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 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

  18. 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

  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. 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.

  19. 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

  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. 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.

  13. 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

  14. 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.

  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. 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…

  10. 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…

  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. 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

  16. 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

  17. 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.

  18. 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

  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. 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.

  1. 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

  2. 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

  3. 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.

  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. 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.

  7. 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

  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 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

  1. 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

  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. 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

  4. 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

  5. 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 ...

  6. 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.

  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. 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.

  14. 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

  15. 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

  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. 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.

  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. 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…

  4. 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

  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. 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.

  8. 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.

  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. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  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. 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

  1. 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.

  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. 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…

  6. 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.

  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. 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…

  12. 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.

  13. 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

  14. 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

  15. 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

  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. 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

  3. 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

  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. 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

  7. 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…

  8. 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…

  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

    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.

  12. 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

  13. 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.

  14. 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...

  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. 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

  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. 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

  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. 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

  2. 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

  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. 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

  6. 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

  7. 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

  8. 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

  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. 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

  13. 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

  14. 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

  15. 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

  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. 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...

  18. 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

  19. 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

  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. 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

  9. 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

  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