely reported to be active against methamphetamine (METH)-induced toxicity to neuron, glial cells, and brain endothelial cells. However, the role of melatonin on the inflammatory responses which are mostly caused by blood-brain barrier (BBB) impairment by METH administration has not been investigated. This study used the primary rat brain microvascular endothelial cells (BMVECs) to determine the protective mechanism of melatonin on METH-induced inflammatory responses in the BBB via nuclear factor-ĸB (NF-κB) and nuclear factor erythroid 2-related factor-2 (Nrf2) signaling. Herein, we demonstrated that melatonin reduced the level of the inflammatory mediators, including intercellular adhesion molecules (ICAM)-1, vascular cell adhesion molecules (VCAM)-1, matrix metallopeptidase (MMP)-9, inducible nitric oxide synthase (iNOS), and nitric oxide (NO) caused by METH. These responses were related to the decrease of the expression and translocation of the NF-κB p65 subunit and the activity of NADPH oxidase (NOX)-2. In addition, melatonin promoted the antioxidant processes, modulated the expression and translocation of Nrf2, and also increased the level of heme oxygenase (HO)-1, NAD (P) H: quinone oxidoreductase (NQO)-1, γ-glutamylcysteine synthase (γ-GCLC), and the activity of superoxide dismutase (SOD) through NOX2 mechanism. In addition, we found that the protective role of melatonin in METH-induced inflammatory responses in the BBB was mediated through melatonin receptors (MT1/2). We concluded that the interaction of melatonin with its receptor prevented METH-induced inflammatory responses by suppressing the NF-κB signaling and promoting the Nrf2 signaling before BBB impairment. PMID:27268413

  15. Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

    PubMed Central

    2015-01-01

    Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

  16. Fractional Diffusion Based Modelling and Prediction of Human Brain Response to External Stimuli

    PubMed Central

    Kulish, Vladimir V.

    2015-01-01

    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. PMID:26089955

  17. A Spectral Graphical Model Approach for Learning Brain Connectivity Network of Children's Narrative Comprehension

    PubMed Central

    Meng, Xiangxiang; Karunanayaka, Prasanna; Holland, Scott K.

    2011-01-01

    Abstract Narrative comprehension is a fundamental cognitive skill that involves the coordination of different functional brain regions. We develop a spectral graphical model with model averaging to study the connectivity networks underlying these brain regions using fMRI data collected from a story comprehension task. Based on the spectral density matrices in the frequency domain, this model captures the temporal dependency of the entire fMRI time series between brain regions. A Bayesian model averaging procedure is then applied to select the best directional links that constitute the brain network. Using this model, brain networks of three distinct age groups are constructed to assess the dynamic change of network connectivity with respect to age. PMID:22432453

  18. A Probabilistic Model of Functional Brain Connectivity Network for Discovering Novel Biomarkers

    PubMed Central

    Bian, Jiang; Xie, Mengjun; Topaloglu, Umit; Cisler, Josh M.

    2013-01-01

    Graph theoretical analyses of functional brain connectivity networks have been limited to a static view of brain activities over the entire timeseries. In this paper, we propose a new probabilistic model of the functional brain connectivity network, the strong-edge model, which incorporates the temporal fluctuation of neurodynamics. We also introduce a systematic approach to identifying biomarkers based on network characteristics that quantitatively describe the organization of the brain network. The evaluation results of the proposed strong-edge network model is quite promising. The biomarkers derived from the strong-edge model have achieved much higher prediction accuracy of 89% (ROCAUC: 0.96) in distinguishing depression subjects from healthy controls in comparison with the conventional network model (accuracy: 76%, ROC-AUC: 0.87). These novel biomarkers have the high potential of being applied clinically in diagnosing neurological and psychiatric brain diseases with noninvasive neuroimaging technologies. PMID:24303289

  19. A spectral graphical model approach for learning brain connectivity network of children's narrative comprehension.

    PubMed

    Lin, Xiaodong; Meng, Xiangxiang; Karunanayaka, Prasanna; Holland, Scott K

    2011-01-01

    Narrative comprehension is a fundamental cognitive skill that involves the coordination of different functional brain regions. We develop a spectral graphical model with model averaging to study the connectivity networks underlying these brain regions using fMRI data collected from a story comprehension task. Based on the spectral density matrices in the frequency domain, this model captures the temporal dependency of the entire fMRI time series between brain regions. A Bayesian model averaging procedure is then applied to select the best directional links that constitute the brain network. Using this model, brain networks of three distinct age groups are constructed to assess the dynamic change of network connectivity with respect to age. PMID:22432453

  20. Using computational models to relate structural and functional brain connectivity

    PubMed Central

    Hlinka, Jaroslav; Coombes, Stephen

    2012-01-01

    Modern imaging methods allow a non-invasive assessment of both structural and functional brain connectivity. This has lead to the identification of disease-related alterations affecting functional connectivity. The mechanism of how such alterations in functional connectivity arise in a structured network of interacting neural populations is as yet poorly understood. Here we use a modeling approach to explore the way in which this can arise and to highlight the important role that local population dynamics can have in shaping emergent spatial functional connectivity patterns. The local dynamics for a neural population is taken to be of the Wilson–Cowan type, whilst the structural connectivity patterns used, describing long-range anatomical connections, cover both realistic scenarios (from the CoComac database) and idealized ones that allow for more detailed theoretical study. We have calculated graph–theoretic measures of functional network topology from numerical simulations of model networks. The effect of the form of local dynamics on the observed network state is quantified by examining the correlation between structural and functional connectivity. We document a profound and systematic dependence of the simulated functional connectivity patterns on the parameters controlling the dynamics. Importantly, we show that a weakly coupled oscillator theory explaining these correlations and their variation across parameter space can be developed. This theoretical development provides a novel way to characterize the mechanisms for the breakdown of functional connectivity in diseases through changes in local dynamics. PMID:22805059

  1. Modeling mitochondrial dysfunctions in the brain: from mice to men.

    PubMed

    Breuer, Megan E; Willems, Peter H G M; Russel, Frans G M; Koopman, Werner J H; Smeitink, Jan A M

    2012-03-01

    The biologist Lewis Thomas once wrote: "my mitochondria comprise a very large proportion of me. I cannot do the calculation, but I suppose there is almost as much of them in sheer dry bulk as there is the rest of me". As humans, or indeed as any mammal, bird, or insect, we contain a specific molecular makeup that is driven by vast numbers of these miniscule powerhouses residing in most of our cells (mature red blood cells notwithstanding), quietly replicating, living independent lives and containing their own DNA. Everything we do, from running a marathon to breathing, is driven by these small batteries, and yet there is evidence that these molecular energy sources were originally bacteria, possibly parasitic, incorporated into our cells through symbiosis. Dysfunctions in these organelles can lead to debilitating, and sometimes fatal, diseases of almost all the bodies' major organs. Mitochondrial dysfunction has been implicated in a wide variety of human disorders either as a primary cause or as a secondary consequence. To better understand the role of mitochondrial dysfunction in human disease, a multitude of pharmacologically induced and genetically manipulated animal models have been developed showing to a greater or lesser extent the clinical symptoms observed in patients with known and unknown causes of the disease. This review will focus on diseases of the brain and spinal cord in which mitochondrial dysfunction has been proven or is suspected and on animal models that are currently used to study the etiology, pathogenesis and treatment of these diseases. PMID:21755361

  2. Local Model of Arteriovenous Malformation of the Human Brain

    NASA Astrophysics Data System (ADS)

    Nadezhda Telegina, Ms; Aleksandr Chupakhin, Mr; Aleksandr Cherevko, Mr

    2013-02-01

    Vascular diseases of the human brain are one of the reasons of deaths and people's incapacitation not only in Russia, but also in the world. The danger of an arteriovenous malformation (AVM) is in premature rupture of pathological vessels of an AVM which may cause haemorrhage. Long-term prognosis without surgical treatment is unfavorable. The reduced impact method of AVM treatment is embolization of a malformation which often results in complete obliteration of an AVM. Pre-surgical mathematical modeling of an arteriovenous malformation can help surgeons with an optimal sequence of the operation. During investigations, the simple mathematical model of arteriovenous malformation is developed and calculated, and stationary and non-stationary processes of its embolization are considered. Various sequences of embolization of a malformation are also considered. Calculations were done with approximate steady flow on the basis of balanced equations derived from conservation laws. Depending on pressure difference, a fistula-type AVM should be embolized at first, and then small racemose AVMs are embolized. Obtained results are in good correspondence with neurosurgical AVM practice.

  3. A Drosophila model of closed head traumatic brain injury

    PubMed Central

    Katzenberger, Rebeccah J.; Loewen, Carin A.; Wassarman, Douglas R.; Petersen, Andrew J.; Ganetzky, Barry; Wassarman, David A.

    2013-01-01

    Traumatic brain injury (TBI) is a substantial health issue worldwide, yet the mechanisms responsible for its complex spectrum of pathologies remains largely unknown. To investigate the mechanisms underlying TBI pathologies, we developed a model of TBI in Drosophila melanogaster. The model allows us to take advantage of the wealth of experimental tools available in flies. Closed head TBI was inflicted with a mechanical device that subjects flies to rapid acceleration and deceleration. Similar to humans with TBI, flies with TBI exhibited temporary incapacitation, ataxia, activation of the innate immune response, neurodegeneration, and death. Our data indicate that TBI results in death shortly after a primary injury only if the injury exceeds a certain threshold and that age and genetic background, but not sex, substantially affect this threshold. Furthermore, this threshold also appears to be dependent on the same cellular and molecular mechanisms that control normal longevity. This study demonstrates the potential of flies for providing key insights into human TBI that may ultimately provide unique opportunities for therapeutic intervention. PMID:24127584

  4. An Integrated Model of Training Evaluation and Effectiveness

    ERIC Educational Resources Information Center

    Alvarez, Kaye; Salas, Eduardo; Garofano, Christina M.

    2004-01-01

    A decade of training evaluation and training effectiveness research was reviewed to construct an integrated model of training evaluation and effectiveness. This model integrates four prior evaluation models and results of 10 years of training effectiveness research. It is the first to be constructed using a set of strict criteria and to…

  5. Integrated Model of Teacher Preparation: An Alternate Representation

    ERIC Educational Resources Information Center

    Gafoor K., Abdul

    2011-01-01

    The paper proposes an integrated model of pre-service preparation of teachers by incorporating the principles of critical and constructive approach to teacher education. The paper is an attempt to share the draft of the model with the national audience of teacher educators. The model proposed is integrated, among other things, in that in addition…

  6. Radiolysis Model Formulation for Integration with the Mixed Potential Model

    SciTech Connect

    Buck, Edgar C.; Wittman, Richard S.

    2014-07-10

    The U.S. Department of Energy Office of Nuclear Energy (DOE-NE), Office of Fuel Cycle Technology has established the Used Fuel Disposition Campaign (UFDC) to conduct the research and development activities related to storage, transportation, and disposal of used nuclear fuel (UNF) and high-level radioactive waste. Within the UFDC, the components for a general system model of the degradation and subsequent transport of UNF is being developed to analyze the performance of disposal options [Sassani et al., 2012]. Two model components of the near-field part of the problem are the ANL Mixed Potential Model and the PNNL Radiolysis Model. This report is in response to the desire to integrate the two models as outlined in [Buck, E.C, J.L. Jerden, W.L. Ebert, R.S. Wittman, (2013) “Coupling the Mixed Potential and Radiolysis Models for Used Fuel Degradation,” FCRD-UFD-2013-000290, M3FT-PN0806058

  7. Placebo analgesia and reward processing: Integrating genetics, personality, and intrinsic brain activity

    PubMed Central

    Yu, Rongjun; Gollub, Randy L; Vangel, Mark; Kaptchuk, Ted; Smoller, Jordan W.; Kong, Jian

    2014-01-01

    Our expectations about an event can strongly shape our subjective evaluation and actual experience of events. This ability, applied to the modulation of pain, has the potential to affect therapeutic analgesia substantially and constitutes a foundation for non-pharmacological pain relief. A typical example of such modulation is the placebo effect. Studies indicate that placebo may be regarded as a reward, and brain activity in the reward system is involved in this modulation process. In the present study, we combined resting state functional magnetic resonance imaging (rs-fMRI) measures, genotype at a functional COMT polymorphism (Val158Met), and personality measures in a model to predict the magnitude of placebo conditioning effect indicated by subjective pain rating reduction to calibrated noxious stimuli. We found that the regional homogeneity (ReHo), an index of local neural coherence, in the ventral striatum, was significantly associated with conditioning effects on pain rating changes. We also found that the number of Met alleles at the COMT polymorphism was linearly correlated to the suppression of pain. In a fitted regression model, we found the ReHo in the ventral striatum, COMT genotype, and Openness scores accounted for 59% of the variance in the change in pain ratings. The model was further tested using a separate data set from the same study. Our findings demonstrate the potential of combining resting state connectivity, genetic information and personality to predict placebo effect. PMID:24578196

  8. Multistability in Large Scale Models of Brain Activity

    PubMed Central

    Golos, Mathieu; Jirsa, Viktor; Daucé, Emmanuel

    2015-01-01

    Noise driven exploration of a brain network’s dynamic repertoire has been hypothesized to be causally involved in cognitive function, aging and neurodegeneration. The dynamic repertoire crucially depends on the network’s capacity to store patterns, as well as their stability. Here we systematically explore the capacity of networks derived from human connectomes to store attractor states, as well as various network mechanisms to control the brain’s dynamic repertoire. Using a deterministic graded response Hopfield model with connectome-based interactions, we reconstruct the system’s attractor space through a uniform sampling of the initial conditions. Large fixed-point attractor sets are obtained in the low temperature condition, with a bigger number of attractors than ever reported so far. Different variants of the initial model, including (i) a uniform activation threshold or (ii) a global negative feedback, produce a similarly robust multistability in a limited parameter range. A numerical analysis of the distribution of the attractors identifies spatially-segregated components, with a centro-medial core and several well-delineated regional patches. Those different modes share similarity with the fMRI independent components observed in the “resting state” condition. We demonstrate non-stationary behavior in noise-driven generalizations of the models, with different meta-stable attractors visited along the same time course. Only the model with a global dynamic density control is found to display robust and long-lasting non-stationarity with no tendency toward either overactivity or extinction. The best fit with empirical signals is observed at the edge of multistability, a parameter region that also corresponds to the highest entropy of the attractors. PMID:26709852

  9. Integrated Belowground Greenhouse Gas Flux Modeling (Invited)

    NASA Astrophysics Data System (ADS)

    Davidson, E. A.; Savage, K. E.

    2013-12-01

    Soil greenhouse gas (GHG) emissions play a significant role as biotic feedbacks to climate change. However, these complex processes, involving C, N, and O2 substrates and inhibitors, interactions with plant processes, and environmental influences of temperature, moisture, and gas transport, remain challenging to simulate in process models. Because CO2, CH4, and N2O production and consumption processes are inter-linked through common substrates and the contrasting effects of O2 as either an essential substrate or a potential inhibitor, the simulation of fluxes of any one gas must be consistent with mechanistic simulations and observations of fluxes of the other gases. Simulating the fluxes of one gas alone is a simpler task, but simulating all three gases simultaneously would provide multiple constraints and would afford greater confidence that the most important mechanisms are aptly simulated. A case in point is the challenge of resolving the apparent paradox of observed simultaneous CO2 production by aerobic respiration, CH4 uptake (oxidation), CH4 production, and N2O uptake (reduction) in the same soil profile. Consumption of atmospheric N2O should occur only under reducing conditions, and yet we have observed uptake of atmospheric CH4 (oxidation) and N2O (reduction) simultaneously. One of the great challenges of numerical modeling is determining the appropriate level of complexity when representing the most important environmental controllers. Ignoring complexity, such as simulating microbial processes with only simple Q10 functions, often results in poor model performance, because soil moisture and substrate supply can also be important factors. On the other hand, too much complexity, while perhaps mechanistically compelling, may result in too many poorly constrained parameters. Here we explore a parsimonious modeling framework for consistently integrated mechanistic and mathematical representation of the biophysical processes of belowground GHG production and

  10. Neurodegeneration from mitochondrial insufficiency: nutrients, stem cells, growth factors, and prospects for brain rebuilding using integrative management.

    PubMed

    Kidd, Parris M

    2005-12-01

    Degenerative brain disorders (neurodegeneration) can be frustrating for both conventional and alternative practitioners. A more comprehensive, integrative approach is urgently needed. One emerging focus for intervention is brain energetics. Specifically, mitochondrial insufficiency contributes to the etiopathology of many such disorders. Electron leakages inherent to mitochondrial energetics generate reactive oxygen free radical species that may place the ultimate limit on lifespan. Exogenous toxins, such as mercury and other environmental contaminants, exacerbate mitochondrial electron leakage, hastening their demise and that of their host cells. Studies of the brain in Alzheimer's and other dementias, Down syndrome, stroke, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, Huntington's disease, Friedreich's ataxia, aging, and constitutive disorders demonstrate impairments of the mitochondrial citric acid cycle and oxidative phosphorylation (OXPHOS) enzymes. Imaging or metabolic assays frequently reveal energetic insufficiency and depleted energy reserve in brain tissue in situ. Orthomolecular nutrients involved in mitochondrial metabolism provide clinical benefit. Among these are the essential minerals and the B vitamin group; vitamins E and K; and the antioxidant and energetic cofactors alpha-lipoic acid (ALA), ubiquinone (coenzyme Q10; CoQ10), and nicotinamide adenine dinucleotide, reduced (NADH). Recent advances in the area of stem cells and growth factors encourage optimism regarding brain regeneration. The trophic nutrients acetyl L-carnitine (ALCAR), glycerophosphocholine (GPC), and phosphatidylserine (PS) provide mitochondrial support and conserve growth factor receptors; all three improved cognition in double-blind trials. The omega-3 fatty acid docosahexaenoic acid (DHA) is enzymatically combined with GPC and PS to form membrane phospholipids for nerve cell expansion. Practical recommendations are presented for inte