brain integrating models: Topics by Science.gov

Sample records for brain integrating models

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

PubMed Central

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

2017-01-01

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

DTIC Science & Technology

2016-10-01

Traumatic Brain Injury Research Informatics Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-14-1-0564 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...AWARD NUMBER: W81XWH-14-1-0564 TITLE: Integrating Traumatic Brain Injury Model Systems Data into the Federal Interagency Traumatic Brain Injury...Research Informatics Systems PRINCIPAL INVESTIGATOR: Cynthia Harrison-Felix, PhD CONTRACTING ORGANIZATION: Craig Hospital Englewood, CO 80113
Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

PubMed

Adhikari, Mohit H; Hacker, Carl D; Siegel, Josh S; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo; Corbetta, Maurizio

2017-04-01

While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to
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…
An Anatomically Constrained Model for Path Integration in the Bee Brain.

PubMed

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

2017-10-23

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

PubMed

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

2018-01-01

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

PubMed

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

2016-11-02

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

PubMed

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

2018-01-01

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

NASA Astrophysics Data System (ADS)

Gepner, Ruben; Wolk, Jason; Gershow, Marc

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

PubMed Central

Chen, Ishita; Ong, Rowena E.; Simpson, Amber L.; Sun, Kay; Thompson, Reid C.

2015-01-01

In recent work, an atlas-based statistical model for brain shift prediction, which accounts for uncertainty in the intraoperative environment, has been proposed. Previous work reported in the literature using this technique did not account for local deformation caused by surgical retraction. It is challenging to precisely localize the retractor location prior to surgery and the retractor is often moved in the course of the procedure. This paper proposes a technique that involves computing the retractor-induced brain deformation in the operating room through an active model solve and linearly superposing the solution with the precomputed deformation atlas. As a result, the new method takes advantage of the atlas-based framework’s accounting for uncertainties while also incorporating the effects of retraction with minimal intraoperative computing. This new approach was tested using simulation and phantom experiments. The results showed an improvement in average shift correction from 50% (ranging from 14 to 81%) for gravity atlas alone to 80% using the active solve retraction component (ranging from 73 to 85%). This paper presents a novel yet simple way to integrate retraction into the atlas-based brain shift computation framework. PMID:23864146
Phenotypic Integration of Neurocranium and Brain

PubMed Central

RICHTSMEIER, JOAN T.; ALDRIDGE, KRISTINA; DeLEON, VALERIE B.; PANCHAL, JAYESH; KANE, ALEX A.; MARSH, JEFFREY L.; YAN, PENG; COLE, THEODORE M.

2009-01-01

Evolutionary history of Mammalia provides strong evidence that the morphology of skull and brain change jointly in evolution. Formation and development of brain and skull co-occur and are dependent upon a series of morphogenetic and patterning processes driven by genes and their regulatory programs. Our current concept of skull and brain as separate tissues results in distinct analyses of these tissues by most researchers. In this study, we use 3D computed tomography and magnetic resonance images of pediatric individuals diagnosed with premature closure of cranial sutures (craniosynostosis) to investigate phenotypic relationships between the brain and skull. It has been demonstrated previously that the skull and brain acquire characteristic dysmorphologies in isolated craniosynostosis, but relatively little is known of the developmental interactions that produce these anomalies. Our comparative analysis of phenotypic integration of brain and skull in premature closure of the sagittal and the right coronal sutures demonstrates that brain and skull are strongly integrated and that the significant differences in patterns of association do not occur local to the prematurely closed suture. We posit that the current focus on the suture as the basis for this condition may identify a proximate, but not the ultimate cause for these conditions. Given that premature suture closure reduces the number of cranial bones, and that a persistent loss of skull bones is demonstrated over the approximately 150 million years of synapsid evolution, craniosynostosis may serve as an informative model for evolution of the mammalian skull. PMID:16526048
Phenotypic integration of neurocranium and brain.

PubMed

Richtsmeier, Joan T; Aldridge, Kristina; DeLeon, Valerie B; Panchal, Jayesh; Kane, Alex A; Marsh, Jeffrey L; Yan, Peng; Cole, Theodore M

2006-07-15

Evolutionary history of Mammalia provides strong evidence that the morphology of skull and brain change jointly in evolution. Formation and development of brain and skull co-occur and are dependent upon a series of morphogenetic and patterning processes driven by genes and their regulatory programs. Our current concept of skull and brain as separate tissues results in distinct analyses of these tissues by most researchers. In this study, we use 3D computed tomography and magnetic resonance images of pediatric individuals diagnosed with premature closure of cranial sutures (craniosynostosis) to investigate phenotypic relationships between the brain and skull. It has been demonstrated previously that the skull and brain acquire characteristic dysmorphologies in isolated craniosynostosis, but relatively little is known of the developmental interactions that produce these anomalies. Our comparative analysis of phenotypic integration of brain and skull in premature closure of the sagittal and the right coronal sutures demonstrates that brain and skull are strongly integrated and that the significant differences in patterns of association do not occur local to the prematurely closed suture. We posit that the current focus on the suture as the basis for this condition may identify a proximate, but not the ultimate cause for these conditions. Given that premature suture closure reduces the number of cranial bones, and that a persistent loss of skull bones is demonstrated over the approximately 150 million years of synapsid evolution, craniosynostosis may serve as an informative model for evolution of the mammalian skull. Copyright 2006 Wiley-Liss, Inc.
Creating the brain and interacting with the brain: an integrated approach to understanding the brain.

PubMed

Morimoto, Jun; Kawato, Mitsuo

2015-03-06

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

PubMed

Pomann, Gina-Maria; Sweeney, Elizabeth M; Reich, Daniel S; Staicu, Ana-Maria; Shinohara, Russell T

2015-09-10

Multiple sclerosis (MS) is an immune-mediated neurological disease that causes morbidity and disability. In patients with MS, the accumulation of lesions in the white matter of the brain is associated with disease progression and worse clinical outcomes. Breakdown of the blood-brain barrier in newer lesions is indicative of more active disease-related processes and is a primary outcome considered in clinical trials of treatments for MS. Such abnormalities in active MS lesions are evaluated in vivo using contrast-enhanced structural MRI, during which patients receive an intravenous infusion of a costly magnetic contrast agent. In some instances, the contrast agents can have toxic effects. Recently, local image regression techniques have been shown to have modest performance for assessing the integrity of the blood-brain barrier based on imaging without contrast agents. These models have centered on the problem of cross-sectional classification in which patients are imaged at a single study visit and pre-contrast images are used to predict post-contrast imaging. In this paper, we extend these methods to incorporate historical imaging information, and we find the proposed model to exhibit improved performance. We further develop scan-stratified case-control sampling techniques that reduce the computational burden of local image regression models, while respecting the low proportion of the brain that exhibits abnormal vascular permeability. Copyright © 2015 John Wiley & Sons, Ltd.
The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

PubMed

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

2016-02-01

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

PubMed

Ouss-Ryngaert, Lisa

2010-12-01

Our model of psychotherapy for patients with brain lesions is based on an integrative approach of psychobehavioral symptoms, especially from the neuropsychological and psychodynamic perspectives. Adjustment of technical modalities and aims of psychoanalytical therapy is required for these patients. The analysis of the influence of cognitive disorders on transference and contre-transference plays a major role, including the role of procedural processes in changes in the intersubjective relationship between the patient and the therapist. Two vignettes are presented to illustrate our model, which respects the integrity of the cognitive and psychodynamic approaches and can be implemented by only one therapist, using alternatively each lecture, or by a working team bringing to light the different aspects of the same symptom.
Realistic modeling of neurons and networks: towards brain simulation.

PubMed

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

2013-01-01

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.

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
Examination of Blood-Brain Barrier (BBB) Integrity In A Mouse Brain Tumor Model

PubMed Central

On, Ngoc; Mitchell, Ryan; Savant, Sanjot D.; Bachmeier, Corbin. J.; Hatch, Grant M.; Miller, Donald W.

2013-01-01

The present study evaluates, both functionally and biochemically, brain tumor-induced alterations in brain capillary endothelial cells. Brain tumors were induced in Balb/c mice via intracranial injection of Lewis Lung carcinoma (3LL) cells into the right hemisphere of the mouse brain using stereotaxic apparatus. Blood-brain barrier (BBB) permeability was assessed at various stages of tumor development, using both radiolabeled tracer permeability and magnetic resonance imaging (MRI) with gadolinium diethylene-triamine-pentaacetate contrast enhancement (Gad-DTPA). The expression of the drug efflux transporter, P-glycoprotein (P-gp), in the BBB at various stages of tumor development was also evaluated by Western blot and immunohistochemistry. Median mouse survival following tumor cell injection was 17 days. The permeability of the BBB to 3H-mannitol was similar in both brain hemispheres at 7 and 10 days post-injection. By day 15, there was a 2-fold increase in 3H-mannitol permeability in the tumor bearing hemispheres compared to the non-tumor hemispheres. Examination of BBB permeability with Gad-DTPA contrast enhanced MRI indicated cerebral vascular permeability changes were confined to the tumor area. The permeability increase observed at the later stages of tumor development correlated with an increase in cerebral vascular volume suggesting angiogenesis within the tumor bearing hemisphere. Furthermore, the Gad-DPTA enhancement observed within the tumor area was significantly less than Gad-DPTA enhancement within the circumventricular organs not protected by the BBB. Expression of P-gp in both the tumor bearing and non-tumor bearing portions of the brain appeared similar at all time points examined. These studies suggest that although BBB integrity is altered within the tumor site at later stages of development, the BBB is still functional and limiting in terms of solute and drug permeability in and around the tumor. PMID:23184143
Early brain development toward shaping of human mind: an integrative psychoneurodevelopmental model in prenatal and perinatal medicine.

PubMed

Hruby, Radovan; Maas, Lili M; Fedor-Freybergh, P G

2013-01-01

The article introduces an integrative psychoneurodevelopmental model of complex human brain and mind development based on the latest findings in prenatal and perinatal medicine in terms of integrative neuroscience. The human brain development is extraordinarily complex set of events and could be influenced by a lot of factors. It is supported by new insights into the early neuro-ontogenic processes with the help of structural 3D magnetic resonance imaging or diffusion tensor imaging of fetal human brain. Various factors and targets for neural development including birth weight variability, fetal and early-life programming, fetal neurobehavioral states and fetal behavioral responses to various stimuli and others are discussed. Molecular biology reveals increasing sets of genes families as well as transcription and neurotropic factors together with critical epigenetic mechanisms to be deeply employed in the crucial neurodevelopmental events. Another field of critical importance is psychoimmuno-neuroendocrinology. Various effects of glucocorticoids as well as other hormones, prenatal stress and fetal HPA axis modulation are thought to be of special importance for brain development. The early postnatal period is characterized by the next intense shaping of complex competences, induced mainly by the very unique mother - newborn´s interactions and bonding. All these mechanisms serve to shape individual human mind with complex abilities and neurobehavioral strategies. Continuous research elucidating these special competences of human fetus and newborn/child supports integrative neuroscientific approach to involve various scientific disciplines for the next progress in human brain and mind research, and opens new scientific challenges and philosophic attitudes. New findings and approaches in this field could establish new methods in science, in primary prevention and treatment strategies, and markedly contribute to the development of modern integrative and personalized
Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases.

PubMed

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.
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
Modelling brain emergent behaviours through coevolution of neural agents.

PubMed

Maniadakis, Michail; Trahanias, Panos

2006-06-01

Recently, many research efforts focus on modelling partial brain areas with the long-term goal to support cognitive abilities of artificial organisms. Existing models usually suffer from heterogeneity, which constitutes their integration very difficult. The present work introduces a computational framework to address brain modelling tasks, emphasizing on the integrative performance of substructures. Moreover, implemented models are embedded in a robotic platform to support its behavioural capabilities. We follow an agent-based approach in the design of substructures to support the autonomy of partial brain structures. Agents are formulated to allow the emergence of a desired behaviour after a certain amount of interaction with the environment. An appropriate collaborative coevolutionary algorithm, able to emphasize both the speciality of brain areas and their cooperative performance, is employed to support design specification of agent structures. The effectiveness of the proposed approach is illustrated through the implementation of computational models for motor cortex and hippocampus, which are successfully tested on a simulated mobile robot.
A Culture-Behavior-Brain Loop Model of Human Development.

PubMed

Han, Shihui; Ma, Yina

2015-11-01

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

PubMed

Woodman, M Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.
Integrating neuroinformatics tools in TheVirtualBrain

PubMed Central

Woodman, M. Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A.; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting. PMID:24795617
Tick-borne encephalitis virus infects human brain microvascular endothelial cells without compromising blood-brain barrier integrity.

PubMed

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

2017-07-01

Alteration of the blood-brain barrier (BBB) is a hallmark of tick-borne encephalitis (TBE), a life-threating human viral neuroinfection. However, the mechanism of BBB breakdown during TBE, as well as TBE virus (TBEV) entry into the brain is unclear. Here, primary human microvascular endothelial cells (HBMECs) were infected with TBEV to study interactions with the BBB. Although the number of infected cells was relatively low in culture (<5%), the infection was persistent with high TBEV yields (>10 6 pfu/ml). Infection did not induce any significant changes in the expression of key tight junction proteins or upregulate the expression of cell adhesion molecules, and did not alter the highly organized intercellular junctions between HBMECs. In an in vitro BBB model, the virus crossed the BBB via a transcellular pathway without compromising the integrity of the cell monolayer. The results indicate that HBMECs may support TBEV entry into the brain without altering BBB integrity. Copyright © 2017 Elsevier Inc. All rights reserved.
A Network Model of the Emotional Brain.

PubMed

Pessoa, Luiz

2017-05-01

Emotion is often understood in terms of a circumscribed set of cortical and subcortical brain regions. I propose, instead, that emotion should be understood in terms of large-scale network interactions spanning the entire neuroaxis. I describe multiple anatomical and functional principles of brain organization that lead to the concept of 'functionally integrated systems', cortical-subcortical systems that anchor the organization of emotion in the brain. The proposal is illustrated by describing the cortex-amygdala integrated system and how it intersects with systems involving the ventral striatum/accumbens, septum, hippocampus, hypothalamus, and brainstem. The important role of the thalamus is also highlighted. Overall, the model clarifies why the impact of emotion is wide-ranging, and how emotion is interlocked with perception, cognition, motivation, and action. Copyright © 2017 Elsevier Ltd. All rights reserved.
Development of a cerebral circulation model for the automatic control of brain physiology.

PubMed

Utsuki, T

2015-01-01

In various clinical guidelines of brain injury, intracranial pressure (ICP), cerebral blood flow (CBF) and brain temperature (BT) are essential targets for precise management for brain resuscitation. In addition, the integrated automatic control of BT, ICP, and CBF is required for improving therapeutic effects and reducing medical costs and staff burden. Thus, a new model of cerebral circulation was developed in this study for integrative automatic control. With this model, the CBF and cerebral perfusion pressure of a normal adult male were regionally calculated according to cerebrovascular structure, blood viscosity, blood distribution, CBF autoregulation, and ICP. The analysis results were consistent with physiological knowledge already obtained with conventional studies. Therefore, the developed model is potentially available for the integrative control of the physiological state of the brain as a reference model of an automatic control system, or as a controlled object in various control simulations.
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
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.
An in vivo model of functional and vascularized human brain organoids.

PubMed

Mansour, Abed AlFatah; Gonçalves, J Tiago; Bloyd, Cooper W; Li, Hao; Fernandes, Sarah; Quang, Daphne; Johnston, Stephen; Parylak, Sarah L; Jin, Xin; Gage, Fred H

2018-06-01

Differentiation of human pluripotent stem cells to small brain-like structures known as brain organoids offers an unprecedented opportunity to model human brain development and disease. To provide a vascularized and functional in vivo model of brain organoids, we established a method for transplanting human brain organoids into the adult mouse brain. Organoid grafts showed progressive neuronal differentiation and maturation, gliogenesis, integration of microglia, and growth of axons to multiple regions of the host brain. In vivo two-photon imaging demonstrated functional neuronal networks and blood vessels in the grafts. Finally, in vivo extracellular recording combined with optogenetics revealed intragraft neuronal activity and suggested graft-to-host functional synaptic connectivity. This combination of human neural organoids and an in vivo physiological environment in the animal brain may facilitate disease modeling under physiological conditions.
Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders

PubMed Central

Lord, Louis-David; Stevner, Angus B.; Kringelbach, Morten L.

2017-01-01

To survive in an ever-changing environment, the brain must seamlessly integrate a rich stream of incoming information into coherent internal representations that can then be used to efficiently plan for action. The brain must, however, balance its ability to integrate information from various sources with a complementary capacity to segregate information into modules which perform specialized computations in local circuits. Importantly, evidence suggests that imbalances in the brain's ability to bind together and/or segregate information over both space and time is a common feature of several neuropsychiatric disorders. Most studies have, however, until recently strictly attempted to characterize the principles of integration and segregation in static (i.e. time-invariant) representations of human brain networks, hence disregarding the complex spatio-temporal nature of these processes. In the present Review, we describe how the emerging discipline of whole-brain computational connectomics may be used to study the causal mechanisms of the integration and segregation of information on behaviourally relevant timescales. We emphasize how novel methods from network science and whole-brain computational modelling can expand beyond traditional neuroimaging paradigms and help to uncover the neurobiological determinants of the abnormal integration and segregation of information in neuropsychiatric disorders. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’. PMID:28507228
Dependence of normal brain integral dose and normal tissue complication probability on the prescription isodose values for γ-knife radiosurgery

NASA Astrophysics Data System (ADS)

Ma, Lijun

2001-11-01

A recent multi-institutional clinical study suggested possible benefits of lowering the prescription isodose lines for stereotactic radiosurgery procedures. In this study, we investigate the dependence of the normal brain integral dose and the normal tissue complication probability (NTCP) on the prescription isodose values for γ-knife radiosurgery. An analytical dose model was developed for γ-knife treatment planning. The dose model was commissioned by fitting the measured dose profiles for each helmet size. The dose model was validated by comparing its results with the Leksell gamma plan (LGP, version 5.30) calculations. The normal brain integral dose and the NTCP were computed and analysed for an ensemble of treatment cases. The functional dependence of the normal brain integral dose and the NCTP versus the prescribing isodose values was studied for these cases. We found that the normal brain integral dose and the NTCP increase significantly when lowering the prescription isodose lines from 50% to 35% of the maximum tumour dose. Alternatively, the normal brain integral dose and the NTCP decrease significantly when raising the prescribing isodose lines from 50% to 65% of the maximum tumour dose. The results may be used as a guideline for designing future dose escalation studies for γ-knife applications.
Computational modeling of neurostimulation in brain diseases.

PubMed

Wang, Yujiang; Hutchings, Frances; Kaiser, Marcus

2015-01-01

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

PubMed

Batchos, Elisabeth; Easton, Amanda; Haak, Christopher; Ditchman, Nicole

2018-08-01

Individuals with acquired brain injury (ABI) may not only struggle with physical and cognitive impairments, but may also face challenges reintegrating into the community socially. Research has demonstrated that following ABI, individuals' social networks tend to dwindle, support may decline, and isolation increases. This study examined factors impacting social integration in a community-based sample of 102 individuals with ABI. Potential predictors included emotional support, instrumental support, problem solving confidence, and approach-avoidance style (AAS) of problem solving, while controlling for age, gender, education, and time since injury. Hierarchical regression was used to analyze whether these factors were predictive of social integration. The final model accounted for 33% of the variance in social integration outcomes. Results demonstrated that emotional support was initially a significant predictor; however, when controlling for emotional support the variance in social integration was better accounted for by social problem solving - specifically, AAS. A follow-up mediation analysis indicated that the relationship between social problem solving (specifically, AAS) and social integration was partially mediated by emotional support. This suggests that for individuals with ABI, a tendency to approach rather than avoid social problem solving issues is a significant predictor for social integration both directly and indirectly through its association with emotional social support. Implications for Rehabilitation Both instrumental and emotional social support should be assessed in patients with acquired brain injury (ABI), ensuring that emotional needs are met in addition to the more obvious instrumental needs. Barriers to problem solving for people with ABI may limit optimal social integration; thus, assessment and intervention aimed at increasing AAS are recommended. To enhance the social integration outcomes of people with brain injury, strength

Graph theoretical modeling of baby brain networks.

PubMed

Zhao, Tengda; Xu, Yuehua; He, Yong

2018-06-12

The human brain undergoes explosive growth during the prenatal period and the first few postnatal years, establishing an early infrastructure for the later development of behaviors and cognitions. Revealing the developmental rules during the early phrase is essential in understanding the emergence of brain function and the origin of developmental disorders. The graph-theoretical network modeling in combination with multiple neuroimaging probes provides an important research framework to explore early development of the topological wiring and organizational paradigms of the brain. Here, we reviewed studies which employed neuroimaging and graph-theoretical modeling to investigate brain network development from approximately 20 gestational weeks to 2 years of age. Specifically, the structural and functional brain networks have evolved to highly efficient topological architectures in the early stage; where the structural network remains ahead and paves the way for the development of functional network. The brain network develops in a heterogeneous order, from primary to higher-order systems and from a tendency of network segregation to network integration in the prenatal and postnatal periods. The early brain network topologies show abilities in predicting certain cognitive and behavior performance in later life, and their impairments are likely to continue into childhood and even adulthood. These macroscopic topological changes are found to be associated with possible microstructural maturations, such as axonal growth and myelinations. Collectively, this review provides a detailed delineation of the early changes of the baby brains in the graph-theoretical modeling framework, which opens up a new avenue to understand the developmental principles of the connectome. Copyright © 2018. Published by Elsevier Inc.
Functional atlas of the awake rat brain: A neuroimaging study of rat brain specialization and integration.

PubMed

Ma, Zhiwei; Perez, Pablo; Ma, Zilu; Liu, Yikang; Hamilton, Christina; Liang, Zhifeng; Zhang, Nanyin

2018-04-15

Connectivity-based parcellation approaches present an innovative method to segregate the brain into functionally specialized regions. These approaches have significantly advanced our understanding of the human brain organization. However, parallel progress in animal research is sparse. Using resting-state fMRI data and a novel, data-driven parcellation method, we have obtained robust functional parcellations of the rat brain. These functional parcellations reveal the regional specialization of the rat brain, which exhibited high within-parcel homogeneity and high reproducibility across animals. Graph analysis of the whole-brain network constructed based on these functional parcels indicates that the rat brain has a topological organization similar to humans, characterized by both segregation and integration. Our study also provides compelling evidence that the cingulate cortex is a functional hub region conserved from rodents to humans. Together, this study has characterized the rat brain specialization and integration, and has significantly advanced our understanding of the rat brain organization. In addition, it is valuable for studies of comparative functional neuroanatomy in mammalian brains. Copyright © 2016 Elsevier Inc. All rights reserved.
Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.
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
The brain, self and society: a social-neuroscience model of predictive processing.

PubMed

Kelly, Michael P; Kriznik, Natasha M; Kinmonth, Ann Louise; Fletcher, Paul C

2018-05-10

This paper presents a hypothesis about how social interactions shape and influence predictive processing in the brain. The paper integrates concepts from neuroscience and sociology where a gulf presently exists between the ways that each describe the same phenomenon - how the social world is engaged with by thinking humans. We combine the concepts of predictive processing models (also called predictive coding models in the neuroscience literature) with ideal types, typifications and social practice - concepts from the sociological literature. This generates a unified hypothetical framework integrating the social world and hypothesised brain processes. The hypothesis combines aspects of neuroscience and psychology with social theory to show how social behaviors may be "mapped" onto brain processes. It outlines a conceptual framework that connects the two disciplines and that may enable creative dialogue and potential future research.
From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

Naumann, Eva A; Fitzgerald, James E; Dunn, Timothy W; Rihel, Jason; Sompolinsky, Haim; Engert, Florian

2016-11-03

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data. Copyright © 2016 Elsevier Inc. All rights reserved.
Angiotensin receptors and β-catenin regulate brain endothelial integrity in malaria

PubMed Central

Basu-Roy, Upal; Ty, Maureen; Alique, Matilde; Fernandez-Arias, Cristina; Movila, Alexandru; Gomes, Pollyanna; Edagha, Innocent; Wassmer, Samuel C.; Walther, Thomas

2016-01-01

Cerebral malaria is characterized by cytoadhesion of Plasmodium falciparum–infected red blood cells (Pf-iRBCs) to endothelial cells in the brain, disruption of the blood-brain barrier, and cerebral microhemorrhages. No available antimalarial drugs specifically target the endothelial disruptions underlying this complication, which is responsible for the majority of malaria-associated deaths. Here, we have demonstrated that ruptured Pf-iRBCs induce activation of β-catenin, leading to disruption of inter–endothelial cell junctions in human brain microvascular endothelial cells (HBMECs). Inhibition of β-catenin–induced TCF/LEF transcription in the nucleus of HBMECs prevented the disruption of endothelial junctions, confirming that β-catenin is a key mediator of P. falciparum adverse effects on endothelial integrity. Blockade of the angiotensin II type 1 receptor (AT1) or stimulation of the type 2 receptor (AT2) abrogated Pf-iRBC–induced activation of β-catenin and prevented the disruption of HBMEC monolayers. In a mouse model of cerebral malaria, modulation of angiotensin II receptors produced similar effects, leading to protection against cerebral malaria, reduced cerebral hemorrhages, and increased survival. In contrast, AT2-deficient mice were more susceptible to cerebral malaria. The interrelation of the β-catenin and the angiotensin II signaling pathways opens immediate host-targeted therapeutic possibilities for cerebral malaria and other diseases in which brain endothelial integrity is compromised. PMID:27643439
Comparison of two integration methods for dynamic causal modeling of electrophysiological data.

PubMed

Lemaréchal, Jean-Didier; George, Nathalie; David, Olivier

2018-06-01

Dynamic causal modeling (DCM) is a methodological approach to study effective connectivity among brain regions. Based on a set of observations and a biophysical model of brain interactions, DCM uses a Bayesian framework to estimate the posterior distribution of the free parameters of the model (e.g. modulation of connectivity) and infer architectural properties of the most plausible model (i.e. model selection). When modeling electrophysiological event-related responses, the estimation of the model relies on the integration of the system of delay differential equations (DDEs) that describe the dynamics of the system. In this technical note, we compared two numerical schemes for the integration of DDEs. The first, and standard, scheme approximates the DDEs (more precisely, the state of the system, with respect to conduction delays among brain regions) using ordinary differential equations (ODEs) and solves it with a fixed step size. The second scheme uses a dedicated DDEs solver with adaptive step sizes to control error, making it theoretically more accurate. To highlight the effects of the approximation used by the first integration scheme in regard to parameter estimation and Bayesian model selection, we performed simulations of local field potentials using first, a simple model comprising 2 regions and second, a more complex model comprising 6 regions. In these simulations, the second integration scheme served as the standard to which the first one was compared. Then, the performances of the two integration schemes were directly compared by fitting a public mismatch negativity EEG dataset with different models. The simulations revealed that the use of the standard DCM integration scheme was acceptable for Bayesian model selection but underestimated the connectivity parameters and did not allow an accurate estimation of conduction delays. Fitting to empirical data showed that the models systematically obtained an increased accuracy when using the second
Integrating Brain and Biomechanical Models—A New Paradigm for Understanding Neuro-muscular Control

PubMed Central

James, Sebastian S.; Papapavlou, Chris; Blenkinsop, Alexander; Cope, Alexander J.; Anderson, Sean R.; Moustakas, Konstantinos; Gurney, Kevin N.

2018-01-01

To date, realistic models of how the central nervous system governs behavior have been restricted in scope to the brain, brainstem or spinal column, as if these existed as disembodied organs. Further, the model is often exercised in relation to an in vivo physiological experiment with input comprising an impulse, a periodic signal or constant activation, and output as a pattern of neural activity in one or more neural populations. Any link to behavior is inferred only indirectly via these activity patterns. We argue that to discover the principles of operation of neural systems, it is necessary to express their behavior in terms of physical movements of a realistic motor system, and to supply inputs that mimic sensory experience. To do this with confidence, we must connect our brain models to neuro-muscular models and provide relevant visual and proprioceptive feedback signals, thereby closing the loop of the simulation. This paper describes an effort to develop just such an integrated brain and biomechanical system using a number of pre-existing models. It describes a model of the saccadic oculomotor system incorporating a neuromuscular model of the eye and its six extraocular muscles. The position of the eye determines how illumination of a retinotopic input population projects information about the location of a saccade target into the system. A pre-existing saccadic burst generator model was incorporated into the system, which generated motoneuron activity patterns suitable for driving the biomechanical eye. The model was demonstrated to make accurate saccades to a target luminance under a set of environmental constraints. Challenges encountered in the development of this model showed the importance of this integrated modeling approach. Thus, we exposed shortcomings in individual model components which were only apparent when these were supplied with the more plausible inputs available in a closed loop design. Consequently we were able to suggest missing
Basic difference between brain and computer: integration of asynchronous processes implemented as hardware model of the retina.

PubMed

Przybyszewski, Andrzej W; Linsay, Paul S; Gaudiano, Paolo; Wilson, Christopher M

2007-01-01

There exists a common view that the brain acts like a Turing machine: The machine reads information from an infinite tape (sensory data) and, on the basis of the machine's state and information from the tape, an action (decision) is made. The main problem with this model lies in how to synchronize a large number of tapes in an adaptive way so that the machine is able to accomplish tasks such as object classification. We propose that such mechanisms exist already in the eye. A popular view is that the retina, typically associated with high gain and adaptation for light processing, is actually performing local preprocessing by means of its center-surround receptive field. We would like to show another property of the retina: The ability to integrate many independent processes. We believe that this integration is implemented by synchronization of neuronal oscillations. In this paper, we present a model of the retina consisting of a series of coupled oscillators which can synchronize on several scales. Synchronization is an analog process which is converted into a digital spike train in the output of the retina. We have developed a hardware implementation of this model, which enables us to carry out rapid simulation of multineuron oscillatory dynamics. We show that the properties of the spike trains in our model are similar to those found in vivo in the cat retina.
Finding influential nodes for integration in brain networks using optimal percolation theory.

PubMed

Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

2018-06-11

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.
High-throughput screening for identification of blood-brain barrier integrity enhancers: a drug repurposing opportunity to rectify vascular amyloid toxicity

PubMed Central

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

2016-01-01

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, five 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
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. Copyright © 2014 Elsevier B.V. All rights reserved.
A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410
Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767
Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

2008-04-01

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.
Endothelial β-Catenin Signaling Is Required for Maintaining Adult Blood-Brain Barrier Integrity and CNS Homeostasis

PubMed Central

Tran, Khiem A.; Zhang, Xianming; Predescu, Dan; Huang, Xiaojia; Machado, Roberto F.; Göthert, Joachim R.; Malik, Asrar B.; Valyi-Nagy, Tibor; Zhao, You-Yang

2015-01-01

Background The blood-brain barrier (BBB) formed by brain endothelial cells (ECs) interconnected by tight junctions (TJs) is essential for the homeostasis of the central nervous system (CNS). Although studies have shown the importance of various signaling molecules in BBB formation during development, little is known about the molecular basis regulating the integrity of the adult BBB. Methods and Results Using a mouse model with tamoxifen-inducible EC-restricted disruption of ctnnb1 (iCKO), here we show that endothelial β-catenin signaling is essential for maintaining BBB integrity and CNS homeostasis in adult. The iCKO mice developed severe seizures accompanied by neuronal injury, multiple brain petechial hemorrhages, and CNS inflammation, and all died postictal. Disruption of endothelial β-catenin induced BBB breakdown and downregulation of specific TJ proteins Claudin-1 and -3 in adult brain ECs. The clinical relevance of the data is indicated by the observation of decreased expression of Claudin-1 and nuclear β-catenin in brain ECs of hemorrhagic lesions of hemorrhagic stroke patients. Conclusion These results demonstrate the prerequisite role of endothelial β-catenin in maintaining the integrity of adult BBB. The results suggest that BBB dysfunction secondary to defective β-catenin transcription activity is a key pathogenic factor in hemorrhagic stroke, seizure activity and CNS inflammation. PMID:26538583
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

2016-07-06

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.
C5a alters blood-brain barrier integrity in experimental lupus

PubMed Central

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

2010-01-01

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-Tnfrsf6lpr (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
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.

Brain/MINDS: brain-mapping project in Japan

PubMed Central

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-01-01

There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas. PMID:25823872
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,…
An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States

DTIC Science & Technology

2015-12-22

AFRL-AFOSR-VA-TR-2016-0037 An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States Adrian Lee UNIVERSITY OF WASHINGTON...to 14-09-2015 4. TITLE AND SUBTITLE An Integrated Neuroscience and Engineering Approach to Classifying Human Brain- States 5a. CONTRACT NUMBER 5b...specific cognitive states remains elusive, owing perhaps to limited crosstalk between the fields of neuroscience and engineering. Here, we report a
A Right Brain/Left Brain Model of Acting.

ERIC Educational Resources Information Center

Bowlen, Clark

Using current right brain/left brain research, this paper develops a model that explains acting's underlying quality--the actor is both himself and the character. Part 1 presents (1) the background of the right brain/left brain theory, (2) studies showing that propositional communication is a left hemisphere function while affective communication…
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…
Tau depletion prevents progressive blood-brain barrier damage in a mouse model of tauopathy.

PubMed

Blair, Laura J; Frauen, Haley D; Zhang, Bo; Nordhues, Bryce A; Bijan, Sara; Lin, Yen-Chi; Zamudio, Frank; Hernandez, Lidice D; Sabbagh, Jonathan J; Selenica, Maj-Linda B; Dickey, Chad A

2015-01-31

The blood-brain barrier (BBB) is damaged in tauopathies, including progressive supranuclear palsy (PSP) and Alzheimer's disease (AD), which is thought to contribute to pathogenesis later in the disease course. In AD, BBB dysfunction has been associated with amyloid beta (Aß) pathology, but the role of tau in this process is not well characterized. Since increased BBB permeability is found in tauopathies without Aß pathology, like PSP, we suspected that tau accumulation alone could not only be sufficient, but even more important than Aß for BBB damage. Longitudinal evaluation of brain tissue from the tetracycline-regulatable rTg4510 tau transgenic mouse model showed progressive IgG, T cell and red blood cell infiltration. The Evans blue (EB) dye that is excluded from the brain when the BBB is intact also permeated the brains of rTg4510 mice following peripheral administration, indicative of a bonafide BBB defect, but this was only evident later in life. Thus, despite the marked brain atrophy and inflammation that occurs earlier in this model, BBB integrity is maintained. Interestingly, BBB dysfunction emerged at the same time that perivascular tau emerged around major hippocampal blood vessels. However, when tau expression was suppressed using doxycycline, BBB integrity was preserved, suggesting that the BBB can be stabilized in a tauopathic brain by reducing tau levels. For the first time, these data demonstrate that tau alone can initiate breakdown of the BBB, but the BBB is remarkably resilient, maintaining its integrity in the face of marked brain atrophy, neuroinflammation and toxic tau accumulation. Moreover, the BBB can recover integrity when tau levels are reduced. Thus, late stage interventions targeting tau may slow the vascular contributions to cognitive impairment and dementia that occur in tauopathies.
Amplitude-integrated EEG in newborns with critical congenital heart disease predicts preoperative brain magnetic resonance imaging findings.

PubMed

Mulkey, Sarah B; Yap, Vivien L; Bai, Shasha; Ramakrishnaiah, Raghu H; Glasier, Charles M; Bornemeier, Renee A; Schmitz, Michael L; Bhutta, Adnan T

2015-06-01

The study aims are to evaluate cerebral background patterns using amplitude-integrated electroencephalography in newborns with critical congenital heart disease, determine if amplitude-integrated electroencephalography is predictive of preoperative brain injury, and assess the incidence of preoperative seizures. We hypothesize that amplitude-integrated electroencephalography will show abnormal background patterns in the early preoperative period in infants with congenital heart disease that have preoperative brain injury on magnetic resonance imaging. Twenty-four newborns with congenital heart disease requiring surgery at younger than 30 days of age were prospectively enrolled within the first 3 days of age at a tertiary care pediatric hospital. Infants had amplitude-integrated electroencephalography for 24 hours beginning close to birth and preoperative brain magnetic resonance imaging. The amplitude-integrated electroencephalographies were read to determine if the background pattern was normal, mildly abnormal, or severely abnormal. The presence of seizures and sleep-wake cycling were noted. The preoperative brain magnetic resonance imaging scans were used for brain injury and brain atrophy assessment. Fifteen of 24 infants had abnormal amplitude-integrated electroencephalography at 0.71 (0-2) (mean [range]) days of age. In five infants, the background pattern was severely abnormal. (burst suppression and/or continuous low voltage). Of the 15 infants with abnormal amplitude-integrated electroencephalography, 9 (60%) had brain injury. One infant with brain injury had a seizure on amplitude-integrated electroencephalography. A severely abnormal background pattern on amplitude-integrated electroencephalography was associated with brain atrophy (P = 0.03) and absent sleep-wake cycling (P = 0.022). Background cerebral activity is abnormal on amplitude-integrated electroencephalography following birth in newborns with congenital heart disease who have findings of
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…
Consciousness, information integration, and the brain.

PubMed

Tononi, Giulio

2005-01-01

Clinical observations have established that certain parts of the brain are essential for consciousness whereas other parts are not. For example, different areas of the cerebral cortex contribute different modalities and submodalities of consciousness, whereas the cerebellum does not, despite having even more neurons. It is also well established that consciousness depends on the way the brain functions. For example, consciousness is much reduced during slow wave sleep and generalized seizures, even though the levels of neural activity are comparable or higher than in wakefulness. To understand why this is so, empirical observations on the neural correlates of consciousness need to be complemented by a principled theoretical approach. Otherwise, it is unlikely that we could ever establish to what extent consciousness is present in neurological conditions such as akinetic mutism, psychomotor seizures, or sleepwalking, and to what extent it is present in newborn babies and animals. A principled approach is provided by the information integration theory of consciousness. This theory claims that consciousness corresponds to a system's capacity to integrate information, and proposes a way to measure such capacity. The information integration theory can account for several neurobiological observations concerning consciousness, including: (i) the association of consciousness with certain neural systems rather than with others; (ii) the fact that neural processes underlying consciousness can influence or be influenced by neural processes that remain unconscious; (iii) the reduction of consciousness during dreamless sleep and generalized seizures; and (iv) the time requirements on neural interactions that support consciousness.
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.
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.
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.
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.
In vitro models and systems for evaluating the dynamics of drug delivery to the healthy and diseased brain.

PubMed

Modarres, Hassan Pezeshgi; Janmaleki, Mohsen; Novin, Mana; Saliba, John; El-Hajj, Fatima; RezayatiCharan, Mahdi; Seyfoori, Amir; Sadabadi, Hamid; Vandal, Milène; Nguyen, Minh Dang; Hasan, Anwarul; Sanati-Nezhad, Amir

2018-03-10

The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis and transport of drugs to the brain. The conventional animal and Transwell BBB models along with emerging microfluidic-based BBB-on-chip systems have provided fundamental functionalities of the BBB and facilitated the testing of drug delivery to the brain tissue. However, developing biomimetic and predictive BBB models capable of reasonably mimicking essential characteristics of the BBB functions is still a challenge. In addition, detailed analysis of the dynamics of drug delivery to the healthy or diseased brain requires not only biomimetic BBB tissue models but also new systems capable of monitoring the BBB microenvironment and dynamics of barrier function and delivery mechanisms. This review provides a comprehensive overview of recent advances in microengineering of BBB models with different functional complexity and mimicking capability of healthy and diseased states. It also discusses new technologies that can make the next generation of biomimetic human BBBs containing integrated biosensors for real-time monitoring the tissue microenvironment and barrier function and correlating it with the dynamics of drug delivery. Such integrated system addresses important brain drug delivery questions related to the treatment of brain diseases. We further discuss how the combination of in vitro BBB systems, computational models and nanotechnology supports for characterization of the dynamics of drug delivery to the brain. Copyright © 2018 Elsevier B.V. All rights reserved.
The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

PubMed

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

2018-06-01

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

PubMed Central

Howes, Oliver D; Murray, Robin M

2014-01-01

Schizophrenia remains a major burden1. The dopamine (DA) and neurodevelopmental hypotheses attempt to explain the pathogenic mechanisms and origins of the disorder respectively2-4. Recently an alternative, the cognitive model, has gained popularity5. However the first two theories have not been satisfactorily integrated, and the most influential iteration of the cognitive model makes no mention of DA, neurodevelopment, or indeed the brain5. Here we show that developmental alterations secondary to variant genes, early hazards to the brain and childhood adversity, sensitise the DA system, and result in excessive presynaptic DA synthesis and DA release. Social adversity biases the cognitive schema that the individual uses to interpret experiences towards paranoid interpretations. Subsequent stress results in dysregulated DA release, causing the misattribution of salience to stimuli, which are then misinterpreted by the biased cognitive processes. The resulting paranoia and hallucinations in turn cause further stress, and eventually repeated DA dysregulation hard-wires the psychotic beliefs. Finally we consider the implications of this model for understanding and treating schizophrenia. PMID:24315522
Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction.

PubMed

Zhu, Zude; Yang, Fengjun; Li, Dongning; Zhou, Lianjun; Liu, Ying; Zhang, Ying; Chen, Xuezhi

2017-01-01

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

PubMed

Moser, D A; Doucet, G E; Ing, A; Dima, D; Schumann, G; Bilder, R M; Frangou, S

2017-12-05

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network.Molecular Psychiatry advance online publication, 5 December 2017; doi:10.1038/mp.2017.247.

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.
Multicolor Fluorescence Imaging of Traumatic Brain Injury in a Cryolesion Mouse Model

PubMed Central

2012-01-01

Traumatic brain injury is characterized by initial tissue damage, which then can lead to secondary processes such as cell death and blood-brain-barrier disruption. Clinical and preclinical studies of traumatic brain injury typically employ anatomical imaging techniques and there is a need for new molecular imaging methods that provide complementary biochemical information. Here, we assess the ability of a targeted, near-infrared fluorescent probe, named PSS-794, to detect cell death in a brain cryolesion mouse model that replicates certain features of traumatic brain injury. In short, the model involves brief contact of a cold rod to the head of a living, anesthetized mouse. Using noninvasive whole-body fluorescence imaging, PSS-794 permitted visualization of the cryolesion in the living animal. Ex vivo imaging and histological analysis confirmed PSS-794 localization to site of brain cell death. The nontargeted, deep-red Tracer-653 was validated as a tracer dye for monitoring blood-brain-barrier disruption, and a binary mixture of PSS-794 and Tracer-653 was employed for multicolor imaging of cell death and blood-brain-barrier permeability in a single animal. The imaging data indicates that at 3 days after brain cryoinjury the amount of cell death had decreased significantly, but the integrity of the blood-brain-barrier was still impaired; at 7 days, the blood-brain-barrier was still three times more permeable than before cryoinjury. PMID:22860222
An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

PubMed

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

2017-11-22

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

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

Lagerwaard, Frank J.; Hoorn, Elles A.P. van der; Verbakel, Wilko

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

PubMed

Chow, Hei-man; Herrup, Karl

2015-11-01

DNA damage is correlated with and may drive the ageing process. Neurons in the brain are postmitotic and are excluded from many forms of DNA repair; therefore, neurons are vulnerable to various neurodegenerative diseases. The challenges facing the field are to understand how and when neuronal DNA damage accumulates, how this loss of genomic integrity might serve as a 'time keeper' of nerve cell ageing and why this process manifests itself as different diseases in different individuals.
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.
Endothelial β-Catenin Signaling Is Required for Maintaining Adult Blood-Brain Barrier Integrity and Central Nervous System Homeostasis.

PubMed

Tran, Khiem A; Zhang, Xianming; Predescu, Dan; Huang, Xiaojia; Machado, Roberto F; Göthert, Joachim R; Malik, Asrar B; Valyi-Nagy, Tibor; Zhao, You-Yang

2016-01-12

The blood-brain barrier (BBB) formed by brain endothelial cells interconnected by tight junctions is essential for the homeostasis of the central nervous system. Although studies have shown the importance of various signaling molecules in BBB formation during development, little is known about the molecular basis regulating the integrity of the adult BBB. Using a mouse model with tamoxifen-inducible endothelial cell-restricted disruption of ctnnb1 (iCKO), we show here that endothelial β-catenin signaling is essential for maintaining BBB integrity and central nervous system homeostasis in adult mice. The iCKO mice developed severe seizures accompanied by neuronal injury, multiple brain petechial hemorrhages, and central nervous system inflammation, and all had postictal death. Disruption of endothelial β-catenin induced BBB breakdown and downregulation of the specific tight junction proteins claudin-1 and -3 in adult brain endothelial cells. The clinical relevance of the data is indicated by the observation of decreased expression of claudin-1 and nuclear β-catenin in brain endothelial cells of hemorrhagic lesions of hemorrhagic stroke patients. These results demonstrate the prerequisite role of endothelial β-catenin in maintaining the integrity of adult BBB. The results suggest that BBB dysfunction secondary to defective β-catenin transcription activity is a key pathogenic factor in hemorrhagic stroke, seizure activity, and central nervous system inflammation. © 2015 American Heart Association, Inc.
MicroCT and microMRI imaging of a prenatal mouse model of increased brain size

NASA Astrophysics Data System (ADS)

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

2008-08-01

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

PubMed

Zhan, Rui; Zhao, Mingming; Zhou, Ting; Chen, Yue; Yu, Weiwei; Zhao, Lei; Zhang, Tao; Wang, Hecheng; Yang, Huan; Jin, Yinglan; He, Qihua; Yang, Xiaoda; Guo, Xiangyang; Willard, Belinda; Pan, Bing; Huang, Yining; Chen, Yingyu; Chui, Dehua; Zheng, Lemin

2018-06-07

Atherosclerosis was considered to induce many vascular-related complications, such as acute myocardial infarction and stroke. Abnormal lipid metabolism and its peroxidation inducing blood-brain barrier (BBB) leakage were associated with the pre-clinical stage of stroke. Dapsone (DDS), an anti-inflammation and anti-oxidation drug, has been found to have protective effects on vascular. However, whether DDS has a protective role on brain microvessels during lipid oxidation had yet to be elucidated. We investigated brain microvascular integrity in a high-fat diet (HFD) mouse model. We designed this study to explore whether DDS had protective effects on brain microvessels under lipid oxidation and tried to explain the underlying mechanism. In our live optical study, we found that DDS significantly attenuated brain microvascular leakage through reducing serum oxidized low-density lipoprotein (oxLDL) in HFD mice (p < 0.001), and DDS significantly inhibited LDL oxidation in vitro (p < 0.001). Our study showed that DDS protected tight junction proteins: ZO-1 (p < 0.001), occludin (p < 0.01), claudin-5 (p < 0.05) of microvascular endothelial cells in vivo and in vitro. DDS reversed LAMP1 aggregation in cytoplasm, and decreased the destruction of tight junction protein: ZO-1 in vitro. We first revealed that DDS had a protective role on cerebral microvessels through preventing tight junction ZO-1 from abnormal degradation by autophagy and reducing lysosome accumulation. Our findings suggested the significance of DDS in protecting brain microvessels under lipid metabolic disorders, which revealed a novel potential therapeutic strategy in brain microvascular-related diseases.
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
Developing a comprehensive framework of community integration for people with acquired brain injury: a conceptual analysis.

PubMed

Shaikh, Nusratnaaz M; Kersten, Paula; Siegert, Richard J; Theadom, Alice

2018-03-06

Despite increasing emphasis on the importance of community integration as an outcome for acquired brain injury (ABI), there is still no consensus on the definition of community integration. The aim of this study was to complete a concept analysis of community integration in people with ABI. The method of concept clarification was used to guide concept analysis of community integration based on a literature review. Articles were included if they explored community integration in people with ABI. Data extraction was performed by the initial coding of (1) the definition of community integration used in the articles, (2) attributes of community integration recognized in the articles' findings, and (3) the process of community integration. This information was synthesized to develop a model of community integration. Thirty-three articles were identified that met the inclusion criteria. The construct of community integration was found to be a non-linear process reflecting recovery over time, sequential goals, and transitions. Community integration was found to encompass six components including: independence, sense of belonging, adjustment, having a place to live, involved in a meaningful occupational activity, and being socially connected into the community. Antecedents to community integration included individual, injury-related, environmental, and societal factors. The findings of this concept analysis suggest that the concept of community integration is more diverse than previously recognized. New measures and rehabilitation plans capturing all attributes of community integration are needed in clinical practice. Implications for rehabilitation Understanding of perceptions and lived experiences of people with acquired brain injury through this analysis provides basis to ensure rehabilitation meets patients' needs. This model highlights the need for clinicians to be aware and assess the role of antecedents as well as the attributes of community integration itself to
Disruption of blood-brain barrier integrity in postmortem alcoholic brain: preclinical evidence of TLR4 involvement from a binge-like drinking model.

PubMed

Rubio-Araiz, Ana; Porcu, Francesca; Pérez-Hernández, Mercedes; García-Gutiérrez, Mª Salud; Aracil-Fernández, María Auxiliadora; Gutierrez-López, María Dolores; Guerri, Consuelo; Manzanares, Jorge; O'Shea, Esther; Colado, María Isabel

2017-07-01

Inflammatory cytokines and reactive oxygen species are reported to be involved in blood-brain barrier (BBB) disruption. Because there is evidence that ethanol (EtOH) induces release of free radicals, cytokines and inflammatory mediators we examined BBB integrity and matrix metalloproteinase (MMP) activity in postmortem human alcoholic brain and investigated the role of TLR4 signaling in BBB permeability in TLR4-knockout mice under a binge-like EtOH drinking protocol. Immunohistochemical studies showed reduced immunoreactivity of the basal lamina protein, collagen-IV and of the tight junction protein, claudin-5 in dorsolateral prefrontal cortex of alcoholics. There was also increased MMP-9 activity and expression of phosphorylated ERK1/2 and p-38. Greater number of CD45+ IR cells were observed associated with an enhanced neuroinflammatory response reflected by increased GFAP and Iba-1 immunostaining. To further explore effects of high EtOH consumption on BBB integrity we studied TLR4-knockout mice exposed to the drinking in the dark paradigm. Repetitive EtOH exposure in wild-type mice decreased hippocampal expression of laminin and collagen-IV and increased IgG immunoreactivity, indicating IgG extravasation. Western blot analysis also revealed increased MyD88 and p-ERK1/2 levels. None of these changes was observed in TLR4-knockout mice. Collectively, these findings indicate that chronic EtOH increases degradation of tight junctions and extracellular matrix in postmortem human brain and induces a neuroinflammatory response associated with activation of ERK1/2 and p-38 and greater MMP-9 activity. The EtOH-induced effects on BBB impairment are not evident in the hippocampus of TLR4-knockout mice, suggesting the involvement of TLR4 signaling in the underlying mechanism leading to BBB disruption in mice. © 2016 Society for the Study of Addiction.
Through the Immune Looking Glass: A Model for Brain Memory Strategies

PubMed Central

Sánchez-Ramón, Silvia; Faure, Florence

2016-01-01

The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust’s madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective. PMID:26869886
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
An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

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

2017-01-01

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

PubMed Central

Vemana, Vinith

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

HSP27 Protects the Blood-Brain Barrier Against Ischemia-Induced Loss of Integrity

PubMed Central

Leak, Rehana K.; Zhang, Lili; Stetler, R. Anne; Weng, Zhongfang; Li, Peiying; Atkins, G. Brandon; Gao, Yanqin; Chen, Jun

2014-01-01

Loss of integrity of the blood-brain barrier (BBB) in stroke victims initiates a devastating cascade of events including extravasation of blood-borne molecules, water, and inflammatory cells deep into brain parenchyma. Thus, it is important to identify mechanisms by which BBB integrity can be maintained in the face of ischemic injury in experimental stroke. We previously demonstrated that the phylogenetically conserved small heat shock protein 27 (HSP27) protects against transient middle cerebral artery occlusion (tMCAO). Here we show that HSP27 transgenic overexpression also maintains the integrity of the BBB in mice subjected to tMCAO. Extravasation of endogenous IgG antibodies and exogenous FITC-albumin into the brain following tMCAO was reduced in transgenic mice, as was total brain water content. HSP27 overexpression abolished the appearance of TUNEL-positive profiles in microvessel walls. Transgenics also exhibited less loss of microvessel proteins following tMCAO. Notably, primary endothelial cell cultures were rescued from oxygen-glucose deprivation (OGD) by lentiviral HSP27 overexpression according to four viability assays, supporting a direct effect on this cell type. Finally, HSP27 overexpression reduced the appearance of neutrophils in the brain and inhibited the secretion of five cytokines. These findings reveal a novel role for HSP27 in attenuating ischemia/reperfusion injury - the maintenance of BBB integrity. Endogenous upregulation of HSP27 after ischemia in wild-type animals may exert similar protective functions and warrants further investigation. Exogenous enhancement of HSP27 by rational drug design may lead to future therapies against a host of injuries, including but not limited to a harmful breach in brain vasculature. PMID:23469858
Human Brain Modeling with Its Anatomical Structure and Realistic Material Properties for Brain Injury Prediction.

PubMed

Atsumi, Noritoshi; Nakahira, Yuko; Tanaka, Eiichi; Iwamoto, Masami

2018-05-01

Impairments of executive brain function after traumatic brain injury (TBI) due to head impacts in traffic accidents need to be obviated. Finite element (FE) analyses with a human brain model facilitate understanding of the TBI mechanisms. However, conventional brain FE models do not suitably describe the anatomical structure in the deep brain, which is a critical region for executive brain function, and the material properties of brain parenchyma. In this study, for better TBI prediction, a novel brain FE model with anatomical structure in the deep brain was developed. The developed model comprises a constitutive model of brain parenchyma considering anisotropy and strain rate dependency. Validation was performed against postmortem human subject test data associated with brain deformation during head impact. Brain injury analyses were performed using head acceleration curves obtained from reconstruction analysis of rear-end collision with a human whole-body FE model. The difference in structure was found to affect the regions of strain concentration, while the difference in material model contributed to the peak strain value. The injury prediction result by the proposed model was consistent with the characteristics in the neuroimaging data of TBI patients due to traffic accidents.
Improvement of Blood-Brain Barrier Integrity in Traumatic Brain Injury and Hemorrhagic Shock Following Treatment With Valproic Acid and Fresh Frozen Plasma.

PubMed

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

2018-01-01

Combined traumatic brain injury and hemorrhagic shock are highly lethal. Following injuries, the integrity of the blood-brain barrier can be impaired, contributing to secondary brain insults. The status of the blood-brain barrier represents a potential factor impacting long-term neurologic outcomes in combined injuries. Treatment strategies involving plasma-based resuscitation and valproic acid therapy have shown efficacy in this setting. We hypothesize that a component of this beneficial effect is related to blood-brain barrier preservation. Following controlled traumatic brain injury, hemorrhagic shock, various resuscitation and treatment strategies were evaluated for their association with blood-brain barrier integrity. Analysis of gene expression profiles was performed using Porcine Gene ST 1.1 microarray. Pathway analysis was completed using network analysis tools (Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene Set Enrichment Analysis). Female Yorkshire swine were subjected to controlled traumatic brain injury and 2 hours of hemorrhagic shock (40% blood volume, mean arterial pressure 30-35 mmHg). Subjects were resuscitated with 1) normal saline, 2) fresh frozen plasma, 3) hetastarch, 4) fresh frozen plasma + valproic acid, or 5) hetastarch + valproic acid (n = 5 per group). After 6 hours of observation, brains were harvested for evaluation. Immunofluoroscopic evaluation of the traumatic brain injury site revealed significantly increased expression of tight-junction associated proteins (zona occludin-1, claudin-5) following combination therapy (fresh frozen plasma + valproic acid and hetastarch + valproic acid). The extracellular matrix protein laminin was found to have significantly improved expression with combination therapies. Pathway analysis indicated that valproic acid significantly modulated pathways involved in endothelial barrier function and cell signaling. Resuscitation with fresh frozen plasma results in improved expression of
Dynamic monitoring of blood-brain barrier integrity using water exchange index (WEI) during mannitol and CO2 challenges in mouse brain.

PubMed

Huang, Shuning; Farrar, Christian T; Dai, Guangping; Kwon, Seon Joo; Bogdanov, Alexei A; Rosen, Bruce R; Kim, Young R

2013-04-01

The integrity of the blood-brain barrier (BBB) is critical to normal brain function. Traditional techniques for the assessment of BBB disruption rely heavily on the spatiotemporal analysis of extravasating contrast agents. However, such methods based on the leakage of relatively large molecules are not suitable for the detection of subtle BBB impairment or for the performance of repeated measurements in a short time frame. Quantification of the water exchange rate constant (WER) across the BBB using strictly intravascular contrast agents could provide a much more sensitive method for the quantification of the BBB integrity. To estimate WER, we have recently devised a powerful new method using a water exchange index (WEI) biomarker and demonstrated BBB disruption in an acute stroke model. Here, we confirm that WEI is sensitive to even very subtle changes in the integrity of the BBB caused by: (i) systemic hypercapnia and (ii) low doses of a hyperosmolar solution. In addition, we have examined the sensitivity and accuracy of WEI as a biomarker of WER using computer simulation. In particular, the dependence of the WEI-WER relation on changes in vascular blood volume, T1 relaxation of cellular magnetization and transcytolemmal water exchange was explored. Simulated WEI was found to vary linearly with WER for typically encountered exchange rate constants (1-4 Hz), regardless of the blood volume. However, for very high WER (>5 Hz), WEI became progressively more insensitive to increasing WER. The incorporation of transcytolemmal water exchange, using a three-compartment tissue model, helped to extend the linear WEI regime to slightly higher WER, but had no significant effect for most physiologically important WERs (WER < 4 Hz). Variation in cellular T1 had no effect on WEI. Using both theoretical and experimental approaches, our study validates the utility of the WEI biomarker for the monitoring of BBB integrity. Copyright © 2012 John Wiley & Sons, Ltd.
Dynamic Monitoring of Blood-Brain Barrier Integrity using Water Exchange Index (WEI) During Mannitol and CO2 Challenges in Mouse Brain

PubMed Central

Huang, Shuning; Farrar, Christian T.; Dai, Guangping; Kwon, Seon Joo; Bogdanov, Alexei A.; Rosen, Bruce R.; Kim, Young R.

2012-01-01

The integrity of the blood-brain barrier (BBB) is critical to normal brain function. Traditional techniques for assessing BBB disruption rely heavily on the spatiotemporal analysis of extravasating contrast agents. But such methods based on the leakage of relatively large molecules are not suitable to detect subtle BBB impairment or to perform repeated measurements in a short time frame. Quantification of the water exchange rate constant (WER) across the BBB using strictly intravascular contrast agents could provide a much more sensitive method for quantifying the BBB integrity. For estimating the WER, we have recently devised a powerful new method using a water exchange index (WEI) biomarker and demonstrated BBB disruption in an acute stroke model. Here we confirm that the WEI is sensitive to even very subtle changes in the integrity of the BBB caused by (1) systemic hypercapnia and (2) low doses of a hyperosmolar solution. In addition, we have examined the sensitivity and accuracy of the WEI as a biomarker of the WER using computer simulation. In particular, the dependence of the WEI-WER relation on changes in vascular blood volume, T1 relaxation of cellular magnetization, and transcytolemmal water exchange was explored. The simulated WEI was found to vary linearly with the WER for typically encountered exchange rate constants (1–4 Hz) regardless of the blood volume. However, for very high WER (>5 Hz) the WEI became progressively more insensitive to increasing WER. The incorporation of transcytolemmal water exchange, using a three-compartment tissue model, helped to extend the linear WEI regime to slightly higher WER, but had no significant effect for most physiologically important water exchange rate constants (WER<4 Hz). Variation in the cellular T1 had no effect on the WEI. Using both theoretical and experimental approaches, our study validates the utility of the WEI biomarker for monitoring BBB integrity. PMID:23055278
Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

PubMed

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

2017-05-15

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

PubMed

Bonate, P L

1995-01-01

There are many reasons for wishing to determine the rate of uptake of a drug from blood into brain parenchyma. However, when faced with doing so for the first time, choosing a method can be a formidable task. There are at least 7 methods from which to choose: indicator dilution, brain uptake index, microdialysis, external registration, PET scanning, in situ perfusion, and compartmental modeling. Each method has advantages and disadvantages. Some methods require very little equipment while others require equipment that can cost millions of dollars. Some methods require very little technical experience whereas others require complex surgical manipulation. The mathematics alone for the various methods range from simple algebra to complex integral calculus and differential equations. Like most things in science, as the complexity of the technique increases, so does the quantity of information it provides. This review is meant to serve as a starting point for the researcher who wishes to study transport and uptake across the blood-brain barrier in animal models. An overview of the mathematical theory, as well as an introduction to the techniques, is presented.
New experimental models of the blood-brain barrier for CNS drug discovery

PubMed Central

Kaisar, Mohammad A.; Sajja, Ravi K.; Prasad, Shikha; Abhyankar, Vinay V.; Liles, Taylor; Cucullo, Luca

2017-01-01

Introduction The blood-brain barrier (BBB) is a dynamic biological interface which actively controls the passage of substances between the blood and the central nervous system (CNS). From a biological and functional standpoint, the BBB plays a crucial role in maintaining brain homeostasis inasmuch that deterioration of BBB functions are prodromal to many CNS disorders. Conversely, the BBB hinders the delivery of drugs targeting the brain to treat a variety of neurological diseases. Area covered This article reviews recent technological improvements and innovation in the field of BBB modeling including static and dynamic cell-based platforms, microfluidic systems and the use of stem cells and 3D printing technologies. Additionally, the authors laid out a roadmap for the integration of microfluidics and stem cell biology as a holistic approach for the development of novel in vitro BBB platforms. Expert opinion Development of effective CNS drugs has been hindered by the lack of reliable strategies to mimic the BBB and cerebrovascular impairments in vitro. Technological advancements in BBB modeling have fostered the development of highly integrative and quasi- physiological in vitro platforms to support the process of drug discovery. These advanced in vitro tools are likely to further current understanding of the cerebrovascular modulatory mechanisms. PMID:27782770
Zika virus crosses an in vitro human blood brain barrier model.

PubMed

Alimonti, Judie B; Ribecco-Lutkiewicz, Maria; Sodja, Caroline; Jezierski, Anna; Stanimirovic, Danica B; Liu, Qing; Haqqani, Arsalan S; Conlan, Wayne; Bani-Yaghoub, Mahmud

2018-05-15

Zika virus (ZIKV) is a flavivirus that is highly neurotropic causing congenital abnormalities and neurological damage to the central nervous systems (CNS). In this study, we used a human induced pluripotent stem cell (iPSC)-derived blood brain barrier (BBB) model to demonstrate that ZIKV can infect brain endothelial cells (i-BECs) without compromising the BBB barrier integrity or permeability. Although no disruption to the BBB was observed post-infection, ZIKV particles were released on the abluminal side of the BBB model and infected underlying iPSC-derived neural progenitor cells (i-NPs). AXL, a putative ZIKV cellular entry receptor, was also highly expressed in ZIKV-susceptible i-BEC and i-NPs. This iPSC-derived BBB model can help elucidate the mechanism by which ZIKV can infect BECs, cross the BBB and gain access to the CNS.
Improving the clinical management of traumatic brain injury through the pharmacokinetic modeling of peripheral blood biomarkers.

PubMed

Dadas, Aaron; Washington, Jolewis; Marchi, Nicola; Janigro, Damir

2016-11-30

Blood biomarkers of neurovascular damage are used clinically to diagnose the presence severity or absence of neurological diseases, but data interpretation is confounded by a limited understanding of their dependence on variables other than the disease condition itself. These include half-life in blood, molecular weight, and marker-specific biophysical properties, as well as the effects of glomerular filtration, age, gender, and ethnicity. To study these factors, and to provide a method for markers' analyses, we developed a kinetic model that allows the integrated interpretation of these properties. The pharmacokinetic behaviors of S100B (monomer and homodimer), Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase L1 were modeled using relevant chemical and physical properties; modeling results were validated by comparison with data obtained from healthy subjects or individuals affected by neurological diseases. Brain imaging data were used to model passage of biomarkers across the blood-brain barrier. Our results show the following: (1) changes in biomarker serum levels due to age or disease progression are accounted for by differences in kidney filtration; (2) a significant change in the brain-to-blood volumetric ratio, which is characteristic of infant and adult development, contributes to variation in blood concentration of biomarkers; (3) the effects of extracranial contribution at steady-state are predicted in our model to be less important than suspected, while the contribution of blood-brain barrier disruption is confirmed as a significant factor in controlling markers' appearance in blood, where the biomarkers are typically detected; (4) the contribution of skin to the marker S100B blood levels depends on a direct correlation with pigmentation and not ethnicity; the contribution of extracranial sources for other markers requires further investigation. We developed a multi-compartment, pharmacokinetic model that integrates the biophysical
Reduced integration and improved segregation of functional brain networks in Alzheimer's disease.

PubMed

Kabbara, A; Eid, H; El Falou, W; Khalil, M; Wendling, F; Hassan, M

2018-04-01

Emerging evidence shows that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients' functional brain networks and their cognitive scores. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.
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
A prospective study to evaluate a new residential community reintegration programme for severe chronic brain injury: the Brain Integration Programme.

PubMed

Geurtsen, G J; Martina, J D; Van Heugten, C M; Geurts, A C H

2008-07-01

To assess the effectiveness of a residential community reintegration programme for participants with chronic sequelae of severe acquired brain injury that hamper community functioning. Prospective cohort study. Twenty-four participants with acquired brain injury (traumatic n = 18; stroke n = 3, tumour n = 2, encephalitis n = 1). Participants had impaired illness awareness, alcohol and drug problems and/or behavioural problems. A skills-oriented programme with modules related to independent living, work, social and emotional well-being. The Community Integration Questionnaire, CES-Depression, EuroQOL, Employability Rating Scale, living situation and work status were scored at the start (T0), end of treatment (T1) and 1-year follow-up (T2). Significant effects on the majority of outcome measures were present at T1. Employability significantly improved at T2 and living independently rose from 42% to over 70%. Participants working increased from 38% to 58% and the hours of work per week increased from 8 to 15. The Brain Integration Programme led to a sustained reduction in experienced problems and improved community integration. It is concluded that even participants with complex problems due to severe brain injury who got stuck in life could improve their social participation and emotional well-being through a residential community reintegration programme.
Seizure Control and Memory Impairment Are Related to Disrupted Brain Functional Integration in Temporal Lobe Epilepsy.

PubMed

Park, Chang-Hyun; Choi, Yun Seo; Jung, A-Reum; Chung, Hwa-Kyoung; Kim, Hyeon Jin; Yoo, Jeong Hyun; Lee, Hyang Woon

2017-01-01

Brain functional integration can be disrupted in patients with temporal lobe epilepsy (TLE), but the clinical relevance of this disruption is not completely understood. The authors hypothesized that disrupted functional integration over brain regions remote from, as well as adjacent to, the seizure focus could be related to clinical severity in terms of seizure control and memory impairment. Using resting-state functional MRI data acquired from 48 TLE patients and 45 healthy controls, the authors mapped functional brain networks and assessed changes in a network parameter of brain functional integration, efficiency, to examine the distribution of disrupted functional integration within and between brain regions. The authors assessed whether the extent of altered efficiency was influenced by seizure control status and whether the degree of altered efficiency was associated with the severity of memory impairment. Alterations in the efficiency were observed primarily near the subcortical region ipsilateral to the seizure focus in TLE patients. The extent of regional involvement was greater in patients with poor seizure control: it reached the frontal, temporal, occipital, and insular cortices in TLE patients with poor seizure control, whereas it was limited to the limbic and parietal cortices in TLE patients with good seizure control. Furthermore, TLE patients with poor seizure control experienced more severe memory impairment, and this was associated with lower efficiency in the brain regions with altered efficiency. These findings indicate that the distribution of disrupted brain functional integration is clinically relevant, as it is associated with seizure control status and comorbid memory impairment.
Decomposing Gratitude: Representation and Integration of Cognitive Antecedents of Gratitude in the Brain.

PubMed

Yu, Hongbo; Gao, Xiaoxue; Zhou, Yuanyuan; Zhou, Xiaolin

2018-05-23

Gratitude is a typical social-moral emotion that plays a crucial role in maintaining human cooperative interpersonal relationship. Although neural correlates of gratitude have been investigated, the neurocognitive processes that lead to gratitude, namely, the representation and integration of its cognitive antecedents, remain largely unknown. Here, we combined fMRI and a human social interactive task to investigate how benefactor's cost and beneficiary's benefit, two critical antecedents of gratitude, are encoded and integrated in beneficiary's brain, and how the neural processing of gratitude is converted to reciprocity. A coplayer decided whether to help a human participant (either male or female) avoid pain at his/her own monetary cost; the participants could transfer monetary points to the benefactor with the knowledge that the benefactor was unaware of this transfer. By independently manipulating monetary cost and the degree of pain reduction, we could identify the neural signatures of benefactor's cost and recipient's benefit and examine how they were integrated. Recipient's self-benefit was encoded in reward-sensitive regions (e.g., ventral striatum), whereas benefactor-cost was encoded in regions associated with mentalizing (e.g., temporoparietal junction). Gratitude was represented in perigenual anterior cingulate cortex (pgACC), the strength of which correlated with trait gratitude. Dynamic causal modeling showed that the neural signals representing benefactor-cost and self-benefit passed to pgACC via effective connectivities, suggesting an integrative role of pgACC in generating gratitude. Moreover, gyral ACC plays an intermediary role in converting gratitude representation into reciprocal behaviors. Our findings provide a neural mechanistic account of gratitude and its role in social-moral life. SIGNIFICANCE STATEMENT Gratitude plays an integral role in subjective well-being and harmonious interpersonal relationships. However, the neurocognitive
The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

PubMed Central

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

2015-01-01

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

PubMed

Beuter, Anne

2017-05-01

Recent publications call for more animal models to be used and more experiments to be performed, in order to better understand the mechanisms of neurodegenerative disorders, to improve human health, and to develop new brain stimulation treatments. In response to these calls, some limitations of the current animal models are examined by using Deep Brain Stimulation (DBS) in Parkinson's disease as an illustrative example. Without focusing on the arguments for or against animal experimentation, or on the history of DBS, the present paper argues that given recent technological and theoretical advances, the time has come to consider bioinspired computational modelling as a valid alternative to animal models, in order to design the next generation of human brain stimulation treatments. However, before computational neuroscience is fully integrated in the translational process and used as a substitute for animal models, several obstacles need to be overcome. These obstacles are examined in the context of institutional, financial, technological and behavioural lock-in. Recommendations include encouraging agreement to change long-term habitual practices, explaining what alternative models can achieve, considering economic stakes, simplifying administrative and regulatory constraints, and carefully examining possible conflicts of interest. 2017 FRAME.
Functional integrity in children with anoxic brain injury from drowning.

PubMed

Ishaque, Mariam; Manning, Janessa H; Woolsey, Mary D; Franklin, Crystal G; Tullis, Elizabeth W; Beckmann, Christian F; Fox, Peter T

2017-10-01

Drowning is a leading cause of accidental injury and death in young children. Anoxic brain injury (ABI) is a common consequence of drowning and can cause severe neurological morbidity in survivors. Assessment of functional status and prognostication in drowning victims can be extremely challenging, both acutely and chronically. Structural neuroimaging modalities (CT and MRI) have been of limited clinical value. Here, we tested the utility of resting-state functional MRI (rs-fMRI) for assessing brain functional integrity in this population. Eleven children with chronic, spastic quadriplegia due to drowning-induced ABI were investigated. All were comatose immediately after the injury and gradually regained consciousness, but with varying ability to communicate their cognitive state. Eleven neurotypical children matched for age and gender formed the control group. Resting-state fMRI and co-registered T1-weighted anatomical MRI were acquired at night during drug-aided sleep. Network integrity was quantified by independent components analysis (ICA), at both group- and per-subject levels. Functional-status assessments based on in-home observations were provided by families and caregivers. Motor ICNs were grossly compromised in ABI patients both group-wise and individually, concordant with their prominent motor deficits. Striking preservations of perceptual and cognitive ICNs were observed, and the degree of network preservation correlated (ρ = 0.74) with the per-subject functional status assessments. Collectively, our findings indicate that rs-fMRI has promise for assessing brain functional integrity in ABI and, potentially, in other disorders. Furthermore, our observations suggest that the severe motor deficits observed in this population can mask relatively intact perceptual and cognitive capabilities. Hum Brain Mapp 38:4813-4831, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Trafficking of adeno-associated virus vectors across a model of the blood-brain barrier; a comparative study of transcytosis and transduction using primary human brain endothelial cells.

PubMed

Merkel, Steven F; Andrews, Allison M; Lutton, Evan M; Mu, Dakai; Hudry, Eloise; Hyman, Bradley T; Maguire, Casey A; Ramirez, Servio H

2017-01-01

Developing therapies for central nervous system (CNS) diseases is exceedingly difficult because of the blood-brain barrier (BBB). Notably, emerging technologies may provide promising new options for the treatment of CNS disorders. Adeno-associated virus serotype 9 (AAV9) has been shown to transduce cells in the CNS following intravascular administration in rodents, cats, pigs, and non-human primates. These results suggest that AAV9 is capable of crossing the BBB. However, mechanisms that govern AAV9 transendothelial trafficking at the BBB remain unknown. Furthermore, possibilities that AAV9 may transduce brain endothelial cells or affect BBB integrity still require investigation. Using primary human brain microvascular endothelial cells as a model of the human BBB, we performed transduction and transendothelial trafficking assays comparing AAV9 to AAV2, a serotype that does not cross the BBB or transduce endothelial cells effectively in vivo. Results of our in vitro studies indicate that AAV9 penetrates brain microvascular endothelial cells barriers more effectively than AAV2, but has reduced transduction efficiency. In addition, our data suggest that (i) AAV9 penetrates endothelial barriers through an active, cell-mediated process, and (ii) AAV9 fails to disrupt indicators of BBB integrity such as transendothelial electrical resistance, tight junction protein expression/localization, and inflammatory activation status. Overall, this report shows how human brain endothelial cells configured in BBB models can be utilized for evaluating transendothelial movement and transduction kinetics of various AAV capsids. Importantly, the use of a human in vitro BBB model can provide import insight into the possible effects that candidate AVV gene therapy vectors may have on the status of BBB integrity. Read the Editorial Highlight for this article on page 192. © 2016 International Society for Neurochemistry.
Integrative structure modeling with the Integrative Modeling Platform.

PubMed

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

2018-01-01

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

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

PubMed

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

2018-05-01

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

NASA Astrophysics Data System (ADS)

Berkovich, Simon; Berkovich, Efraim; Lapir, Gennady

1997-08-01

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

PubMed

Stockton, David B; Santamaria, Fidel

2017-10-01

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

PubMed Central

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

2017-01-01

Abstract See Lytton (doi:10.1093/awx018) for a scientific commentary on this article. Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. PMID:28364550
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
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.
Individual brain structure and modelling predict seizure propagation.

PubMed

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

2017-03-01

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

PubMed Central

Small, Steven L.; Buccino, Giovanni; Solodkin, Ana

2017-01-01

Following stroke, patients are commonly left with debilitating motor and speech impairments. This article reviews the state of the art in neurological repair for stroke and proposes a new model for the future. We suggest that stroke treatment—from the time of the ictus itself to living with the consequences—must be fundamentally neurological, from limiting the extent of injury at the outset, to repairing the consequent damage. Our model links brain and behaviour by targeting brain circuits, and we illustrate the model though action observation treatment, which aims to enhance brain network connectivity. The model is based on the assumptions that the mechanisms of neural repair inherently involve cellular and circuit plasticity, that brain plasticity is a synaptic phenomenon that is largely stimulus-dependent, and that brain repair required both physical and behavioural interventions that are tailored to reorganize specific brain circuits. We review current approaches to brain repair after stroke and present our new model, and discuss the biological foundations, rationales, and data to support our novel approach to upper-extremity and language rehabilitation. We believe that by enhancing plasticity at the level of brain network interactions, this neurological model for brain repair could ultimately lead to a cure for stroke. PMID:24217509
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.
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.
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
Integrated Photonic Neural Probes for Patterned Brain Stimulation

DTIC Science & Technology

2017-08-14

two -photon imaging Task 3.2: In vivo demonstration of remote optical stimulation using photonic probes and multi -site electrical recording...have patterned nine e-pixels. We can individually address each e-pixel by tuning the color of the input light to the AWG. Figure (8) shows two ...Report: Integrated Photonic Neural Probes for Patterned Brain Stimulation The views , opinions and/or findings contained in this report are those of the
Impact of Blood-Brain Barrier Integrity on Tumor Growth and Therapy Response in Brain Metastases.

PubMed

Osswald, Matthias; Blaes, Jonas; Liao, Yunxiang; Solecki, Gergely; Gömmel, Miriam; Berghoff, Anna S; Salphati, Laurent; Wallin, Jeffrey J; Phillips, Heidi S; Wick, Wolfgang; Winkler, Frank

2016-12-15

The role of blood-brain barrier (BBB) integrity for brain tumor biology and therapy is a matter of debate. We developed a new experimental approach using in vivo two-photon imaging of mouse brain metastases originating from a melanoma cell line to investigate the growth kinetics of individual tumor cells in response to systemic delivery of two PI3K/mTOR inhibitors over time, and to study the impact of microregional vascular permeability. The two drugs are closely related but differ regarding a minor chemical modification that greatly increases brain penetration of one drug. Both inhibitors demonstrated a comparable inhibition of downstream targets and melanoma growth in vitro In vivo, increased BBB permeability to sodium fluorescein was associated with accelerated growth of individual brain metastases. Melanoma metastases with permeable microvessels responded similarly to equivalent doses of both inhibitors. In contrast, metastases with an intact BBB showed an exclusive response to the brain-penetrating inhibitor. The latter was true for macro- and micrometastases, and even single dormant melanoma cells. Nuclear morphology changes and single-cell regression patterns implied that both inhibitors, if extravasated, target not only perivascular melanoma cells but also those distant to blood vessels. Our study provides the first direct evidence that nonpermeable brain micro- and macrometastases can effectively be targeted by a drug designed to cross the BBB. Small-molecule inhibitors with these optimized properties are promising agents in preventing or treating brain metastases in patients. Clin Cancer Res; 22(24); 6078-87. ©2016 AACRSee related commentary by Steeg et al., p. 5953. ©2016 American Association for Cancer Research.
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
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
Theory and practice in sport psychology and motor behaviour needs to be constrained by integrative modelling of brain and behaviour.

PubMed

Keil, D; Holmes, P; Bennett, S; Davids, K; Smith, N

2000-06-01

Because of advances in technology, the non-invasive study of the human brain has enhanced the knowledge base within the neurosciences, resulting in an increased impact on the psychological study of human behaviour. We argue that application of this knowledge base should be considered in theoretical modelling within sport psychology and motor behaviour alongside existing ideas. We propose that interventions founded on current theoretical and empirical understanding in both psychology and the neurosciences may ultimately lead to greater benefits for athletes during practice and performance. As vehicles for exploring the arguments of a greater integration of psychology and neurosciences research, imagery and perception-action within the sport psychology and motor behaviour domains will serve as exemplars. Current neuroscience evidence will be discussed in relation to theoretical developments; the implications for sport scientists will be considered.
A model for brain life history evolution.

PubMed

González-Forero, Mauricio; Faulwasser, Timm; Lehmann, Laurent

2017-03-01

Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brain's energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting ("me vs nature"), namely when energy-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate model's parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages; (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory; and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills.
The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

PubMed

Melozzi, Francesca; Woodman, Marmaduke M; Jirsa, Viktor K; Bernard, Christophe

2017-01-01

Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease. TVMB enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.
Developing Enhanced Blood–Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling

PubMed Central

Wang, Wenyi; Kim, Marlene T.; Sedykh, Alexander

2015-01-01

Purpose Experimental Blood–Brain Barrier (BBB) permeability models for drug molecules are expensive and time-consuming. As alternative methods, several traditional Quantitative Structure-Activity Relationship (QSAR) models have been developed previously. In this study, we aimed to improve the predictivity of traditional QSAR BBB permeability models by employing relevant public bio-assay data in the modeling process. Methods We compiled a BBB permeability database consisting of 439 unique compounds from various resources. The database was split into a modeling set of 341 compounds and a validation set of 98 compounds. Consensus QSAR modeling workflow was employed on the modeling set to develop various QSAR models. A five-fold cross-validation approach was used to validate the developed models, and the resulting models were used to predict the external validation set compounds. Furthermore, we used previously published membrane transporter models to generate relevant transporter profiles for target compounds. The transporter profiles were used as additional biological descriptors to develop hybrid QSAR BBB models. Results The consensus QSAR models have R2=0.638 for fivefold cross-validation and R2=0.504 for external validation. The consensus model developed by pooling chemical and transporter descriptors showed better predictivity (R2=0.646 for five-fold cross-validation and R2=0.526 for external validation). Moreover, several external bio-assays that correlate with BBB permeability were identified using our automatic profiling tool. Conclusions The BBB permeability models developed in this study can be useful for early evaluation of new compounds (e.g., new drug candidates). The combination of chemical and biological descriptors shows a promising direction to improve the current traditional QSAR models. PMID:25862462

Integrating language models into classifiers for BCI communication: a review.

PubMed

Speier, W; Arnold, C; Pouratian, N

2016-06-01

The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication systems. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.
ADRB2, brain white matter integrity and cognitive ageing in the Lothian Birth Cohort 1936.

PubMed

Lyall, Donald M; Lopez, Lorna M; Bastin, Mark E; Maniega, Susana Muñoz; Penke, Lars; Valdés Hernández, Maria del C; Royle, Natalie A; Starr, John M; Porteous, David J; Wardlaw, Joanna M; Deary, Ian J

2013-01-01

The non-synonymous mutations arg16gly (rs1042713) and gln27glu (rs1042714) in the adrenergic β-2 receptor gene (ADRB2) have been associated with cognitive function and brain white matter integrity. The current study aimed to replicate these findings and expand them to a broader range of cognitive and brain phenotypes. The sample used is a community-dwelling group of older people, the Lothian Birth Cohort 1936. They had been assessed cognitively at age 11 years, and undertook further cognitive assessments and brain diffusion MRI tractography in older age. The sample size range for cognitive function variables was N = 686-765, and for neuroimaging variables was N = 488-587. Previously-reported findings with these genetic variants did not replicate in this cohort. Novel, nominally significant associations were observed; notably, the integrity of the left arcuate fasciculus mediated the association between rs1042714 and the Digit Symbol Coding test of information processing speed. No significant associations of cognitive and brain phenotypes with ADRB2 variants survived correction for false discovery rate. Previous findings may therefore have been subject to type 1 error. Further study into links between ADRB2, cognitive function and brain white matter integrity is required.
Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.
Integrated and Contextual Basic Science Instruction in Preclinical Education: Problem-Based Learning Experience Enriched with Brain/Mind Learning Principles

ERIC Educational Resources Information Center

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

Kabbara, A.; Eid, H.; El Falou, W.; Khalil, M.; Wendling, F.; Hassan, M.

2018-04-01

Objective. Emerging evidence shows that cognitive deficits in Alzheimer’s disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. Approach. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Main results. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients’ functional brain networks and their cognitive scores. Significance. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.
Potentiated antibodies to mu-opiate receptors: effect on integrative activity of the brain.

PubMed

Geiko, V V; Vorob'eva, T M; Berchenko, O G; Epstein, O I

2003-01-01

The effect of homeopathically potentiated antibodies to mu-receptors (10(-100) wt %) on integrative activity of rat brain was studied using the models of self-stimulation of the lateral hypothalamus and convulsions produced by electric current. Electric current was delivered through electrodes implanted into the ventromedial hypothalamus. Single treatment with potentiated antibodies to mu-receptors increased the rate of self-stimulation and decreased the threshold of convulsive seizures. Administration of these antibodies for 7 days led to further activation of the positive reinforcement system and decrease in seizure thresholds. Distilled water did not change the rate of self-stimulation and seizure threshold.
Integration of miRNA and Protein Profiling Reveals Coordinated Neuroadaptations in the Alcohol-Dependent Mouse Brain

PubMed Central

Gorini, Giorgio; Nunez, Yury O.; Mayfield, R. Dayne

2013-01-01

The molecular mechanisms underlying alcohol dependence involve different neurochemical systems and are brain region-dependent. Chronic Intermittent Ethanol (CIE) procedure, combined with a Two-Bottle Choice voluntary drinking paradigm, represents one of the best available animal models for alcohol dependence and relapse drinking. MicroRNAs, master regulators of the cellular transcriptome and proteome, can regulate their targets in a cooperative, combinatorial fashion, ensuring fine tuning and control over a large number of cellular functions. We analyzed cortex and midbrain microRNA expression levels using an integrative approach to combine and relate data to previous protein profiling from the same CIE-subjected samples, and examined the significance of the data in terms of relative contribution to alcohol consumption and dependence. MicroRNA levels were significantly altered in CIE-exposed dependent mice compared with their non-dependent controls. More importantly, our integrative analysis identified modules of coexpressed microRNAs that were highly correlated with CIE effects and predicted target genes encoding differentially expressed proteins. Coexpressed CIE-relevant proteins, in turn, were often negatively correlated with specific microRNA modules. Our results provide evidence that microRNA-orchestrated translational imbalances are driving the behavioral transition from alcohol consumption to dependence. This study represents the first attempt to combine ex vivo microRNA and protein expression on a global scale from the same mammalian brain samples. The integrative systems approach used here will improve our understanding of brain adaptive changes in response to drug abuse and suggests the potential therapeutic use of microRNAs as tools to prevent or compensate multiple neuroadaptations underlying addictive behavior. PMID:24358208
Host matrix metalloproteinases in cerebral malaria: new kids on the block against blood–brain barrier integrity?

PubMed Central

2014-01-01

Cerebral malaria (CM) is a life-threatening complication of falciparum malaria, associated with high mortality rates, as well as neurological impairment in surviving patients. Despite disease severity, the etiology of CM remains elusive. Interestingly, although the Plasmodium parasite is sequestered in cerebral microvessels, it does not enter the brain parenchyma: so how does Plasmodium induce neuronal dysfunction? Several independent research groups have suggested a mechanism in which increased blood–brain barrier (BBB) permeability might allow toxic molecules from the parasite or the host to enter the brain. However, the reported severity of BBB damage in CM is variable depending on the model system, ranging from mild impairment to full BBB breakdown. Moreover, the factors responsible for increased BBB permeability are still unknown. Here we review the prevailing theories on CM pathophysiology and discuss new evidence from animal and human CM models implicating BBB damage. Finally, we will review the newly-described role of matrix metalloproteinases (MMPs) and BBB integrity. MMPs comprise a family of proteolytic enzymes involved in modulating inflammatory response, disrupting tight junctions, and degrading sub-endothelial basal lamina. As such, MMPs represent potential innovative drug targets for CM. PMID:24467887
Central Artery Stiffness, Baroreflex Sensitivity, and Brain White Matter Neuronal Fiber Integrity in Older Adults

PubMed Central

Tarumi, Takashi; de Jong, Daan L.K.; Zhu, David C.; Tseng, Benjamin Y.; Liu, Jie; Hill, Candace; Riley, Jonathan; Womack, Kyle B.; Kerwin, Diana R.; Lu, Hanzhang; Cullum, C. Munro; Zhang, Rong

2015-01-01

Cerebral hypoperfusion elevates the risk of brain white matter (WM) lesions and cognitive impairment. Central artery stiffness impairs baroreflex, which controls systemic arterial perfusion, and may deteriorate neuronal fiber integrity of brain WM. The purpose of this study was to examine the associations among brain WM neuronal fiber integrity, baroreflex sensitivity (BRS), and central artery stiffness in older adults. Fifty-four adults (65±6 years) with normal cognitive function or mild cognitive impairment (MCI) were tested. The neuronal fiber integrity of brain WM was assessed from diffusion metrics acquired by diffusion tensor imaging. BRS was measured in response to acute changes in blood pressure induced by bolus injections of vasoactive drugs. Central artery stiffness was measured by carotid-femoral pulse wave velocity (cfPWV). The WM diffusion metrics including fractional anisotropy (FA) and radial (RD) and axial (AD) diffusivities, BRS, and cfPWV were not different between the control and MCI groups. Thus, the data from both groups were combined for subsequent analyses. Across WM, fiber tracts with decreased FA and increased RD were associated with lower BRS and higher cfPWV, with many of the areas presenting spatial overlap. In particular, the BRS assessed during hypotension was strongly correlated with FA and RD when compared with hypertension. Executive function performance was associated with FA and RD in the areas that correlated with cfPWV and BRS. These findings suggest that baroreflex-mediated control of systemic arterial perfusion, especially during hypotension, may play a crucial role in maintaining neuronal fiber integrity of brain WM in older adults. PMID:25623500
Dynamical Signatures of Structural Connectivity Damage to a Model of the Brain Posed at Criticality.

PubMed

Haimovici, Ariel; Balenzuela, Pablo; Tagliazucchi, Enzo

2016-12-01

Synchronization of brain activity fluctuations is believed to represent communication between spatially distant neural processes. These interareal functional interactions develop in the background of a complex network of axonal connections linking cortical and subcortical neurons, termed the human "structural connectome." Theoretical considerations and experimental evidence support the view that the human brain can be modeled as a system operating at a critical point between ordered (subcritical) and disordered (supercritical) phases. Here, we explore the hypothesis that pathologies resulting from brain injury of different etiologies are related to this model of a critical brain. For this purpose, we investigate how damage to the integrity of the structural connectome impacts on the signatures of critical dynamics. Adopting a hybrid modeling approach combining an empirical weighted network of human structural connections with a conceptual model of critical dynamics, we show that lesions located at highly transited connections progressively displace the model toward the subcritical regime. The topological properties of the nodes and links are of less importance when considered independently of their weight in the network. We observe that damage to midline hubs such as the middle and posterior cingulate cortex is most crucial for the disruption of criticality in the model. However, a similar effect can be achieved by targeting less transited nodes and links whose connection weights add up to an equivalent amount. This implies that brain pathology does not necessarily arise due to insult targeted at well-connected areas and that intersubject variability could obscure lesions located at nonhub regions. Finally, we discuss the predictions of our model in the context of clinical studies of traumatic brain injury and neurodegenerative disorders.
Integrative Review: Post-Craniotomy Pain in the Brain Tumor Patient

PubMed Central

Guilkey, Rebecca Elizabeth; Von Ah, Diane; Carpenter, Janet S.; Stone, Cynthia; Draucker, Claire B.

2015-01-01

Aim To conduct an integrative review to examine evidence of pain and associated symptoms in adult (≥ 21 years of age), post-craniotomy, brain tumor patients hospitalized on intensive care units. Background Healthcare providers believe craniotomies are less painful than other surgical procedures. Understanding how post-craniotomy pain unfolds over time will help inform patient care and aid in future research and policy development. Design Systematic literature search to identify relevant literature. Information abstracted using the Theory of Unpleasant Symptoms’ concepts of influencing factors, symptom clusters and patient performance. Inclusion criteria were indexed, peer-reviewed, full-length, English-language articles. Keywords were ‘traumatic brain injury,’ ‘pain, post-operative,’ ‘brain injuries,’ ‘postoperative pain,’ ‘craniotomy,’ ‘decompressive craniectomy,’ and ‘trephining.’ Data sources Medline, OVID, PubMed and CINAHL databases from 2000 – 2014. Review Method Cooper’s five-stage integrative review method was used to assess and synthesize literature. Results The search yielded 115 manuscripts, with 26 meeting inclusion criteria. Most studies were randomized, controlled trials conducted outside of the United States. All tested pharmacological pain interventions. Post-craniotomy brain tumor pain was well-documented and associated with nausea, vomiting and changes in blood pressure and impacted patient length of hospital stay, but there was no consensus for how best to treat such pain. Conclusion The Theory of Unpleasant Symptoms provided structure to the search. Post-craniotomy pain is experienced by patients, but associated symptoms and impact on patient performance remain poorly understood. Further research is needed to improve understanding and management of post-craniotomy pain in this population. PMID:26734710
Breaking symmetry: the zebrafish as a model for understanding left-right asymmetry in the developing brain.

PubMed

Roussigne, Myriam; Blader, Patrick; Wilson, Stephen W

2012-03-01

How does left-right asymmetry develop in the brain and how does the resultant asymmetric circuitry impact on brain function and lateralized behaviors? By enabling scientists to address these questions at the levels of genes, neurons, circuitry and behavior,the zebrafish model system provides a route to resolve the complexity of brain lateralization. In this review, we present the progress made towards characterizing the nature of the gene networks and the sequence of morphogenetic events involved in the asymmetric development of zebrafish epithalamus. In an attempt to integrate the recent extensive knowledge into a working model and to identify the future challenges,we discuss how insights gained at a cellular/developmental level can be linked to the data obtained at a molecular/genetic level. Finally, we present some evolutionary thoughts and discuss how significant discoveries made in zebrafish should provide entry points to better understand the evolutionary origins of brain lateralization.
Multivariate Heteroscedasticity Models for Functional Brain Connectivity.

PubMed

Seiler, Christof; Holmes, Susan

2017-01-01

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.
Utility of the Croatian translation of the community integration questionnaire-revised in a sample of adults with moderate to severe traumatic brain injury.

PubMed

Tršinski, Dubravko; Tadinac, Meri; Bakran, Žarko; Klepo, Ivana

2018-02-23

To examine the utility of the Community Integration Questionnaire-Revised, translated into Croatian, in a sample of adults with moderate to severe traumatic brain injury. The Community Integration Questionnaire-Revised was administered to a sample of 88 adults with traumatic brain injury and to a control sample matched by gender, age and education. Participants with traumatic brain injury were divided into four subgroups according to injury severity. The internal consistency of the Community Integration Questionnaire-Revised was satisfactory. The differences between the group with traumatic brain injury and the control group were statistically significant for the overall Community Integration Questionnaire-Revised score, as well as for all the subscales apart from the Home Integration subscale. The community Integration Questionnaire-Revised score varied significantly for subgroups with different severity of traumatic brain injury. The results show that the Croatian translation of the Community Integration Questionnaire-Revised is useful in assessing participation in adults with traumatic brain injury and confirm previous findings that severity of injury predicts community integration. Results of the new Electronic Social Networking scale indicate that persons who are more active on electronic social networks report better results for other domains of community integration, especially social activities. Implications for rehabilitation The Croatian translation of the Community Integration Questionnaire-Revised is a valid tool for long-term assessment of participation in various domains in persons with moderate to severe traumatic brain injury Persons with traumatic brain injury who are more active in the use of electronic social networking are also more integrated into social and productivity domains. Targeted training in the use of new technologies could enhance participation after traumatic brain injury.
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
The Human Thalamus Is an Integrative Hub for Functional Brain Networks

PubMed Central

Bertolero, Maxwell A.

2017-01-01

The thalamus is globally connected with distributed cortical regions, yet the functional significance of this extensive thalamocortical connectivity remains largely unknown. By performing graph-theoretic analyses on thalamocortical functional connectivity data collected from human participants, we found that most thalamic subdivisions display network properties that are capable of integrating multimodal information across diverse cortical functional networks. From a meta-analysis of a large dataset of functional brain-imaging experiments, we further found that the thalamus is involved in multiple cognitive functions. Finally, we found that focal thalamic lesions in humans have widespread distal effects, disrupting the modular organization of cortical functional networks. This converging evidence suggests that the human thalamus is a critical hub region that could integrate diverse information being processed throughout the cerebral cortex as well as maintain the modular structure of cortical functional networks. SIGNIFICANCE STATEMENT The thalamus is traditionally viewed as a passive relay station of information from sensory organs or subcortical structures to the cortex. However, the thalamus has extensive connections with the entire cerebral cortex, which can also serve to integrate information processing between cortical regions. In this study, we demonstrate that multiple thalamic subdivisions display network properties that are capable of integrating information across multiple functional brain networks. Moreover, the thalamus is engaged by tasks requiring multiple cognitive functions. These findings support the idea that the thalamus is involved in integrating information across cortical networks. PMID:28450543
TU-G-210-01: Modeling for Breast and Brain HIFU Treatment Planning

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

Christensen, D.

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

PubMed

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

2015-01-01

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

PubMed

Kivunja, Stephen; River, Jo; Gullick, Janice

2018-04-01

To synthesise the literature on the experiences of giving or receiving care for traumatic brain injury for people with traumatic brain injury, their family members and nurses in hospital and rehabilitation settings. Traumatic brain injury represents a major source of physical, social and economic burden. In the hospital setting, people with traumatic brain injury feel excluded from decision-making processes and perceive impatient care. Families describe inadequate information and support for psychological distress. Nurses find the care of people with traumatic brain injury challenging particularly when experiencing heavy workloads. To date, a contemporary synthesis of the literature on people with traumatic brain injury, family and nurse experiences of traumatic brain injury care has not been conducted. Integrative literature review. A systematic search strategy guided by the PRISMA statement was conducted in CINAHL, PubMed, Proquest, EMBASE and Google Scholar. Whittemore and Knafl's (Journal of Advanced Nursing, 52, 2005, 546) integrative review framework guided data reduction, data display, data comparison and conclusion verification. Across the three participant categories (people with traumatic brain injury/family members/nurses) and sixteen subcategories, six cross-cutting themes emerged: seeking personhood, navigating challenging behaviour, valuing skills and competence, struggling with changed family responsibilities, maintaining productive partnerships and reflecting on workplace culture. Traumatic brain injury creates changes in physical, cognitive and emotional function that challenge known ways of being in the world for people. This alters relationship dynamics within families and requires a specific skill set among nurses. Recommendations include the following: (i) formal inclusion of people with traumatic brain injury and families in care planning, (ii) routine risk screening for falls and challenging behaviour to ensure that controls are based on
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.

From Hippocampus to Whole-Brain: The Role of Integrative Processing in Episodic Memory Retrieval

PubMed Central

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

2017-01-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. PMID:28112460
Development of an experimental model of brain tissue heterotopia in the lung

PubMed Central

Quemelo, Paulo Roberto Veiga; Sbragia, Lourenço; Peres, Luiz Cesar

2007-01-01

Summary The presence of heterotopic brain tissue in the lung is a rare abnormality. The cases reported thus far are usually associated with neural tube defects (NTD). As there are no reports of experimental models of NTD that present this abnormality, the objective of the present study was to develop a surgical method of brain tissue heterotopia in the lung. We used 24 pregnant Swiss mice divided into two groups of 12 animals each, denoted 17GD and 18GD according to the gestational day (GD) when caesarean section was performed to collect the fetuses. Surgery was performed on the 15th GD, one fetus was removed by hysterectomy and its brain tissue was cut into small fragments and implanted in the lung of its litter mates. Thirty-four live fetuses were obtained from the 17GD group. Of these, eight (23.5%) were used as control (C), eight (23.5%) were sham operated (S) and 18 (52.9%) were used for pulmonary brain tissue implantation (PBI). Thirty live fetuses were obtained from the females of the 18GD group. Of these, eight (26.6%) were C, eight (26.6%) S and 14 (46.6%) were used for PBI. Histological examination of the fetal trunks showed implantation of GFAP-positive brain tissue in 85% of the fetuses of the 17GD group and in 100% of those of the 18GD group, with no significant difference between groups for any of the parameters analysed. The experimental model proved to be efficient and of relatively simple execution, showing complete integration of the brain tissue with pulmonary and pleural tissue and thus representing a model that will permit the study of different aspects of cell implantation and interaction. PMID:17877535
From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval.

PubMed

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

2017-04-01

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

NASA Astrophysics Data System (ADS)

Speier, W.; Arnold, C.; Pouratian, N.

2016-06-01

Objective. The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication systems. Approach. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Main results. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Significance. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.
Mixed oligomers and monomeric amyloid-β disrupts endothelial cells integrity and reduces monomeric amyloid-β transport across hCMEC/D3 cell line as an in vitro blood-brain barrier model.

PubMed

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

2014-09-01

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

PubMed Central

Lehmann, Laurent

2017-01-01

Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brain’s energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting (“me vs nature”), namely when energy-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate model’s parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages; (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory; and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills. PMID:28278153
In vitro models of the blood–brain barrier: An overview of commonly used brain endothelial cell culture models and guidelines for their use

PubMed Central

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

2016-01-01

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

PubMed

Wittek, Adam; Kikinis, Ron; Warfield, Simon K; Miller, Karol

2005-01-01

In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict deformation field within the brain during the craniotomy-induced brain shift. Deformation of brain surface was used as displacement boundary conditions. Application of the computed deformation field to align (i.e. register) the preoperative images with the intraoperative ones indicated that the model very accurately predicts the displacements of gravity centers of the lateral ventricles and tumor even for very limited information about the brain surface deformation. These results are sufficient to suggest that nonlinear biomechanical models can be regarded as one possible way of complementing medical image processing techniques when conducting nonrigid registration. Important advantage of such models over the linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain tissue stress-strain relationship is linear.
Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model.

PubMed

Wang, Fang; Han, Yong; Wang, Bingyu; Peng, Qian; Huang, Xiaoqun; Miller, Karol; Wittek, Adam

2018-05-12

In this study, we investigate the effects of modelling choices for the brain-skull interface (layers of tissues between the brain and skull that determine boundary conditions for the brain) and the constitutive model of brain parenchyma on the brain responses under violent impact as predicted using computational biomechanics model. We used the head/brain model from Total HUman Model for Safety (THUMS)-extensively validated finite element model of the human body that has been applied in numerous injury biomechanics studies. The computations were conducted using a well-established nonlinear explicit dynamics finite element code LS-DYNA. We employed four approaches for modelling the brain-skull interface and four constitutive models for the brain tissue in the numerical simulations of the experiments on post-mortem human subjects exposed to violent impacts reported in the literature. The brain-skull interface models included direct representation of the brain meninges and cerebrospinal fluid, outer brain surface rigidly attached to the skull, frictionless sliding contact between the brain and skull, and a layer of spring-type cohesive elements between the brain and skull. We considered Ogden hyperviscoelastic, Mooney-Rivlin hyperviscoelastic, neo-Hookean hyperviscoelastic and linear viscoelastic constitutive models of the brain tissue. Our study indicates that the predicted deformations within the brain and related brain injury criteria are strongly affected by both the approach of modelling the brain-skull interface and the constitutive model of the brain parenchyma tissues. The results suggest that accurate prediction of deformations within the brain and risk of brain injury due to violent impact using computational biomechanics models may require representation of the meninges and subarachnoidal space with cerebrospinal fluid in the model and application of hyperviscoelastic (preferably Ogden-type) constitutive model for the brain tissue.
Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than
Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data

PubMed Central

Detwiler, Landon T.; Suciu, Dan; Franklin, Joshua D.; Moore, Eider B.; Poliakov, Andrew V.; Lee, Eunjung S.; Corina, David P.; Ojemann, George A.; Brinkley, James F.

2008-01-01

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts. PMID:19198662
Integrative Etiopathogenetic Models of Psychotic Disorders: Methods, Evidence and Concepts

PubMed Central

Gaebel, Wolfgang; Zielasek, Jürgen

2011-01-01

Integrative models of the etiopathogesnesis of psychotic disorders are needed since a wealth of information from such diverse fields as neurobiology, psychology, and the social sciences is currently changing the concepts of mental disorders. Several approaches to integrate these streams of information into coherent concepts of psychosis are feasible and will need to be assessed in future experimental studies. Common to these concepts are the notion of psychotic disorders as brain disorders and a polythetic approach in that it is increasingly realized that a multitude of interindividually partially different pathogenetic factors interact in individual persons in a complex fashion resulting in the clinical symptoms of psychosis. PMID:21860047
Genetically increased cell-intrinsic excitability enhances neuronal integration into adult brain circuits

PubMed Central

Lin, Chia-Wei; Sim, Shuyin; Ainsworth, Alice; Okada, Masayoshi; Kelsch, Wolfgang; Lois, Carlos

2009-01-01

New neurons are added to the adult brain throughout life, but only half ultimately integrate into existing circuits. Sensory experience is an important regulator of the selection of new neurons but it remains unknown whether experience provides specific patterns of synaptic input, or simply a minimum level of overall membrane depolarization critical for integration. To investigate this issue, we genetically modified intrinsic electrical properties of adult-generated neurons in the mammalian olfactory bulb. First, we observed that suppressing levels of cell-intrinsic neuronal activity via expression of ESKir2.1 potassium channels decreases, whereas enhancing activity via expression of NaChBac sodium channels increases survival of new neurons. Neither of these modulations affects synaptic formation. Furthermore, even when neurons are induced to fire dramatically altered patterns of action potentials, increased levels of cell-intrinsic activity completely blocks cell death triggered by NMDA receptor deletion. These findings demonstrate that overall levels of cell-intrinsic activity govern survival of new neurons and precise firing patterns are not essential for neuronal integration into existing brain circuits. PMID:20152111
Representational geometry: integrating cognition, computation, and the brain

PubMed Central

Kriegeskorte, Nikolaus; Kievit, Rogier A.

2013-01-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. PMID:23876494
Social Competence in Pediatric Brain Tumor Survivors: Application of a Model from Social Neuroscience and Developmental Psychology

PubMed Central

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

2014-01-01

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

NASA Astrophysics Data System (ADS)

Zhang, Aiying; Jia, Bochao; Wang, Yu-Ping

2018-03-01

Adolescence is a transitional period between childhood and adulthood with physical changes, as well as increasing emotional activity. Studies have shown that the emotional sensitivity is related to a second dramatical brain growth. However, there is little focus on the trend of brain development during this period. In this paper, we aim to track the functional brain connectivity development in adolescence using resting state fMRI (rs-fMRI), which amounts to a time-series analysis problem. Most existing methods either require the time point to be fairly long or are only applicable to small graphs. To this end, we adapted a fast Bayesian integrative analysis (FBIA) to address the short time-series difficulty, and combined with adaptive sum of powered score (aSPU) test for group difference. The data we used are the resting state fMRI (rs-fMRI) obtained from the publicly available Philadelphia Neurodevelopmental Cohort (PNC). They include 861 individuals aged 8-22 years who were divided into five different adolescent stages. We summarized the networks with global measurements: segregation and integration, and provided full brain functional connectivity pattern in various stages of adolescence. Moreover, our research revealed several brain functional modules development trends. Our results are shown to be both statistically and biologically significant.
Ethyl pyruvate protects against blood-brain barrier damage and improves long-term neurological outcomes in a rat model of traumatic brain injury.

PubMed

Shi, Hong; Wang, Hai-Lian; Pu, Hong-Jian; Shi, Ye-Jie; Zhang, Jia; Zhang, Wen-Ting; Wang, Guo-Hua; Hu, Xiao-Ming; Leak, Rehana K; Chen, Jun; Gao, Yan-Qin

2015-04-01

Many traumatic brain injury (TBI) survivors sustain neurological disability and cognitive impairments due to the lack of defined therapies to reduce TBI-induced long-term brain damage. Ethyl pyruvate (EP) has shown neuroprotection in several models of acute brain injury. The present study therefore investigated the potential beneficial effect of EP on long-term outcomes after TBI and the underlying mechanisms. Male adult rats were subjected to unilateral controlled cortical impact injury. EP was injected intraperitoneally 15 min after TBI and again at 12, 24, 36, 48, and 60 h after TBI. Neurological deficits, blood-brain barrier (BBB) integrity, and neuroinflammation were assessed. Ethyl pyruvate improved sensorimotor and cognitive functions and ameliorated brain tissue damage up to 28 day post-TBI. BBB breach and brain edema were attenuated by EP at 48 h after TBI. EP suppressed matrix metalloproteinase (MMP)-9 production from peripheral neutrophils and reduced the number of MMP-9-overproducing neutrophils in the spleen, and therefore mitigated MMP-9-mediated BBB breakdown. Moreover, EP exerted potent antiinflammatory effects in cultured microglia and inhibited the elevation of inflammatory mediators in the brain after TBI. Ethyl pyruvate confers long-term neuroprotection against TBI, possibly through breaking the vicious cycle among MMP-9-mediated BBB disruption, neuroinflammation, and long-lasting brain damage. © 2014 John Wiley & Sons Ltd.
Model of brain activation predicts the neural collective influence map of the brain

PubMed Central

Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Makse, Hernán A.

2017-01-01

Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory. PMID:28351973
Mannitol Improves Brain Tissue Oxygenation in a Model of Diffuse Traumatic Brain Injury.

PubMed

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

2015-10-01

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

PubMed

Thomsen, Maj Schneider; Birkelund, Svend; Burkhart, Annette; Stensballe, Allan; Moos, Torben

2017-03-01

The brain vascular basement membrane is important for both blood-brain barrier (BBB) development, stability, and barrier integrity and the contribution hereto from brain capillary endothelial cells (BCECs), pericytes, and astrocytes of the BBB is probably significant. The aim of this study was to analyse four different in vitro models of the murine BBB for expression and possible secretion of major basement membrane proteins from murine BCECs (mBCECs). mBCECs, pericytes and glial cells (mainly astrocytes and microglia) were prepared from brains of C57BL/6 mice. The mBCECs were grown as monoculture, in co-culture with pericytes or mixed glial cells, or as a triple-culture with both pericytes and mixed glial cells. The integrity of the BBB models was validated by measures of transendothelial electrical resistance (TEER) and passive permeability to mannitol. The expression of basement membrane proteins was analysed using RT-qPCR, mass spectrometry and immunocytochemistry. Co-culturing mBCECs with pericytes, mixed glial cells, or both significantly increased the TEER compared to the monoculture, and a low passive permeability was correlated with high TEER. The mBCECs expressed all major basement membrane proteins such as laminin-411, laminin-511, collagen [α1(IV)] 2 α2(IV), agrin, perlecan, and nidogen 1 and 2 in vitro. Increased expression of the laminin α5 subunit correlated with the addition of BBB-inducing factors (hydrocortisone, Ro 20-1724, and pCPT-cAMP), whereas increased expression of collagen IV α1 primarily correlated with increased levels of cAMP. In conclusion, BCECs cultured in vitro coherently form a BBB and express basement membrane proteins as a feature of maturation. Cover Image for this issue: doi: 10.1111/jnc.13789. © 2016 International Society for Neurochemistry.

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.
Your perspective and my benefit: multiple lesion models of self-other integration strategies during social bargaining.

PubMed

Melloni, Margherita; Billeke, Pablo; Baez, Sandra; Hesse, Eugenia; de la Fuente, Laura; Forno, Gonzalo; Birba, Agustina; García-Cordero, Indira; Serrano, Cecilia; Plastino, Angelo; Slachevsky, Andrea; Huepe, David; Sigman, Mariano; Manes, Facundo; García, Adolfo M; Sedeño, Lucas; Ibáñez, Agustín

2016-11-01

Recursive social decision-making requires the use of flexible, context-sensitive long-term strategies for negotiation. To succeed in social bargaining, participants' own perspectives must be dynamically integrated with those of interactors to maximize self-benefits and adapt to the other's preferences, respectively. This is a prerequisite to develop a successful long-term self-other integration strategy. While such form of strategic interaction is critical to social decision-making, little is known about its neurocognitive correlates. To bridge this gap, we analysed social bargaining behaviour in relation to its structural neural correlates, ongoing brain dynamics (oscillations and related source space), and functional connectivity signatures in healthy subjects and patients offering contrastive lesion models of neurodegeneration and focal stroke: behavioural variant frontotemporal dementia, Alzheimer's disease, and frontal lesions. All groups showed preserved basic bargaining indexes. However, impaired self-other integration strategy was found in patients with behavioural variant frontotemporal dementia and frontal lesions, suggesting that social bargaining critically depends on the integrity of prefrontal regions. Also, associations between behavioural performance and data from voxel-based morphometry and voxel-based lesion-symptom mapping revealed a critical role of prefrontal regions in value integration and strategic decisions for self-other integration strategy. Furthermore, as shown by measures of brain dynamics and related sources during the task, the self-other integration strategy was predicted by brain anticipatory activity (alpha/beta oscillations with sources in frontotemporal regions) associated with expectations about others' decisions. This pattern was reduced in all clinical groups, with greater impairments in behavioural variant frontotemporal dementia and frontal lesions than Alzheimer's disease. Finally, connectivity analysis from functional
Studying the Brain in a Dish: 3D Cell Culture Models of Human Brain Development and Disease.

PubMed

Brown, Juliana; Quadrato, Giorgia; Arlotta, Paola

2018-01-01

The study of the cellular and molecular processes of the developing human brain has been hindered by access to suitable models of living human brain tissue. Recently developed 3D cell culture models offer the promise of studying fundamental brain processes in the context of human genetic background and species-specific developmental mechanisms. Here, we review the current state of 3D human brain organoid models and consider their potential to enable investigation of complex aspects of human brain development and the underpinning of human neurological disease. © 2018 Elsevier Inc. All rights reserved.
Representational geometry: integrating cognition, computation, and the brain.

PubMed

Kriegeskorte, Nikolaus; Kievit, Rogier A

2013-08-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. Copyright © 2013 Elsevier Ltd. All rights reserved.
Silencing microRNA-143 protects the integrity of the blood-brain barrier: implications for methamphetamine abuse

PubMed Central

Bai, Ying; Zhang, Yuan; Hua, Jun; Yang, Xiangyu; Zhang, Xiaotian; Duan, Ming; Zhu, Xinjian; Huang, Wenhui; Chao, Jie; Zhou, Rongbin; Hu, Gang; Yao, Honghong

2016-01-01

MicroRNA-143 (miR-143) plays a critical role in various cellular processes; however, the role of miR-143 in the maintenance of blood-brain barrier (BBB) integrity remains poorly defined. Silencing miR-143 in a genetic animal model or via an anti-miR-143 lentivirus prevented the BBB damage induced by methamphetamine. miR-143, which targets p53 unregulated modulator of apoptosis (PUMA), increased the permeability of human brain endothelial cells and concomitantly decreased the expression of tight junction proteins (TJPs). Silencing miR-143 increased the expression of TJPs and protected the BBB integrity against the effects of methamphetamine treatment. PUMA overexpression increased the TJP expression through a mechanism that involved the NF-κB and p53 transcription factor pathways. Mechanistically, methamphetamine mediated up-regulation of miR-143 via sigma-1 receptor with sequential activation of the mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3′ kinase (PI3K)/Akt and STAT3 pathways. These results indicated that silencing miR-143 could provide a novel therapeutic strategy for BBB damage-related vascular dysfunction. PMID:27767041
Using Data-Driven Model-Brain Mappings to Constrain Formal Models of Cognition

PubMed Central

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

2015-01-01

In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases. In this paper we used model-based fMRI analysis to create a data-driven model-brain mapping for five modules of the ACT-R cognitive architecture. We then validated this mapping by applying it to two new datasets with associated models. The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved. We conclude that data-driven model-brain mappings can provide strong constraints on cognitive models, and that model-based fMRI is a suitable way to create such mappings. PMID:25747601
Music plus Music Integration: A Model for Music Education Policy Reform That Reflects the Evolution and Success of Arts Integration Practices in 21st Century American Public Schools

ERIC Educational Resources Information Center

Scripp, Lawrence; Gilbert, Josh

2016-01-01

This article explores the special case of integrative teaching and learning in music as a model for 21st century music education policy reform based on the principles that have evolved out of arts integration research and practices over the past century and informed by the recent rising tide of evidence of music's impact on brain capacity and…
Exposure to Lipopolysaccharide and/or Unconjugated Bilirubin Impair the Integrity and Function of Brain Microvascular Endothelial Cells

PubMed Central

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

2012-01-01

Background Sepsis and jaundice are common conditions in newborns that can lead to brain damage. Though lipopolysaccharide (LPS) is known to alter the integrity of the blood-brain barrier (BBB), little is known on the effects of unconjugated bilirubin (UCB) and even less on the joint effects of UCB and LPS on brain microvascular endothelial cells (BMEC). Methodology/Principal Findings Monolayers of primary rat BMEC were treated with 1 µg/ml LPS and/or 50 µM UCB, in the presence of 100 µM human serum albumin, for 4 or 24 h. Co-cultures of BMEC with astroglial cells, a more complex BBB model, were used in selected experiments. LPS led to apoptosis and UCB induced both apoptotic and necrotic-like cell death. LPS and UCB led to inhibition of P-glycoprotein and activation of matrix metalloproteinases-2 and -9 in mono-cultures. Transmission electron microscopy evidenced apoptotic bodies, as well as damaged mitochondria and rough endoplasmic reticulum in BMEC by either insult. Shorter cell contacts and increased caveolae-like invaginations were noticeable in LPS-treated cells and loss of intercellular junctions was observed upon treatment with UCB. Both compounds triggered impairment of endothelial permeability and transendothelial electrical resistance both in mono- and co-cultures. The functional changes were confirmed by alterations in immunostaining for junctional proteins β-catenin, ZO-1 and claudin-5. Enlargement of intercellular spaces, and redistribution of junctional proteins were found in BMEC after exposure to LPS and UCB. Conclusions LPS and/or UCB exert direct toxic effects on BMEC, with distinct temporal profiles and mechanisms of action. Therefore, the impairment of brain endothelial integrity upon exposure to these neurotoxins may favor their access to the brain, thus increasing the risk of injury and requiring adequate clinical management of sepsis and jaundice in the neonatal period. PMID:22586454
An integrated system for synchronous detection of neuron spikes and dopamine activities in the striatum of Parkinson monkey brain.

PubMed

Xu, Shengwei; Zhang, Yu; Zhang, Song; Xiao, Guihua; Wang, Mixia; Song, Yilin; Gao, Fei; Li, Ziyue; Zhuang, Ping; Chan, Piu; Tao, Guoxian; Yue, Feng; Cai, Xinxia

2018-07-01

Synchronous detecting neuron spikes and dopamine (DA) activities in the non-human primate brain play an important role in understanding of Parkinson's disease (PD). At present, most experiments are carried out by combing of electrodes and commercial instruments, which are inconvenient, time-consuming and inefficient. Herein, this study describes a novel integrated system for monitoring neuron spikes and DA activities in non-human primate brain synchronously. This system integrates an implantable sensor, a dual-function head-stage and a low noise detection instrument. The system was developed efficiently by using the key technologies of noise reduction, interference protection and differential amplification. To demonstrate the utility of this system, synchronous recordings of electrophysiological signals and DA were in vivo performed in a monkey before and after treated as a Parkinson model monkey. The system typically exhibited input-referred noise levels of only ∼ 3 μV RMS , input impedance levels of up to 5.1 GΩ, and a sensitivity of 14.075 pA/μM for DA and could detect electrophysiological signals and DA without mutual interference. In monkey experiments, lower DA concentrations in the striatum and more intensive spikes of the Parkinson model monkey than the normal one were synchronously recorded efficiently. This integrated system will not only significantly simplify the experimental operation and improve the experimental efficiency, but also improve the signal quality and synchronization performance. This integrated system, which is practical, efficient and convenient, can be widely used for the study of PD and other neurological disorders. Copyright © 2018 Elsevier B.V. All rights reserved.
Decentralized Multisensory Information Integration in Neural Systems.

PubMed

Zhang, Wen-Hao; Chen, Aihua; Rasch, Malte J; Wu, Si

2016-01-13

How multiple sensory cues are integrated in neural circuitry remains a challenge. The common hypothesis is that information integration might be accomplished in a dedicated multisensory integration area receiving feedforward inputs from the modalities. However, recent experimental evidence suggests that it is not a single multisensory brain area, but rather many multisensory brain areas that are simultaneously involved in the integration of information. Why many mutually connected areas should be needed for information integration is puzzling. Here, we investigated theoretically how information integration could be achieved in a distributed fashion within a network of interconnected multisensory areas. Using biologically realistic neural network models, we developed a decentralized information integration system that comprises multiple interconnected integration areas. Studying an example of combining visual and vestibular cues to infer heading direction, we show that such a decentralized system is in good agreement with anatomical evidence and experimental observations. In particular, we show that this decentralized system can integrate information optimally. The decentralized system predicts that optimally integrated information should emerge locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas. To extract information reliably from ambiguous environments, the brain integrates multiple sensory cues, which provide different aspects of information about the same entity of interest. Here, we propose a decentralized architecture for multisensory integration. In such a system, no processor is in the center of the network topology and information integration is achieved in a distributed manner through reciprocally connected local processors. Through studying the inference of heading direction with visual and vestibular cues, we show that the decentralized system
Decentralized Multisensory Information Integration in Neural Systems

PubMed Central

Zhang, Wen-hao; Chen, Aihua

2016-01-01

How multiple sensory cues are integrated in neural circuitry remains a challenge. The common hypothesis is that information integration might be accomplished in a dedicated multisensory integration area receiving feedforward inputs from the modalities. However, recent experimental evidence suggests that it is not a single multisensory brain area, but rather many multisensory brain areas that are simultaneously involved in the integration of information. Why many mutually connected areas should be needed for information integration is puzzling. Here, we investigated theoretically how information integration could be achieved in a distributed fashion within a network of interconnected multisensory areas. Using biologically realistic neural network models, we developed a decentralized information integration system that comprises multiple interconnected integration areas. Studying an example of combining visual and vestibular cues to infer heading direction, we show that such a decentralized system is in good agreement with anatomical evidence and experimental observations. In particular, we show that this decentralized system can integrate information optimally. The decentralized system predicts that optimally integrated information should emerge locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas. SIGNIFICANCE STATEMENT To extract information reliably from ambiguous environments, the brain integrates multiple sensory cues, which provide different aspects of information about the same entity of interest. Here, we propose a decentralized architecture for multisensory integration. In such a system, no processor is in the center of the network topology and information integration is achieved in a distributed manner through reciprocally connected local processors. Through studying the inference of heading direction with visual and vestibular cues, we show that
Brain microvascular endothelial-astrocyte cell responses following Japanese encephalitis virus infection in an in vitro human blood-brain barrier model.

PubMed

Patabendige, Adjanie; Michael, Benedict D; Craig, Alister G; Solomon, Tom

2018-06-01

Japanese encephalitis virus (JEV) remains a leading cause of encephalitis, globally, which continues to grow in importance despite the availability of vaccines. Viral entry into the brain can occur via the blood-brain barrier (BBB), and inflammation at the BBB is a common final pathway in many brain infections. However, the role of the BBB during JEV infection and the contribution of the endothelial and astrocytic cell inflammation in facilitating virus entry into the brain are incompletely understood. We established a BBB model using human brain endothelial cells (HBECs) and human astrocytes. HBECs are polarised, and therefore the model was inoculated by JEV from the apical side to simulate the in vivo situation. The effects of JEV on the BBB permeability and release of inflammatory mediators from both apical and basolateral sides, representing the blood and the brain side respectively were investigated. JEV infected HBECs with limited active virus production, before crossing the BBB and infecting astrocytes. Control of JEV production by HBECs was associated with a significant increase in permeability, and with elevation of many host mediators, including cytokines, chemokines, cellular adhesion molecules, and matrix metalloproteases. When compared to the controls, significantly higher amounts of mediators were released from the apical side as opposed to the basolateral side. The increased release of mediators over time also correlated with increased BBB permeability. Treatment with dexamethasone led to a significant reduction in the release of interleukin 6 (IL6), C-C motif chemokine ligand 5 (CCL5) and C-X-C motif chemokine ligand 10 (CXCL10) from the apical side with a reduction in BBB disruption and no change in JEV production. The results are consistent with the hypothesis that JEV infection of the BBB triggers the production of a range of host mediators from both endothelial cells and astrocytes, which control JEV production but disrupt BBB integrity thus
Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

PubMed Central

Sunkin, Susan M.; Ng, Lydia; Lau, Chris; Dolbeare, Tim; Gilbert, Terri L.; Thompson, Carol L.; Hawrylycz, Michael; Dang, Chinh

2013-01-01

The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal. PMID:23193282
Heterogeneous integration of adult-generated granule cells into the epileptic brain

PubMed Central

Murphy, Brian L.; Pun, Raymund Y.K.; Yin, Hulian; Faulkner, Christian R.; Loepke, Andreas W.; Danzer, Steve C.

2011-01-01

The functional impact of adult-generated granule cells in the epileptic brain is unclear, with data supporting both protective and maladaptive roles. These conflicting findings could be explained if new granule cells integrate heterogeneously, with some cells taking neutral or adaptive roles, while others contribute to recurrent circuitry supporting seizures. Here, we tested this hypothesis by completing detailed morphological characterizations of age- and experience-defined cohorts of adult-generated granule cells from transgenic mice. The majority of newborn cells exposed to an epileptogenic insult exhibited reductions in dendritic spine number, suggesting reduced excitatory input to these cells. A significant subset, however, exhibited higher spine numbers. These latter cells tended to have enlarged cell bodies, long basal dendrites or both. Moreover, cells with basal dendrites received significantly more recurrent mossy fiber input through their apical dendrites, indicating that these cells are robustly integrated into the pathological circuitry of the epileptic brain. These data imply that newborn cells play complex – and potentially conflicting – roles in epilepsy. PMID:21209195
Integrating sensorimotor systems in a robot model of cricket behavior

NASA Astrophysics Data System (ADS)

Webb, Barbara H.; Harrison, Reid R.

2000-10-01

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

PubMed

Morozova, Maria; Koschutnig, Karl; Klein, Elise; Wood, Guilherme

2016-01-15

Non-linear effects of age on white matter integrity are ubiquitous in the brain and indicate that these effects are more pronounced in certain brain regions at specific ages. Box-Cox analysis is a technique to increase the log-likelihood of linear relationships between variables by means of monotonic non-linear transformations. Here we employ Box-Cox transformations to flexibly and parsimoniously determine the degree of non-linearity of age-related effects on white matter integrity by means of model comparisons using a voxel-wise approach. Analysis of white matter integrity in a sample of adults between 20 and 89years of age (n=88) revealed that considerable portions of the white matter in the corpus callosum, cerebellum, pallidum, brainstem, superior occipito-frontal fascicle and optic radiation show non-linear effects of age. Global analyses revealed an increase in the average non-linearity from fractional anisotropy to radial diffusivity, axial diffusivity, and mean diffusivity. These results suggest that Box-Cox transformations are a useful and flexible tool to investigate more complex non-linear effects of age on white matter integrity and extend the functionality of the Box-Cox analysis in neuroimaging. Copyright © 2015 Elsevier Inc. All rights reserved.
Modeling brain circuitry over a wide range of scales.

PubMed

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.
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
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.

A High-Performance Application Specific Integrated Circuit for Electrical and Neurochemical Traumatic Brain Injury Monitoring.

PubMed

Pagkalos, Ilias; Rogers, Michelle L; Boutelle, Martyn G; Drakakis, Emmanuel M

2018-05-22

This paper presents the first application specific integrated chip (ASIC) for the monitoring of patients who have suffered a Traumatic Brain Injury (TBI). By monitoring the neurophysiological (ECoG) and neurochemical (glucose, lactate and potassium) signals of the injured human brain tissue, it is possible to detect spreading depolarisations, which have been shown to be associated with poor TBI patient outcome. This paper describes the testing of a new 7.5 mm 2 ASIC fabricated in the commercially available AMS 0.35 μm CMOS technology. The ASIC has been designed to meet the demands of processing the injured brain tissue's ECoG signals, recorded by means of depth or brain surface electrodes, and neurochemical signals, recorded using microdialysis coupled to microfluidics-based electrochemical biosensors. The potentiostats use switchedcapacitor charge integration to record currents with 100 fA resolution, and allow automatic gain changing to track the falling sensitivity of a biosensor. This work supports the idea of a "behind the ear" wireless microplatform modality, which could enable the monitoring of currently non-monitored mobile TBI patients for the onset of secondary brain injury. ©2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.
Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

PubMed

Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.
Salience network integrity predicts default mode network function after traumatic brain injury

PubMed Central

Bonnelle, Valerie; Ham, Timothy E.; Leech, Robert; Kinnunen, Kirsi M.; Mehta, Mitul A.; Greenwood, Richard J.; Sharp, David J.

2012-01-01

Efficient behavior involves the coordinated activity of large-scale brain networks, but the way in which these networks interact is uncertain. One theory is that the salience network (SN)—which includes the anterior cingulate cortex, presupplementary motor area, and anterior insulae—regulates dynamic changes in other networks. If this is the case, then damage to the structural connectivity of the SN should disrupt the regulation of associated networks. To investigate this hypothesis, we studied a group of 57 patients with cognitive impairments following traumatic brain injury (TBI) and 25 control subjects using the stop-signal task. The pattern of brain activity associated with stop-signal task performance was studied by using functional MRI, and the structural integrity of network connections was quantified by using diffusion tensor imaging. Efficient inhibitory control was associated with rapid deactivation within parts of the default mode network (DMN), including the precuneus and posterior cingulate cortex. TBI patients showed a failure of DMN deactivation, which was associated with an impairment of inhibitory control. TBI frequently results in traumatic axonal injury, which can disconnect brain networks by damaging white matter tracts. The abnormality of DMN function was specifically predicted by the amount of white matter damage in the SN tract connecting the right anterior insulae to the presupplementary motor area and dorsal anterior cingulate cortex. The results provide evidence that structural integrity of the SN is necessary for the efficient regulation of activity in the DMN, and that a failure of this regulation leads to inefficient cognitive control. PMID:22393019
Meditation is associated with increased brain network integration.

PubMed

van Lutterveld, Remko; van Dellen, Edwin; Pal, Prasanta; Yang, Hua; Stam, Cornelis Jan; Brewer, Judson

2017-09-01

This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration. Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4-8 Hz), alpha (8-13 Hz) and lower beta (13-20 Hz) frequency bands. Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0.012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0.056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0.016 and P = 0.028 respectively). No significant differences between groups were observed for the theta and beta frequency bands. These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using
Intraoperative virtual brain counseling

NASA Astrophysics Data System (ADS)

Jiang, Zhaowei; Grosky, William I.; Zamorano, Lucia J.; Muzik, Otto; Diaz, Fernando

1997-06-01

Our objective is to offer online real-tim e intelligent guidance to the neurosurgeon. Different from traditional image-guidance technologies that offer intra-operative visualization of medical images or atlas images, virtual brain counseling goes one step further. It can distinguish related brain structures and provide information about them intra-operatively. Virtual brain counseling is the foundation for surgical planing optimization and on-line surgical reference. It can provide a warning system that alerts the neurosurgeon if the chosen trajectory will pass through eloquent brain areas. In order to fulfill this objective, tracking techniques are involved for intra- operativity. Most importantly, a 3D virtual brian environment, different from traditional 3D digitized atlases, is an object-oriented model of the brain that stores information about different brain structures together with their elated information. An object-oriented hierarchical hyper-voxel space (HHVS) is introduced to integrate anatomical and functional structures. Spatial queries based on position of interest, line segment of interest, and volume of interest are introduced in this paper. The virtual brain environment is integrated with existing surgical pre-planning and intra-operative tracking systems to provide information for planning optimization and on-line surgical guidance. The neurosurgeon is alerted automatically if the planned treatment affects any critical structures. Architectures such as HHVS and algorithms, such as spatial querying, normalizing, and warping are presented in the paper. A prototype has shown that the virtual brain is intuitive in its hierarchical 3D appearance. It also showed that HHVS, as the key structure for virtual brain counseling, efficiently integrates multi-scale brain structures based on their spatial relationships.This is a promising development for optimization of treatment plans and online surgical intelligent guidance.
Diffusion tensor imaging reveals adolescent binge ethanol-induced brain structural integrity alterations in adult rats that correlate with behavioral dysfunction.

PubMed

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

2016-07-01

Adolescence is characterized by considerable brain maturation that coincides with the development of adult behavior. Binge drinking is common during adolescence and can have deleterious effects on brain maturation because of the heightened neuroplasticity of the adolescent brain. Using an animal model of adolescent intermittent ethanol [AIE; 5.0 g/kg, intragastric, 20 percent EtOH w/v; 2 days on/2 days off from postnatal day (P)25 to P55], we assessed the adult brain structural volumes and integrity on P80 and P220 using diffusion tensor imaging (DTI). While we did not observe a long-term effect of AIE on structural volumes, AIE did reduce axial diffusivity (AD) in the cerebellum, hippocampus and neocortex. Radial diffusivity (RD) was reduced in the hippocampus and neocortex of AIE-treated animals. Prior AIE treatment did not affect fractional anisotropy (FA), but did lead to long-term reductions of mean diffusivity (MD) in both the cerebellum and corpus callosum. AIE resulted in increased anxiety-like behavior and diminished object recognition memory, the latter of which was positively correlated with DTI measures. Across aging, whole brain volumes increased, as did volumes of the corpus callosum and neocortex. This was accompanied by age-associated AD reductions in the cerebellum and neocortex as well as RD and MD reductions in the cerebellum. Further, we found that FA increased in both the cerebellum and corpus callosum as rats aged from P80 to P220. Thus, both age and AIE treatment caused long-term changes to brain structural integrity that could contribute to cognitive dysfunction. © 2015 Society for the Study of Addiction.
Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability.

PubMed

Heye, Anna K; Thrippleton, Michael J; Armitage, Paul A; Valdés Hernández, Maria Del C; Makin, Stephen D; Glatz, Andreas; Sakka, Eleni; Wardlaw, Joanna M

2016-01-15

There is evidence that subtle breakdown of the blood-brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n=201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a "sham" DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and K(Trans) estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low
Tracer kinetic modelling for DCE-MRI quantification of subtle blood–brain barrier permeability

PubMed Central

Heye, Anna K.; Thrippleton, Michael J.; Armitage, Paul A.; Valdés Hernández, Maria del C.; Makin, Stephen D.; Glatz, Andreas; Sakka, Eleni; Wardlaw, Joanna M.

2016-01-01

There is evidence that subtle breakdown of the blood–brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n = 201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a “sham” DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and KTrans estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model
Brain network segregation and integration during an epoch-related working memory fMRI experiment.

PubMed

Fransson, Peter; Schiffler, Björn C; Thompson, William Hedley

2018-05-17

The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution. At a global level, the cognitively more taxing 2-back epochs elicited an overall stronger response of integration between subnetworks compared to the 0-back epochs. Moreover, the visual, sensorimotor and fronto-parietal subnetworks displayed characteristic and distinct temporal profiles of segregation and integration during the 0- and 2-back epochs. During the interspersed epochs of baseline, several subnetworks, including the visual, fronto-parietal, cingulo-opercular and dorsal attention subnetworks showed pronounced increases in segregation. Using a drift diffusion model we show that the response time for the 2-back trials are correlated with integration for the fronto-parietal subnetwork and correlated with segregation for the visual subnetwork. Our results elucidate the fast-evolving events with regard to subnetwork integration and segregation that occur in an epoch-related task fMRI experiment. Our findings suggest that minute changes in subnetwork integration are of importance for task performance. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
The Virtual Brain: a simulator of primate brain network dynamics

PubMed Central

Sanz Leon, Paula; Knock, Stuart A.; Woodman, M. Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. PMID:23781198
The Virtual Brain: a simulator of primate brain network dynamics.

PubMed

Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.
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.
Brain temperature changes during selective cooling with endovascular intracarotid cold saline infusion: simulation using human data fitted with an integrated mathematical model.

PubMed

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

2013-03-01

The feasibility of rapid cerebral hypothermia induction in humans with intracarotid cold saline infusion (ICSI) was investigated using a hybrid approach of jugular venous bulb temperature (JVBT) sampling and mathematical modeling of transient and steady state brain temperature distribution. This study utilized both forward mathematical modeling, in which brain temperatures were predicted based on input saline temperatures, and inverse modeling, where brain temperatures were inferred based on JVBT. Changes in ipsilateral anterior circulation territory temperature (IACT) were estimated in eight patients as a result of 10 min of a cold saline infusion of 33 ml/min. During ICSI, the measured JVBT dropped by 0.76±0.18°C while the modeled JVBT decreased by 0.86±0.18°C. The modeled IACT decreased by 2.1±0.23°C. In the inverse model, IACT decreased by 1.9±0.23°C. The results of this study suggest that mild cerebral hypothermia can be induced rapidly and safely with ICSI in the neuroangiographical setting. The JVBT corrected mathematical model can be used as a non-invasive estimate of transient and steady state cerebral temperature changes.
Dendritic integration: 60 years of progress.

PubMed

Stuart, Greg J; Spruston, Nelson

2015-12-01

Understanding how individual neurons integrate the thousands of synaptic inputs they receive is critical to understanding how the brain works. Modeling studies in silico and experimental work in vitro, dating back more than half a century, have revealed that neurons can perform a variety of different passive and active forms of synaptic integration on their inputs. But how are synaptic inputs integrated in the intact brain? With the development of new techniques, this question has recently received substantial attention, with new findings suggesting that many of the forms of synaptic integration observed in vitro also occur in vivo, including in awake animals. Here we review six decades of progress, which collectively highlights the complex ways that single neurons integrate their inputs, emphasizing the critical role of dendrites in information processing in the brain.
Biochemical Markers of Brain Injury: An Integrated Proteomics-Based Approach

DTIC Science & Technology

2005-02-01

Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author( s ) and should not be construed as an official...Brain Injury: An Integrated DAMD17-03-1-0066 Proteomics-Based Approach 6. AUTHOR( S ) Ronald L. Hayes, Ph.D. 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS...10. SPONSORING / MONITORING AGENCY NAME( S ) AND ADDRESS(ES) AGENCY REPORT NUMBER U.S. Army Medical Research and Materiel Command Fort Detrick
What is community integration anyway?: defining meaning following traumatic brain injury.

PubMed

Sander, Angelle M; Clark, Allison; Pappadis, Monique R

2010-01-01

Full community integration, or participation in society, is the ultimate goal of rehabilitation and of research conducted in the field of rehabilitation for persons with traumatic brain injury (TBI). Community integration has been traditionally defined by 3 main areas: employment or other productive activity, independent living, and social activity. However, these have not always received equal weighting and attention in clinical or research efforts. Significant gaps remain in our understanding of factors that impact community integration and in our ability to intervene to improve participation for persons with TBI. This article describes 3 main challenges for researchers and rehabilitation professionals. First, a comprehensive meaning of community integration is needed, which includes the viewpoints and preferences of persons with TBI. Second, cultural competence in measurement and intervention is needed. Third, a thorough assessment of environmental factors impacting participation is needed and should be incorporated into research and treatment planning.
Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459
Integrated But Not Whole? Applying an Ontological Account of Human Organismal Unity to the Brain Death Debate.

PubMed

Moschella, Melissa

2016-10-01

As is clear in the 2008 report of the President's Council on Bioethics, the brain death debate is plagued by ambiguity in the use of such key terms as 'integration' and 'wholeness'. Addressing this problem, I offer a plausible ontological account of organismal unity drawing on the work of Hoffman and Rosenkrantz, and then apply that account to the case of brain death, concluding that a brain dead body lacks the unity proper to a human organism, and has therefore undergone a substantial change. I also show how my view can explain hard cases better than one in which biological integration (as understood by Alan Shewmon and the President's Council) is taken to imply ontological wholeness or unity. © 2016 John Wiley & Sons Ltd.
Implications of the Vienna Integrated Model of Art Perception for art-based interventions in clinical populations: Comment on "Move me, astonish me... delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Taruffi, Liila; Koelsch, Stefan

2017-07-01

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

PubMed

Goranson, Tamara E; Graves, Roger E; Allison, Deborah; La Freniere, Ron

2003-09-01

To determine the extent to which participation in a multidisciplinary rehabilitation programme and patient characteristics predict improvement in community integration following mild-to-moderate traumatic brain injury (TBI). A non-randomized case-control study was conducted employing a pre-test-post-test multiple regression design. Archival data for 42 patients with mild-to-moderate TBI who completed the Community Integration Questionnaire (CIQ) at intake and again 6-18 months later were analysed. Half the sample participated in an intensive outpatient rehabilitation programme that provided multi-modal interventions, while the other half received no rehabilitation. The two groups were matched on age, education and time since injury. On the CIQ Home Integration scale, participation in rehabilitation and female gender predicted better outcome. On the Productivity scale, patients with a lower age at injury had better outcome. Outcome on both of these scales, as well as on the Social Integration scale, was predicted by the baseline pre-test score (initial severity). Overall, multidisciplinary rehabilitation appeared to increase personal independence. It is also concluded that: (1) multivariate analysis can reveal the relative importance of multiple predictors of outcome; (2) different predictors may predict different aspects of outcome; and (3) more sensitive and specific outcome measures are needed.

Integrating Whole Brain Teaching Strategies to Create a More Engaged Learning Environment

ERIC Educational Resources Information Center

Palasigue, Jesame Torres

2009-01-01

In today's postmodern society, it is getting harder and harder to get the students engaged in classroom instruction and learning. The purpose of this research project was to seek ways to create a more engaged learning environment for the students. The teacher-researcher integrated the most current educational reform "Whole Brain Teaching" method…
The integrate model of emotion, thinking and self regulation: an application to the "paradox of aging".

PubMed

Williams, Leanne M; Gatt, Justine M; Hatch, Ainslie; Palmer, Donna M; Nagy, Marie; Rennie, Christopher; Cooper, Nicholas J; Morris, Charlotte; Grieve, Stuart; Dobson-Stone, Carol; Schofield, Peter; Clark, C Richard; Gordon, Evian; Arns, Martijn; Paul, Robert H

2008-09-01

This study was undertaken using the INTEGRATE Model of brain organization, which is based on a temporal continuum of emotion, thinking and self regulation. In this model, the key organizing principle of self adaption is the motivation to minimize danger and maximize reward. This principle drives brain organization across a temporal continuum spanning milliseconds to seconds, minutes and hours. The INTEGRATE Model comprises three distinct processes across this continuum. Emotion is defined by automatic action tendencies triggered by signals that are significant due to their relevance to minimizing danger-maximizing reward (such as abrupt, high contrast stimuli). Thinking represents cognitive functions and feelings that rely on brain and body feedback emerging from around 200 ms post-stimulus onwards. Self regulation is the modulation of emotion, thinking and feeling over time, according to more abstract adaptions to minimize danger-maximize reward. Here, we examined the impact of dispositional factors, age and genetic variation, on this temporal continuum. Brain Resource methodology provided a standardized platform for acquiring genetic, brain and behavioral data in the same 1000 healthy subjects. Results showed a "paradox" of declining function in the "thinking" time scale over the lifespan (6 to 80+ years), but a corresponding preservation or even increase in automatic functions of "emotion" and "self regulation". This paradox was paralleled by a greater loss of grey matter in cortical association areas (assessed using MRI) over age, but a relative preservation of subcortical grey matter. Genetic polymorphisms associated with both healthy function and susceptibility to disorder (including the BDNFVal(66)Met, COMTVal(158/108)Met, MAOA and DRD4 tandem repeat and 5HTT-LPR polymorphisms) made specific contributions to emotion, thinking and self regulatory functions, which also varied according to age.
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.
Preservation of mitochondrial functional integrity in mitochondria isolated from small cryopreserved mouse brain areas.

PubMed

Valenti, Daniela; de Bari, Lidia; De Filippis, Bianca; Ricceri, Laura; Vacca, Rosa Anna

2014-01-01

Studies of mitochondrial bioenergetics in brain pathophysiology are often precluded by the need to isolate mitochondria immediately after tissue dissection from a large number of brain biopsies for comparative studies. Here we present a procedure of cryopreservation of small brain areas from which mitochondrial enriched fractions (crude mitochondria) with high oxidative phosphorylation efficiency can be isolated. Small mouse brain areas were frozen and stored in a solution containing glycerol as cryoprotectant. Crude mitochondria were isolated by differential centrifugation from both cryopreserved and freshly explanted brain samples and were compared with respect to their ability to generate membrane potential and produce ATP. Intactness of outer and inner mitochondrial membranes was verified by polarographic ascorbate and cytochrome c tests and spectrophotometric assay of citrate synthase activity. Preservation of structural integrity and oxidative phosphorylation efficiency was successfully obtained in crude mitochondria isolated from different areas of cryopreserved mouse brain samples. Long-term cryopreservation of small brain areas from which intact and phosphorylating mitochondria can be isolated for the study of mitochondrial bioenergetics will significantly expand the study of mitochondrial defects in neurological pathologies, allowing large comparative studies and favoring interlaboratory and interdisciplinary analyses. Copyright © 2013 Elsevier Inc. All rights reserved.
Relationships among measures of balance, gait, and community integration in people with brain injury.

PubMed

Perry, Susan B; Woollard, Jason; Little, Susan; Shroyer, Kathleen

2014-01-01

To examine the relationship among measures of gait, balance, and community integration in adults with brain injury. Two rehabilitation hospitals. Thirty-four community-dwelling individuals with brain injury, aged 18 to 61 years (mean = 32 years), who were able to walk at least 12 m independently or with supervision. Mean time post-brain injury was 52 ± 44 months. Cross-sectional study. Community Balance and Mobility Scale, Dynamic Gait Index, Ten-Meter Walk Test for gait speed, and the Community Integration Questionnaire (CIQ). Mean balance and gait scores were as follows: 54 ± 26 of 96 on the Community Balance and Mobility Scale; 19 ± 5 of 24 on the Dynamic Gait Index; and gait speed of 1.36 ± 0.88 m/s. Mean score on the CIQ was 16 ± 5 of 29. Correlations between the balance/gait measures and the total CIQ score ranged from 0.21 to 0.30 and were not significant. All 3 balance/gait measures correlated significantly with the CIQ Productivity subscale (range = 0.38-0.52). The ability of people with brain injury to engage in work/school/volunteer activity may be reduced by impairments in balance and mobility. Future research should explore this relationship and determine whether interventions that improve balance and mobility result in improved community productivity.
Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation.

PubMed

Bolton, Thomas A W; Jochaut, Delphine; Giraud, Anne-Lise; Van De Ville, Dimitri

2018-06-01

To refine our understanding of autism spectrum disorders (ASD), studies of the brain in dynamic, multimodal and ecological experimental settings are required. One way to achieve this is to compare the neural responses of ASD and typically developing (TD) individuals when viewing a naturalistic movie, but the temporal complexity of the stimulus hampers this task, and the presence of intrinsic functional connectivity (FC) may overshadow movie-driven fluctuations. Here, we detected inter-subject functional correlation (ISFC) transients to disentangle movie-induced functional changes from underlying resting-state activity while probing FC dynamically. When considering the number of significant ISFC excursions triggered by the movie across the brain, connections between remote functional modules were more heterogeneously engaged in the ASD population. Dynamically tracking the temporal profiles of those ISFC changes and tying them to specific movie subparts, this idiosyncrasy in ASD responses was then shown to involve functional integration and segregation mechanisms such as response inhibition, background suppression, or multisensory integration, while low-level visual processing was spared. Through the application of a new framework for the study of dynamic experimental paradigms, our results reveal a temporally localized idiosyncrasy in ASD responses, specific to short-lived episodes of long-range functional interplays. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Network integrity of the parental brain in infancy supports the development of children's social competencies.

PubMed

Abraham, Eyal; Hendler, Talma; Zagoory-Sharon, Orna; Feldman, Ruth

2016-11-01

The cross-generational transmission of mammalian sociality, initiated by the parent's postpartum brain plasticity and species-typical behavior that buttress offspring's socialization, has not been studied in humans. In this longitudinal study, we measured brain response of 45 primary-caregiving parents to their infant's stimuli, observed parent-infant interactions, and assayed parental oxytocin (OT). Intra- and inter-network connectivity were computed in three main networks of the human parental brain: core limbic, embodied simulation and mentalizing. During preschool, two key child social competencies were observed: emotion regulation and socialization. Parent's network integrity in infancy predicted preschoolers' social outcomes, with subcortical and cortical network integrity foreshadowing simple evolutionary-based regulatory tactics vs complex self-regulatory strategies and advanced socialization. Parent-infant synchrony mediated the links between connectivity of the parent's embodied simulation network and preschoolers' ability to use cognitive/executive emotion regulation strategies, highlighting the inherently dyadic nature of this network and its long-term effects on tuning young to social life. Parent's inter-network core limbic-embodied simulation connectivity predicted children's OT as moderated by parental OT. Findings challenge solipsistic neuroscience perspectives by demonstrating how the parent-offspring interface enables the brain of one human to profoundly impact long-term adaptation of another. © The Author (2016). Published by Oxford University Press.
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.
Finite difference time domain (FDTD) modeling of implanted deep brain stimulation electrodes and brain tissue.

PubMed

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

2009-01-01

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

NASA Astrophysics Data System (ADS)

Wakamatsu, Hidetoshi; Gaohua, Lu

Various surface-cooling apparatus such as the cooling cap, muffler and blankets have been commonly used for the cooling of the brain to provide hypothermic neuro-protection for patients of hypoxic-ischemic encephalopathy. The present paper is aimed at the brain temperature regulation from the viewpoint of automatic system control, in order to help clinicians decide an optimal temperature of the cooling fluid provided for these three types of apparatus. At first, a biothermal model characterized by dynamic ambient temperatures is constructed for adult patient, especially on account of the clinical practice of hypothermia and anesthesia in the brain hypothermia treatment. Secondly, the model is represented by the state equation as a lumped parameter linear dynamic system. The biothermal model is justified from their various responses corresponding to clinical phenomena and treatment. Finally, the optimal regulator is tentatively designed to give clinicians some suggestions on the optimal temperature regulation of the patient’s brain. It suggests the patient’s brain temperature could be optimally controlled to follow-up the temperature process prescribed by the clinicians. This study benefits us a great clinical possibility for the automatic hypothermia treatment.
A pilot study on the operationalization of the Model of Occupational Self Efficacy: A model for the reintegration of persons with brain injuries to their worker roles.

PubMed

Soeker, Shaheed

2015-01-01

Traumatic brain injury causes functional limitations that can cause people to struggle to reintegrate in the workplace despite participating in work rehabilitation programmes. The aim of the study was to explore, and describe the experiences of individuals with Traumatic Brain Injury regarding returning to work through the use of the model of occupational self-efficacy. In the study 10 individuals who were diagnosed with a mild to moderate brain injury participated in the study. The research study was positioned within the qualitative paradigm specifically utilizing case study methodology. In order to gather data from the participants, individual interviews and participant observation techniques were used. Two themes emerged from the findings of the study theme one reflected the barriers related to the use of the model (i.e. Theme one: Effective participation in the model is affected by financial assistance). The second theme related to the enabling factors related to the use of the model (i.e. Theme two: A sense of normality). The findings of this study indicated that the Model of Occupational Self Efficacy (MOS) is a useful model to use in retraining the work skills of individual's who sustained a traumatic brain injury. The participants in this study could maintain employment in the open labour market for a period of at least 12 months and it improved their ability to accept their brain injury as well as adapt to their worker roles. The MOS also provides a framework for facilitating community integration.
Melanoma Brain Metastasis: Mechanisms, Models, and Medicine

PubMed Central

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
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
Development of a model for whole brain learning of physiology.

PubMed

Eagleton, Saramarie; Muller, Anton

2011-12-01

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

PubMed

Puthiyedth, Nisha; Riveros, Carlos; Berretta, Regina; Moscato, Pablo

2016-01-01

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. 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. 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. In addition, we identified
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.
Further refinement of the Escherichia coli brain abscess model in rat.

PubMed

Nazzaro, J M; Pagel, M A; Neuwelt, E A

1992-09-01

The rat brain abscess model provides a substrate for the modeling of delivery of therapeutic agents to intracerebral mass lesions. We now report refinement of the Escherichia coli brain abscess model in rat. A K1 surface antigen-negative E. coli isolated from human blood culture was stereotaxically inoculated into deep brain sites. Histopathologic analyses and quantitative cultures demonstrated the consistent production of lesions. No animal in this consecutive series developed meningitis, ventriculitis or sepsis. By contrast, prior experience with E. coli abscess production resulted in 25% failure rate of abscess production or death from sepsis. This improvement in the model may be attributable to specific characteristics of the bacteria used, modification of the inoculation method or the intracerebral placement technique. The present work suggests a reliable and consistent brain abscess model, which may be further used to study brain suppuration.
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.
Modeling the impact of COPD on the brain.

PubMed

Borson, Soo; Scanlan, James; Friedman, Seth; Zuhr, Elizabeth; Fields, Julie; Aylward, Elizabeth; Mahurin, Rodney; Richards, Todd; Anzai, Yoshimi; Yukawa, Michi; Yeh, Shingshing

2008-01-01

Previous studies have shown that COPD adversely affects distant organs and body systems, including the brain. This pilot study aims to model the relationships between respiratory insufficiency and domains related to brain function, including low mood, subtly impaired cognition, systemic inflammation, and brain structural and neurochemical abnormalities. Nine healthy controls were compared with 18 age- and education-matched medically stable-COPD patients, half of whom were oxygen-dependent. Measures included depression, anxiety, cognition, health status, spirometry, oximetry at rest and during 6-minute walk, and resting plasma cytokines and soluble receptors, brain MRI, and MR spectroscopy in regions relevant to mood and cognition. ANOVA was used to compare controls with patients and with COPD subgroups (oxygen users [n = 9] and nonusers [n = 9]), and only variables showing group differences at p < or = 0.05 were included in multiple regressions controlling for age, gender, and education to develop the final model. Controls and COPD patients differed significantly in global cognition and memory, mood, and soluble TNFR1 levels but not brain structural or neurochemical measures. Multiple regressions identified pathways linking disease severity with impaired performance on sensitive cognitive processing measures, mediated through oxygen dependence, and with systemic inflammation (TNFR1), related through poor 6-minute walk performance. Oxygen desaturation with activity was related to indicators of brain tissue damage (increased frontal choline, which in turn was associated with subcortical white matter attenuation). This empirically derived model provides a conceptual framework for future studies of clinical interventions to protect the brain in patients with COPD, such as earlier oxygen supplementation for patients with desaturation during everyday activities.
Modeling the impact of COPD on the brain

PubMed Central

Borson, Soo; Scanlan, James; Friedman, Seth; Zuhr, Elizabeth; Fields, Julie; Aylward, Elizabeth; Mahurin, Rodney; Richards, Todd; Anzai, Yoshimi; Yukawa, Michi; Yeh, Shingshing

2008-01-01

Previous studies have shown that COPD adversely affects distant organs and body systems, including the brain. This pilot study aims to model the relationships between respiratory insufficiency and domains related to brain function, including low mood, subtly impaired cognition, systemic inflammation, and brain structural and neurochemical abnormalities. Nine healthy controls were compared with 18 age- and education-matched medically stable COPD patients, half of whom were oxygen-dependent. Measures included depression, anxiety, cognition, health status, spirometry, oximetry at rest and during 6-minute walk, and resting plasma cytokines and soluble receptors, brain MRI, and MR spectroscopy in regions relevant to mood and cognition. ANOVA was used to compare controls with patients and with COPD subgroups (oxygen users [n = 9] and nonusers [n = 9]), and only variables showing group differences at p ≤ 0.05 were included in multiple regressions controlling for age, gender, and education to develop the final model. Controls and COPD patients differed significantly in global cognition and memory, mood, and soluble TNFR1 levels but not brain structural or neurochemical measures. Multiple regressions identified pathways linking disease severity with impaired performance on sensitive cognitive processing measures, mediated through oxygen dependence, and with systemic inflammation (TNFR1), related through poor 6-minute walk performance. Oxygen desaturation with activity was related to indicators of brain tissue damage (increased frontal choline, which in turn was associated with subcortical white matter attenuation). This empirically derived model provides a conceptual framework for future studies of clinical interventions to protect the brain in patients with COPD, such as earlier oxygen supplementation for patients with desaturation during everyday activities. PMID:18990971

Distributed multisensory integration in a recurrent network model through supervised learning

NASA Astrophysics Data System (ADS)

Wang, He; Wong, K. Y. Michael

Sensory integration between different modalities has been extensively studied. It is suggested that the brain integrates signals from different modalities in a Bayesian optimal way. However, how the Bayesian rule is implemented in a neural network remains under debate. In this work we propose a biologically plausible recurrent network model, which can perform Bayesian multisensory integration after trained by supervised learning. Our model is composed of two modules, each for one modality. We assume that each module is a recurrent network, whose activity represents the posterior distribution of each stimulus. The feedforward input on each module is the likelihood of each modality. Two modules are integrated through cross-links, which are feedforward connections from the other modality, and reciprocal connections, which are recurrent connections between different modules. By stochastic gradient descent, we successfully trained the feedforward and recurrent coupling matrices simultaneously, both of which resembles the Mexican-hat. We also find that there are more than one set of coupling matrices that can approximate the Bayesian theorem well. Specifically, reciprocal connections and cross-links will compensate each other if one of them is removed. Even though trained with two inputs, the network's performance with only one input is in good accordance with what is predicted by the Bayesian theorem.
A discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-D MRI.

PubMed

Wels, Michael; Carneiro, Gustavo; Aplas, Alexander; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2008-01-01

In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation approach based on a Markov random field (MRF) model that combines probabilistic boosting trees (PBT) and lower-level segmentation via graph cuts. The PBT algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. The discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. A mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. The proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. This segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. A quantitative evaluation illustrates the robustness of the proposed method. Despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-D MR brain tumor segmentation in adult patients. The entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.
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
Lentivector Integration Sites in Ependymal Cells From a Model of Metachromatic Leukodystrophy: Non-B DNA as a New Factor Influencing Integration

PubMed Central

McAllister, Robert G; Liu, Jiahui; Woods, Matthew W; Tom, Sean K; Rupar, C Anthony; Barr, Stephen D

2014-01-01

The blood–brain barrier controls the passage of molecules from the blood into the central nervous system (CNS) and is a major challenge for treatment of neurological diseases. Metachromatic leukodystrophy is a neurodegenerative lysosomal storage disease caused by loss of arylsulfatase A (ARSA) activity. Gene therapy via intraventricular injection of a lentiviral vector is a potential approach to rapidly and permanently deliver therapeutic levels of ARSA to the CNS. We present the distribution of integration sites of a lentiviral vector encoding human ARSA (LV-ARSA) in murine brain choroid plexus and ependymal cells, administered via a single intracranial injection into the CNS. LV-ARSA did not exhibit a strong preference for integration in or near actively transcribed genes, but exhibited a strong preference for integration in or near satellite DNA. We identified several genomic hotspots for LV-ARSA integration and identified a consensus target site sequence characterized by two G-quadruplex-forming motifs flanking the integration site. In addition, our analysis identified several other non-B DNA motifs as new factors that potentially influence lentivirus integration, including human immunodeficiency virus type-1 in human cells. Together, our data demonstrate a clinically favorable integration site profile in the murine brain and identify non-B DNA as a potential new host factor that influences lentiviral integration in murine and human cells. PMID:25158091
Multilayer modeling and analysis of human brain networks

PubMed Central

2017-01-01

Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916
Vinorelbine Delivery and Efficacy in the MDA-MB-231BR Preclinical Model of Brain Metastases of Breast Cancer.

PubMed

Samala, Ramakrishna; Thorsheim, Helen R; Goda, Satyanarayana; Taskar, Kunal; Gril, Brunilde; Steeg, Patricia S; Smith, Quentin R

2016-12-01

To evaluate vinorelbine drug exposure and activity in brain metastases of the human MDA-MB-231BR breast cancer model using integrated imaging and analysis. Brain and systemic metastases were created by administration of cancer cells in female NuNu mice. After metastases developed, animals were administered vinorelbine at the maximal tolerated dose (12 mg/kg), and were evaluated thereafter for total and unbound drug pharmacokinetics, biomarker TUNEL staining, and barrier permeability to Texas red. Median brain metastasis drug exposure was 4-fold greater than normal brain, yet only ~8% of non-barrier systemic metastases, which suggests restricted brain exposure. Unbound vinorelbine tissue/plasma partition coefficient, K p,uu , equaled ~1.0 in systemic metastases, but 0.03-0.22 in brain metastases, documenting restricted equilibration. In select sub-regions of highest drug-uptake brain metastases, K p,uu approached 1.0, indicating complete focal barrier breakdown. Most vinorelbine-treated brain metastases exhibited little or no positive early apoptosis TUNEL staining in vivo. The in vivo unbound vinorelbine IC 50 for TUNEL-positive staining (56 nM) was 4-fold higher than that measured in vitro (14 nM). Consistent with this finding, P-glycoprotein expression was observed to be substantially upregulated in brain metastasis cells in vivo. Vinorelbine exposure at maximum tolerated dose was less than one-tenth that in systemic metastases in >70% of brain metastases, and was associated with negligible biomarker effect. In small subregions of the highest uptake brain metastases, compromise of blood-tumor barrier appeared complete. The results suggest that restricted delivery accounts for 80% of the compromise in drug efficacy for vinorelbine against this model.
The frequently used intraperitoneal hyponatraemia model induces hypovolaemic hyponatraemia with possible model-dependent brain sodium loss.

PubMed

Overgaard-Steensen, Christian; Stødkilde-Jørgensen, Hans; Larsson, Anders; Tønnesen, Else; Frøkiaer, Jørgen; Ring, Troels

2016-07-01

What is the central question of this study? The brain response to acute hyponatraemia is usually studied in rodents by intraperitoneal instillation of hypotonic fluids (i.p. model). The i.p. model is described as 'dilutional' and 'syndrome of inappropriate ADH (SIADH)', but the mechanism has not been explored systematically and might affect the brain response. Therefore, in vivo brain and muscle response were studied in pigs. What is the main finding and its importance? The i.p. model induces hypovolaemic hyponatraemia attributable to sodium redistribution, not dilution. A large reduction in brain sodium is observed, probably because of the specific mechanism causing the hyponatraemia. This is not accounted for in current understanding of the brain response to acute hyponatraemia. Hyponatraemia is common clinically, and if it develops rapidly, brain oedema evolves, and severe morbidity and even death may occur. Experimentally, acute hyponatraemia is most frequently studied in small animal models, in which the hyponatraemia is produced by intraperitoneal instillation of hypotonic fluids (i.p. model). This hyponatraemia model is described as 'dilutional' or 'syndrome of inappropriate ADH (SIADH)', but seminal studies contradict this interpretation. To confront this issue, we developed an i.p. model in a large animal (the pig) and studied water and electrolyte responses in brain, muscle, plasma and urine. We hypothesized that hyponatraemia was induced by simple water dilution, with no change in organ sodium content. Moderate hypotonic hyponatraemia was induced by a single i.v. dose of desmopressin and intraperitoneal instillation of 2.5% glucose. All animals were anaesthetized and intensively monitored. In vivo brain and muscle water was determined by magnetic resonance imaging and related to the plasma sodium concentration. Muscle water content increased less than expected as a result of pure dilution, and muscle sodium content decreased significantly (by 28
Disruption of White Matter Integrity in Adult Survivors of Childhood Brain Tumors: Correlates with Long-Term Intellectual Outcomes.

PubMed

King, Tricia Z; Wang, Liya; Mao, Hui

2015-01-01

Although chemotherapy and radiation treatment have contributed to increased survivorship, treatment-induced brain injury has been a concern when examining long-term intellectual outcomes of survivors. Specifically, disruption of brain white matter integrity and its relationship to intellectual outcomes in adult survivors of childhood brain tumors needs to be better understood. Fifty-four participants underwent diffusion tensor imaging in addition to structural MRI and an intelligence test (IQ). Voxel-wise group comparisons of fractional anisotropy calculated from DTI data were performed using Tract Based Spatial Statistics (TBSS) on 27 survivors (14 treated with radiation with and without chemotherapy and 13 treated without radiation treatment on average over 13 years since diagnosis) and 27 healthy comparison participants. Whole brain white matter fractional anisotropy (FA) differences were explored between each group. The relationships between IQ and FA in the regions where statistically lower FA values were found in survivors were examined, as well as the role of cumulative neurological factors. The group of survivors treated with radiation with and without chemotherapy had lower IQ relative to the group of survivors without radiation treatment and the healthy comparison group. TBSS identified white matter regions with significantly different mean fractional anisotropy between the three different groups. A lower level of white matter integrity was found in the radiation with or without chemotherapy treated group compared to the group without radiation treatment and also the healthy control group. The group without radiation treatment had a lower mean FA relative to healthy controls. The white matter disruption of the radiation with or without chemotherapy treated survivors was positively correlated with IQ and cumulative neurological factors. Lower long-term intellectual outcomes of childhood brain tumor survivors are associated with lower white matter integrity
Prenatal Exposure of Guinea Pigs to the Organophosphorus Pesticide Chlorpyrifos Disrupts the Structural and Functional Integrity of the Brain

PubMed Central

Mullins, Roger J.; Xu, Su; Pereira, Edna F.R.; Pescrille, Joseph D.; Todd, Spencer W.; Mamczarz, Jacek; Albuquerque, Edson X.; Gullapalli, Rao P.

2015-01-01

This study was designed to test the hypothesis that prenatal exposure of guinea pigs to the organophosphorus (OP) pesticide chlorpyrifos (CPF) disrupts the structural and functional integrity of the brain. Pregnant guinea pigs were injected with chlorpyrifos (20 mg/kg, s.c.) or vehicle (peanut oil) once per day for ten consecutive days, starting approximately on the 50th day of gestation. Cognitive behavior of female offspring was examined starting at 40–45 post-natal days (PND) using the Morris Water Maze (MWM), and brain structural integrity was analyzed at PND 70 using magnetic resonance imaging (MRI) methods, including T2-weighted anatomical scans and Diffusion Kurtosis Imaging (DKI). The offspring of exposed mothers had significantly decreased body weight and brain volume, particularly in the frontal regions of the brain including the striatum. Furthermore, the offspring demonstrated significant spatial learning deficits in MWM recall compared to the vehicle group. Diffusion measures revealed reduced white matter integrity within the striatum and amygdala that correlated with spatial learning performance. These findings reveal the lasting effect of pre-natal exposure to CPF as well as the danger of mother to child transmission of CPF in the environment. PMID:25704171
Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

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

PubMed Central

Pantazatos, Spiro P.; Li, Jianrong; Pavlidis, Paul; Lussier, Yves A.

2009-01-01

An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets. PMID:20495688
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.
A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.

PubMed

Yao, Zizhen; Mich, John K; Ku, Sherman; Menon, Vilas; Krostag, Anne-Rachel; Martinez, Refugio A; Furchtgott, Leon; Mulholland, Heather; Bort, Susan; Fuqua, Margaret A; Gregor, Ben W; Hodge, Rebecca D; Jayabalu, Anu; May, Ryan C; Melton, Samuel; Nelson, Angelique M; Ngo, N Kiet; Shapovalova, Nadiya V; Shehata, Soraya I; Smith, Michael W; Tait, Leah J; Thompson, Carol L; Thomsen, Elliot R; Ye, Chaoyang; Glass, Ian A; Kaykas, Ajamete; Yao, Shuyuan; Phillips, John W; Grimley, Joshua S; Levi, Boaz P; Wang, Yanling; Ramanathan, Sharad

2017-01-05

During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/β-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders. Copyright © 2017 Elsevier Inc. All rights reserved.
Brain mechanisms in religion and spirituality: An integrative predictive processing framework.

PubMed

van Elk, Michiel; Aleman, André

2017-02-01

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

PubMed Central

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

2016-01-01

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

PubMed

Gisiger, Thomas; Kerszberg, Michel

2006-04-01

It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning), and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task), or recalling from this image another one that has been associated with it during training (delayed-pair association task). The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.
Network integrity of the parental brain in infancy supports the development of children’s social competencies

PubMed Central

Abraham, Eyal; Hendler, Talma; Zagoory-Sharon, Orna

2016-01-01

The cross-generational transmission of mammalian sociality, initiated by the parent’s postpartum brain plasticity and species-typical behavior that buttress offspring’s socialization, has not been studied in humans. In this longitudinal study, we measured brain response of 45 primary-caregiving parents to their infant’s stimuli, observed parent–infant interactions, and assayed parental oxytocin (OT). Intra- and inter-network connectivity were computed in three main networks of the human parental brain: core limbic, embodied simulation and mentalizing. During preschool, two key child social competencies were observed: emotion regulation and socialization. Parent’s network integrity in infancy predicted preschoolers’ social outcomes, with subcortical and cortical network integrity foreshadowing simple evolutionary-based regulatory tactics vs complex self-regulatory strategies and advanced socialization. Parent–infant synchrony mediated the links between connectivity of the parent’s embodied simulation network and preschoolers' ability to use cognitive/executive emotion regulation strategies, highlighting the inherently dyadic nature of this network and its long-term effects on tuning young to social life. Parent’s inter-network core limbic-embodied simulation connectivity predicted children’s OT as moderated by parental OT. Findings challenge solipsistic neuroscience perspectives by demonstrating how the parent–offspring interface enables the brain of one human to profoundly impact long-term adaptation of another. PMID:27369068
Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

PubMed

Siettos, Constantinos; Starke, Jens

2016-09-01

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

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

PubMed Central

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

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

PubMed

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

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

PubMed

Girard, Romuald; Zeineddine, Hussein A; Orsbon, Courtney; Tan, Huan; Moore, Thomas; Hobson, Nick; Shenkar, Robert; Lightle, Rhonda; Shi, Changbin; Fam, Maged D; Cao, Ying; Shen, Le; Neander, April I; Rorrer, Autumn; Gallione, Carol; Tang, Alan T; Kahn, Mark L; Marchuk, Douglas A; Luo, Zhe-Xi; Awad, Issam A

2016-09-15

Cerebral cavernous malformations (CCMs) are hemorrhagic brain lesions, where murine models allow major mechanistic discoveries, ushering genetic manipulations and preclinical assessment of therapies. Histology for lesion counting and morphometry is essential yet tedious and time consuming. We herein describe the application and validations of X-ray micro-computed tomography (micro-CT), a non-destructive technique allowing three-dimensional CCM lesion count and volumetric measurements, in transgenic murine brains. We hereby describe a new contrast soaking technique not previously applied to murine models of CCM disease. Volumetric segmentation and image processing paradigm allowed for histologic correlations and quantitative validations not previously reported with the micro-CT technique in brain vascular disease. Twenty-two hyper-dense areas on micro-CT images, identified as CCM lesions, were matched by histology. The inter-rater reliability analysis showed strong consistency in the CCM lesion identification and staging (K=0.89, p<0.0001) between the two techniques. Micro-CT revealed a 29% greater CCM lesion detection efficiency, and 80% improved time efficiency. Serial integrated lesional area by histology showed a strong positive correlation with micro-CT estimated volume (r(2)=0.84, p<0.0001). Micro-CT allows high throughput assessment of lesion count and volume in pre-clinical murine models of CCM. This approach complements histology with improved accuracy and efficiency, and can be applied for lesion burden assessment in other brain diseases. Copyright © 2016 Elsevier B.V. All rights reserved.
Docosahexaenoic acid: brain accretion and roles in neuroprotection after brain hypoxia and ischemia.

PubMed

Mayurasakorn, Korapat; Williams, Jill J; Ten, Vadim S; Deckelbaum, Richard J

2011-03-01

With important effects on neuronal lipid composition, neurochemical signaling and cerebrovascular pathobiology, docosahexaenoic acid (DHA), a n-3 polyunsaturated fatty acid, may emerge as a neuroprotective agent against cerebrovascular disease. This paper examines pathways for DHA accretion in brain and evidence for possible roles of DHA in prophylactic and therapeutic approaches for cerebrovascular disease. DHA is a major n-3 fatty acid in the mammalian central nervous system and enhances synaptic activities in neuronal cells. DHA can be obtained through diet or to a limited extent via conversion from its precursor, α-linolenic acid (α-LNA). DHA attenuates brain necrosis after hypoxic ischemic injury, principally by modulating membrane biophysical properties and maintaining integrity in functions between presynaptic and postsynaptic areas, resulting in better stabilizing intracellular ion balance in hypoxic-ischemic insult. Additionally, DHA alleviates brain apoptosis, by inducing antiapoptotic activities such as decreasing responses to reactive oxygen species, upregulating antiapoptotic protein expression, downregulating apoptotic protein expression, and maintaining mitochondrial integrity and function. DHA in brain relates to a number of efficient delivery and accretion pathways. In animal models DHA renders neuroprotection after hypoxic-ischemic injury by regulating multiple molecular pathways and gene expression.
Advance Preparation in Task-Switching: Converging Evidence from Behavioral, Brain Activation, and Model-Based Approaches

PubMed Central

Karayanidis, Frini; Jamadar, Sharna; Ruge, Hannes; Phillips, Natalie; Heathcote, Andrew; Forstmann, Birte U.

2010-01-01

Recent research has taken advantage of the temporal and spatial resolution of event-related brain potentials (ERPs) and functional magnetic resonance imaging (fMRI) to identify the time course and neural circuitry of preparatory processes required to switch between different tasks. Here we overview some key findings contributing to understanding strategic processes in advance preparation. Findings from these methodologies are compatible with advance preparation conceptualized as a set of processes activated for both switch and repeat trials, but with substantial variability as a function of individual differences and task requirements. We then highlight new approaches that attempt to capitalize on this variability to link behavior and brain activation patterns. One approach examines correlations among behavioral, ERP and fMRI measures. A second “model-based” approach accounts for differences in preparatory processes by estimating quantitative model parameters that reflect latent psychological processes. We argue that integration of behavioral and neuroscientific methodologies is key to understanding the complex nature of advance preparation in task-switching. PMID:21833196
Monitoring Blood-Brain Barrier Integrity Following Amyloid-β Immunotherapy Using Gadolinium-Enhanced MRI in a PDAPP Mouse Model.

PubMed

Blockx, Ines; Einstein, Steve; Guns, Pieter-Jan; Van Audekerke, Johan; Guglielmetti, Caroline; Zago, Wagner; Roose, Dimitri; Verhoye, Marleen; Van der Linden, Annemie; Bard, Frederique

2016-09-06

Amyloid-related imaging abnormalities (ARIA) have been reported with some anti-amyloid-β (Aβ) immunotherapy trials. They are detected with magnetic resonance imaging (MRI) and thought to represent transient accumulation of fluid/edema (ARIA-E) or microhemorrhages (ARIA-H). Although the clinical significance and pathophysiology are unknown, it has been proposed that anti-Aβimmunotherapy may affect blood-brain barrier (BBB) integrity. To examine vascular integrity in aged (12-16 months) PDAPP and wild type mice (WT), we performed a series of longitudinal in vivo MRI studies. Mice were treated on a weekly basis using anti-Aβimmunotherapy (3D6) and follow up was done longitudinally from 1-12 weeks after treatment. BBB-integrity was assessed using both visual assessment of T1-weighted scans and repeated T1 mapping in combination with gadolinium (Gd-DOTA). A subset of 3D6 treated PDAPP mice displayed numerous BBB disruptions, whereas WT and saline-treated PDAPP mice showed intact BBB integrity under the conditions tested. In addition, the contrast induced decrease in T1 value was observed in the meningeal and midline area. BBB disruption events occurred early during treatment (between 1 and 5 weeks), were transient, and resolved quickly. Finally, BBB-leakages associated with microhemorrhages were confirmed by Perls'Prussian blue histopathological analysis. Our preclinical findings support the hypothesis that 3D6 leads to transient leakage from amyloid-positive vessels. The current study has provided valuable insights on the time course of vascular alterations during immunization treatment and supports further research in relation to the nature of ARIA and the utility of in vivo repeated T1 MRI as a translational tool.
Characterization of the resting-state brain network topology in the 6-hydroxydopamine rat model of Parkinson’s disease

PubMed Central

Simmons, Camilla; Mesquita, Michel B.; Wood, Tobias C.; Williams, Steve C. R.; Vernon, Anthony C.; Cash, Diana

2017-01-01

Resting-state functional MRI (rsfMRI) is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson’s disease (PD), revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine (6-OHDA) rat, a robust experimental model of the dopamine depletion implicated in PD. Using graph theory to analyse the rsfMRI data, we were able to provide meaningful and translatable measures of integrity, influence and segregation of the underlying functional brain architecture. Specifically, we confirm that rats share a similar functional brain network topology as observed in humans, characterised by small-worldness and modularity. Interestingly, we observed significantly reduced functional connectivity in the 6-OHDA rats, primarily in the ipsilateral (lesioned) hemisphere as evidenced by significantly lower node degree, local efficiency and clustering coefficient in the motor, orbital and sensorimotor cortices. In contrast, we found significantly, and bilaterally, increased thalamic functional connectivity in the lesioned rats. The unilateral deficits in the cortex are consistent with the unilateral nature of this model and further support the validity of the rsfMRI technique in rodents. We thereby provide a methodological framework for the investigation of brain networks in other rodent experimental models of PD, as well as of animal models in general, for cross-comparison with human data. PMID:28249008
Normal Brain-Skull Development with Hybrid Deformable VR Models Simulation.

PubMed

Jin, Jing; De Ribaupierre, Sandrine; Eagleson, Roy

2016-01-01

This paper describes a simulation framework for a clinical application involving skull-brain co-development in infants, leading to a platform for craniosynostosis modeling. Craniosynostosis occurs when one or more sutures are fused early in life, resulting in an abnormal skull shape. Surgery is required to reopen the suture and reduce intracranial pressure, but is difficult without any predictive model to assist surgical planning. We aim to study normal brain-skull growth by computer simulation, which requires a head model and appropriate mathematical methods for brain and skull growth respectively. On the basis of our previous model, we further specified suture model into fibrous and cartilaginous sutures and develop algorithm for skull extension. We evaluate the resulting simulation by comparison with datasets of cases and normal growth.
Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep.

PubMed

Deco, Gustavo; Tagliazucchi, Enzo; Laufs, Helmut; Sanjuán, Ana; Kringelbach, Morten L

2017-01-01

A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.
Physical Exercise Keeps the Brain Connected: Biking Increases White Matter Integrity in Patients With Schizophrenia and Healthy Controls

PubMed Central

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

2015-01-01

It has been shown that learning a new skill leads to structural changes in the brain. However, it is unclear whether it is the acquisition or continuous practicing of the skill that causes this effect and whether brain connectivity of patients with schizophrenia can benefit from such practice. We examined the effect of 6 months exercise on a stationary bicycle on the brain in patients with schizophrenia and healthy controls. Biking is an endemic skill in the Netherlands and thus offers an ideal situation to disentangle the effects of learning vs practice. The 33 participating patients with schizophrenia and 48 healthy individuals were assigned to either one of two conditions, ie, physical exercise or life-as-usual, balanced for diagnosis. Diffusion tensor imaging brain scans were made prior to and after intervention. We demonstrate that irrespective of diagnosis regular physical exercise of an overlearned skill, such as bicycling, significantly increases the integrity, especially of motor functioning related, white matter fiber tracts whereas life-as-usual leads to a decrease in fiber integrity. Our findings imply that exercise of an overlearned physical skill improves brain connectivity in patients and healthy individuals. This has important implications for understanding the effect of fitness programs on the brain in both healthy subjects and patients with schizophrenia. Moreover, the outcome may even apply to the nonphysical realm. PMID:25829377
Inferring brain-computational mechanisms with models of activity measurements

PubMed Central

Diedrichsen, Jörn

2016-01-01

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
Bridging animal and human models of exercise-induced brain plasticity

PubMed Central

Voss, Michelle W.; Vivar, Carmen; Kramer, Arthur F.; van Praag, Henriette

2015-01-01

Significant progress has been made in understanding the neurobiological mechanisms through which exercise protects and restores the brain. In this feature review, we integrate animal and human research, examining physical activity effects across multiple levels of description (neurons up to inter-regional pathways). We evaluate the influence of exercise on hippocampal structure and function, addressing common themes such as spatial memory and pattern separation, brain structure and plasticity, neurotrophic factors, and vasculature. Areas of research focused more within species, such as hippocampal neurogenesis in rodents, also provide crucial insight into the protective role of physical activity. Overall, converging evidence suggests exercise benefits brain function and cognition across the mammalian lifespan, which may translate into reduced risk for Alzheimer’s disease (AD) in humans. PMID:24029446
A family of hyperelastic models for human brain tissue

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

PubMed

Ostrowski, N L

1998-11-01

The nonapeptide, oxytocin (OT), has been implicated in a wide range of physiological, behavioral and pharmacological effects related to learning and memory, parturition and lactation, maternal and sexual behavior, and the formation of social attachments. Specific G-protein linked membrane bound OT receptors mediate OTs effects. The unavailability of highly selective pharmacological ligands that discriminate the OT receptor from the highly homologous vasopressin receptors (V1a, V1b and V2 subtypes) has made it difficult to confirm specific effects of oxytocin, particularly in brain regions where OT and multiple AVP receptor subtypes may be coexpressed. Here, data on the oxytocin receptor (OTR) messenger ribonucleic acid (mRNA) localization in brain are presented in the context of a model that proposes a reproductive state-dependent role for steroid-hormone restructuring of neural circuits, and a role for oxytocin in the integration of neural transmission in pathways subserving: (1) steroid-sensitive reproductive behaviors; (2) learning; and (3) reinforcement. It is hypothesized that social attachments emerge as a consequence of a conditioned association between OT-related activity in these pathways and the eliciting stimulus.
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. Copyright © 2013 Wiley Periodicals, Inc.
From synthetic modeling of social interaction to dynamic theories of brain-body-environment-body-brain systems.

PubMed

Froese, Tom; Iizuka, Hiroyuki; Ikegami, Takashi

2013-08-01

Synthetic approaches to social interaction support the development of a second-person neuroscience. Agent-based models and psychological experiments can be related in a mutually informing manner. Models have the advantage of making the nonlinear brain-body-environment-body-brain system as a whole accessible to analysis by dynamical systems theory. We highlight some general principles of how social interaction can partially constitute an individual's behavior.
Integration of fMRI, NIROT and ERP for studies of human brain function.

PubMed

Gore, John C; Horovitz, Silvina G; Cannistraci, Christopher J; Skudlarski, Pavel

2006-05-01

Different methods of assessing human brain function possess specific advantages and disadvantages compared to others, but it is believed that combining different approaches will provide greater information than can be obtained from each alone. For example, functional magnetic resonance imaging (fMRI) has good spatial resolution but poor temporal resolution, whereas the converse is true for electrophysiological recordings (event-related potentials or ERPs). In this review of recent work, we highlight a novel approach to combining these modalities in a manner designed to increase information on the origins and locations of the generators of specific ERPs and the relationship between fMRI and ERP signals. Near infrared imaging techniques have also been studied as alternatives to fMRI and can be readily integrated with simultaneous electrophysiological recordings. Each of these modalities may in principle be also used in so-called steady-state acquisitions in which the correlational structure of signals from the brain may be analyzed to provide new insights into brain function.
Callosal Function in Pediatric Traumatic Brain Injury Linked to Disrupted White Matter Integrity

PubMed Central

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

2015-01-01

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

PubMed

Yamanishi, Teruya; Liu, Jian-Qin; Nishimura, Haruhiko

2012-08-01

Recently, numerous attempts have been made to understand the dynamic behavior of complex brain systems using neural network models. The fluctuations in blood-oxygen-level-dependent (BOLD) brain signals at less than 0.1 Hz have been observed by functional magnetic resonance imaging (fMRI) for subjects in a resting state. This phenomenon is referred to as a "default-mode brain network." In this study, we model the default-mode brain network by functionally connecting neural communities composed of spiking neurons in a complex network. Through computational simulations of the model, including transmission delays and complex connectivity, the network dynamics of the neural system and its behavior are discussed. The results show that the power spectrum of the modeled fluctuations in the neuron firing patterns is consistent with the default-mode brain network's BOLD signals when transmission delays, a characteristic property of the brain, have finite values in a given range.

Using induced pluripotent stem cells derived neurons to model brain diseases.

PubMed

McKinney, Cindy E

2017-07-01

The ability to use induced pluripotent stem cells (iPSC) to model brain diseases is a powerful tool for unraveling mechanistic alterations in these disorders. Rodent models of brain diseases have spurred understanding of pathology but the concern arises that they may not recapitulate the full spectrum of neuron disruptions associated with human neuropathology. iPSC derived neurons, or other neural cell types, provide the ability to access pathology in cells derived directly from a patient's blood sample or skin biopsy where availability of brain tissue is limiting. Thus, utilization of iPSC to study brain diseases provides an unlimited resource for disease modelling but may also be used for drug screening for effective therapies and may potentially be used to regenerate aged or damaged cells in the future. Many brain diseases across the spectrum of neurodevelopment, neurodegenerative and neuropsychiatric are being approached by iPSC models. The goal of an iPSC based disease model is to identify a cellular phenotype that discriminates the disease-bearing cells from the control cells. In this mini-review, the importance of iPSC cell models validated for pluripotency, germline competency and function assessments is discussed. Selected examples for the variety of brain diseases that are being approached by iPSC technology to discover or establish the molecular basis of the neuropathology are discussed.
A hierarchical model of the evolution of human brain specializations

PubMed Central

Barrett, H. Clark

2012-01-01

The study of information-processing adaptations in the brain is controversial, in part because of disputes about the form such adaptations might take. Many psychologists assume that adaptations come in two kinds, specialized and general-purpose. Specialized mechanisms are typically thought of as innate, domain-specific, and isolated from other brain systems, whereas generalized mechanisms are developmentally plastic, domain-general, and interactive. However, if brain mechanisms evolve through processes of descent with modification, they are likely to be heterogeneous, rather than coming in just two kinds. They are likely to be hierarchically organized, with some design features widely shared across brain systems and others specific to particular processes. Also, they are likely to be largely developmentally plastic and interactive with other brain systems, rather than canalized and isolated. This article presents a hierarchical model of brain specialization, reviewing evidence for the model from evolutionary developmental biology, genetics, brain mapping, and comparative studies. Implications for the search for uniquely human traits are discussed, along with ways in which conventional views of modularity in psychology may need to be revised. PMID:22723350
A generative model of whole-brain effective connectivity.

PubMed

Frässle, Stefan; Lomakina, Ekaterina I; Kasper, Lars; Manjaly, Zina M; Leff, Alex; Pruessmann, Klaas P; Buhmann, Joachim M; Stephan, Klaas E

2018-05-25

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure. Copyright © 2018. Published by Elsevier Inc.
Integrative strategies to identify candidate genes in rodent models of human alcoholism.

PubMed

Treadwell, Julie A

2006-01-01

The search for genes underlying alcohol-related behaviours in rodent models of human alcoholism has been ongoing for many years with only limited success. Recently, new strategies that integrate several of the traditional approaches have provided new insights into the molecular mechanisms underlying ethanol's actions in the brain. We have used alcohol-preferring C57BL/6J (B6) and alcohol-avoiding DBA/2J (D2) genetic strains of mice in an integrative strategy combining high-throughput gene expression screening, genetic segregation analysis, and mapping to previously published quantitative trait loci to uncover candidate genes for the ethanol-preference phenotype. In our study, 2 genes, retinaldehyde binding protein 1 (Rlbp1) and syntaxin 12 (Stx12), were found to be strong candidates for ethanol preference. Such experimental approaches have the power and the potential to greatly speed up the laborious process of identifying candidate genes for the animal models of human alcoholism.
An integrative model of auditory phantom perception: tinnitus as a unified percept of interacting separable subnetworks.

PubMed

De Ridder, Dirk; Vanneste, Sven; Weisz, Nathan; Londero, Alain; Schlee, Winnie; Elgoyhen, Ana Belen; Langguth, Berthold

2014-07-01

Tinnitus is a considered to be an auditory phantom phenomenon, a persistent conscious percept of a salient memory trace, externally attributed, in the absence of a sound source. It is perceived as a phenomenological unified coherent percept, binding multiple separable clinical characteristics, such as its loudness, the sidedness, the type (pure tone, noise), the associated distress and so on. A theoretical pathophysiological framework capable of explaining all these aspects in one model is highly needed. The model must incorporate both the deafferentation based neurophysiological models and the dysfunctional noise canceling model, and propose a 'tinnitus core' subnetwork. The tinnitus core can be defined as the minimal set of brain areas that needs to be jointly activated (=subnetwork) for tinnitus to be consciously perceived, devoid of its affective components. The brain areas involved in the other separable characteristics of tinnitus can be retrieved by studies on spontaneous resting state magnetic and electrical activity in people with tinnitus, evaluated for the specific aspect investigated and controlled for other factors. By combining these functional imaging studies with neuromodulation techniques some of the correlations are turned into causal relationships. Thereof, a heuristic pathophysiological framework is constructed, integrating the tinnitus perceptual core with the other tinnitus related aspects. This phenomenological unified percept of tinnitus can be considered an emergent property of multiple, parallel, dynamically changing and partially overlapping subnetworks, each with a specific spontaneous oscillatory pattern and functional connectivity signature. Communication between these different subnetworks is proposed to occur at hubs, brain areas that are involved in multiple subnetworks simultaneously. These hubs can take part in each separable subnetwork at different frequencies. Communication between the subnetworks is proposed to occur at
Gpr124 is essential for blood-brain barrier integrity in central nervous system disease.

PubMed

Chang, Junlei; Mancuso, Michael R; Maier, Carolina; Liang, Xibin; Yuki, Kanako; Yang, Lu; Kwong, Jeffrey W; Wang, Jing; Rao, Varsha; Vallon, Mario; Kosinski, Cynthia; Zhang, J J Haijing; Mah, Amanda T; Xu, Lijun; Li, Le; Gholamin, Sharareh; Reyes, Teresa F; Li, Rui; Kuhnert, Frank; Han, Xiaoyuan; Yuan, Jenny; Chiou, Shin-Heng; Brettman, Ari D; Daly, Lauren; Corney, David C; Cheshier, Samuel H; Shortliffe, Linda D; Wu, Xiwei; Snyder, Michael; Chan, Pak; Giffard, Rona G; Chang, Howard Y; Andreasson, Katrin; Kuo, Calvin J

2017-04-01

Although blood-brain barrier (BBB) compromise is central to the etiology of diverse central nervous system (CNS) disorders, endothelial receptor proteins that control BBB function are poorly defined. The endothelial G-protein-coupled receptor (GPCR) Gpr124 has been reported to be required for normal forebrain angiogenesis and BBB function in mouse embryos, but the role of this receptor in adult animals is unknown. Here Gpr124 conditional knockout (CKO) in the endothelia of adult mice did not affect homeostatic BBB integrity, but resulted in BBB disruption and microvascular hemorrhage in mouse models of both ischemic stroke and glioblastoma, accompanied by reduced cerebrovascular canonical Wnt-β-catenin signaling. Constitutive activation of Wnt-β-catenin signaling fully corrected the BBB disruption and hemorrhage defects of Gpr124-CKO mice, with rescue of the endothelial gene tight junction, pericyte coverage and extracellular-matrix deficits. We thus identify Gpr124 as an endothelial GPCR specifically required for endothelial Wnt signaling and BBB integrity under pathological conditions in adult mice. This finding implicates Gpr124 as a potential therapeutic target for human CNS disorders characterized by BBB disruption.
Development of three-dimensional brain arteriovenous malformation model for patient communication and young neurosurgeon education.

PubMed

Dong, Mengqi; Chen, Guangzhong; Qin, Kun; Ding, Xiaowen; Zhou, Dong; Peng, Chao; Zeng, Shaojian; Deng, Xianming

2018-01-15

Rapid prototyping technology is used to fabricate three-dimensional (3D) brain arteriovenous malformation (AVM) models and facilitate presurgical patient communication and medical education for young surgeons. Two intracranial AVM cases were selected for this study. Using 3D CT angiography or 3D rotational angiography images, the brain AVM models were reconstructed on personal computer and the rapid prototyping process was completed using a 3D printer. The size and morphology of the models were compared to brain digital subtraction arteriography of the same patients. 3D brain AVM models were used for preoperative patient communication and young neurosurgeon education. Two brain AVM models were successfully produced. By neurosurgeons' evaluation, the printed models have high fidelity with the actual brain AVM structures of the patients. The patient responded positively toward the brain AVM model specific to himself. Twenty surgical residents from residency programs tested the brain AVM models and provided positive feedback on their usefulness as educational tool and resemblance to real brain AVM structures. Patient-specific 3D printed models of brain AVM can be constructed with high fidelity. 3D printed brain AVM models are proved to be helpful in preoperative patient consultation, surgical planning and resident training.
Integrated Modeling Environment

NASA Technical Reports Server (NTRS)

Mosier, Gary; Stone, Paul; Holtery, Christopher

2006-01-01

The Integrated Modeling Environment (IME) is a software system that establishes a centralized Web-based interface for integrating people (who may be geographically dispersed), processes, and data involved in a common engineering project. The IME includes software tools for life-cycle management, configuration management, visualization, and collaboration.
Pathophysiological Responses in Rat and Mouse Models of Radiation-Induced Brain Injury.

PubMed

Yang, Lianhong; Yang, Jianhua; Li, Guoqian; Li, Yi; Wu, Rong; Cheng, Jinping; Tang, Yamei

2017-03-01

The brain is the major dose-limiting organ in patients undergoing radiotherapy for assorted conditions. Radiation-induced brain injury is common and mainly occurs in patients receiving radiotherapy for malignant head and neck tumors, arteriovenous malformations, or lung cancer-derived brain metastases. Nevertheless, the underlying mechanisms of radiation-induced brain injury are largely unknown. Although many treatment strategies are employed for affected individuals, the effects remain suboptimal. Accordingly, animal models are extremely important for elucidating pathogenic radiation-associated mechanisms and for developing more efficacious therapies. So far, models employing various animal species with different radiation dosages and fractions have been introduced to investigate the prevention, mechanisms, early detection, and management of radiation-induced brain injury. However, these models all have limitations, and none are widely accepted. This review summarizes the animal models currently set forth for studies of radiation-induced brain injury, especially rat and mouse, as well as radiation dosages, dose fractionation, and secondary pathophysiological responses.
Brain networks engaged in audiovisual integration during speech perception revealed by persistent homology-based network filtration.

PubMed

Kim, Heejung; Hahm, Jarang; Lee, Hyekyoung; Kang, Eunjoo; Kang, Hyejin; Lee, Dong Soo

2015-05-01

The human brain naturally integrates audiovisual information to improve speech perception. However, in noisy environments, understanding speech is difficult and may require much effort. Although the brain network is supposed to be engaged in speech perception, it is unclear how speech-related brain regions are connected during natural bimodal audiovisual or unimodal speech perception with counterpart irrelevant noise. To investigate the topological changes of speech-related brain networks at all possible thresholds, we used a persistent homological framework through hierarchical clustering, such as single linkage distance, to analyze the connected component of the functional network during speech perception using functional magnetic resonance imaging. For speech perception, bimodal (audio-visual speech cue) or unimodal speech cues with counterpart irrelevant noise (auditory white-noise or visual gum-chewing) were delivered to 15 subjects. In terms of positive relationship, similar connected components were observed in bimodal and unimodal speech conditions during filtration. However, during speech perception by congruent audiovisual stimuli, the tighter couplings of left anterior temporal gyrus-anterior insula component and right premotor-visual components were observed than auditory or visual speech cue conditions, respectively. Interestingly, visual speech is perceived under white noise by tight negative coupling in the left inferior frontal region-right anterior cingulate, left anterior insula, and bilateral visual regions, including right middle temporal gyrus, right fusiform components. In conclusion, the speech brain network is tightly positively or negatively connected, and can reflect efficient or effortful processes during natural audiovisual integration or lip-reading, respectively, in speech perception.
Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

Abstract A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states. PMID:28966977
Brain-mapping projects using the common marmoset.

PubMed

Okano, Hideyuki; Mitra, Partha

2015-04-01

Globally, there is an increasing interest in brain-mapping projects, including the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative project in the USA, the Human Brain Project (HBP) in Europe, and the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) project in Japan. These projects aim to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain. Brain/MINDS is focused on structural and functional mapping of the common marmoset (Callithrix jacchus) brain. This non-human primate has numerous advantages for brain mapping, including a well-developed frontal cortex and a compact brain size, as well as the availability of transgenic technologies. In the present review article, we discuss strategies for structural and functional mapping of the marmoset brain and the relation of the common marmoset to other animals models. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Dynamic causal modelling of brain-behaviour relationships.

PubMed

Rigoux, L; Daunizeau, J

2015-08-15

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

PubMed Central

Lacquaniti, Francesco; La Scaleia, Barbara; Maffei, Vincenzo

2014-01-01

Gravity is crucial for spatial perception, postural equilibrium, and movement generation. The vestibular apparatus is the main sensory system involved in monitoring gravity. Hair cells in the vestibular maculae respond to gravitoinertial forces, but they cannot distinguish between linear accelerations and changes of head orientation relative to gravity. The brain deals with this sensory ambiguity (which can cause some lethal airplane accidents) by combining several cues with the otolith signals: angular velocity signals provided by the semicircular canals, proprioceptive signals from muscles and tendons, visceral signals related to gravity, and visual signals. In particular, vision provides both static and dynamic signals about body orientation relative to the vertical, but it poorly discriminates arbitrary accelerations of moving objects. However, we are able to visually detect the specific acceleration of gravity since early infancy. This ability depends on the fact that gravity effects are stored in brain regions which integrate visual, vestibular, and neck proprioceptive signals and combine this information with an internal model of gravity effects. PMID:25061610
Multisensory integration and internal models for sensing gravity effects in primates.

PubMed

Lacquaniti, Francesco; Bosco, Gianfranco; Gravano, Silvio; Indovina, Iole; La Scaleia, Barbara; Maffei, Vincenzo; Zago, Myrka

2014-01-01

Gravity is crucial for spatial perception, postural equilibrium, and movement generation. The vestibular apparatus is the main sensory system involved in monitoring gravity. Hair cells in the vestibular maculae respond to gravitoinertial forces, but they cannot distinguish between linear accelerations and changes of head orientation relative to gravity. The brain deals with this sensory ambiguity (which can cause some lethal airplane accidents) by combining several cues with the otolith signals: angular velocity signals provided by the semicircular canals, proprioceptive signals from muscles and tendons, visceral signals related to gravity, and visual signals. In particular, vision provides both static and dynamic signals about body orientation relative to the vertical, but it poorly discriminates arbitrary accelerations of moving objects. However, we are able to visually detect the specific acceleration of gravity since early infancy. This ability depends on the fact that gravity effects are stored in brain regions which integrate visual, vestibular, and neck proprioceptive signals and combine this information with an internal model of gravity effects.
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.
Dendrimer brain uptake and targeted therapy for brain injury in a large animal model of hypothermic circulatory arrest.

PubMed

Mishra, Manoj K; Beaty, Claude A; Lesniak, Wojciech G; Kambhampati, Siva P; Zhang, Fan; Wilson, Mary A; Blue, Mary E; Troncoso, Juan C; Kannan, Sujatha; Johnston, Michael V; Baumgartner, William A; Kannan, Rangaramanujam M

2014-03-25

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

PubMed Central

2015-01-01

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

PubMed

Emmett, Mark R; Kroes, Roger A; Moskal, Joseph R; Conrad, Charles A; Priebe, Waldemar; Laezza, Fernanda; Meyer-Baese, Anke; Nilsson, Carol L

2014-01-01

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.
Integrative Biological Analysis For Neuropsychopharmacology

PubMed Central

Emmett, Mark R; Kroes, Roger A; Moskal, Joseph R; Conrad, Charles A; Priebe, Waldemar; Laezza, Fernanda; Meyer-Baese, Anke; Nilsson, Carol L

2014-01-01

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches—proteomics, transcriptomics, metabolomics, and glycomics—have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studes that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine. PMID:23800968

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

PubMed

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

2017-02-11

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

PubMed Central

Richardet, Renaud; Chappelier, Jean-Cédric; Telefont, Martin; Hill, Sean

2015-01-01

Motivation: In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications. This lack of normalization and centralization hinders the large-scale integration of brain connectivity results. In this article, we present text-mining models to extract and aggregate brain connectivity results from 13.2 million PubMed abstracts and 630 216 full-text publications related to neuroscience. The brain regions are identified with three different named entity recognizers (NERs) and then normalized against two atlases: the Allen Brain Atlas (ABA) and the atlas from the Brain Architecture Management System (BAMS). We then use three different extractors to assess inter-region connectivity. Results: NERs and connectivity extractors are evaluated against a manually annotated corpus. The complete in litero extraction models are also evaluated against in vivo connectivity data from ABA with an estimated precision of 78%. The resulting database contains over 4 million brain region mentions and over 100 000 (ABA) and 122 000 (BAMS) potential brain region connections. This database drastically accelerates connectivity literature review, by providing a centralized repository of connectivity data to neuroscientists. Availability and implementation: The resulting models are publicly available at github.com/BlueBrain/bluima. Contact: renaud.richardet@epfl.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25609795
A dynamic in vivo-like organotypic blood-brain barrier model to probe metastatic brain tumors

NASA Astrophysics Data System (ADS)

Xu, Hui; Li, Zhongyu; Yu, Yue; Sizdahkhani, Saman; Ho, Winson S.; Yin, Fangchao; Wang, Li; Zhu, Guoli; Zhang, Min; Jiang, Lei; Zhuang, Zhengping; Qin, Jianhua

2016-11-01

The blood-brain barrier (BBB) restricts the uptake of many neuro-therapeutic molecules, presenting a formidable hurdle to drug development in brain diseases. We proposed a new and dynamic in vivo-like three-dimensional microfluidic system that replicates the key structural, functional and mechanical properties of the blood-brain barrier in vivo. Multiple factors in this system work synergistically to accentuate BBB-specific attributes-permitting the analysis of complex organ-level responses in both normal and pathological microenvironments in brain tumors. The complex BBB microenvironment is reproduced in this system via physical cell-cell interaction, vascular mechanical cues and cell migration. This model possesses the unique capability to examine brain metastasis of human lung, breast and melanoma cells and their therapeutic responses to chemotherapy. The results suggest that the interactions between cancer cells and astrocytes in BBB microenvironment might affect the ability of malignant brain tumors to traverse between brain and vascular compartments. Furthermore, quantification of spatially resolved barrier functions exists within a single assay, providing a versatile and valuable platform for pharmaceutical development, drug testing and neuroscientific research.
Identification of brain metastasis genes and therapeutic evaluation of histone deacetylase inhibitors in a clinically relevant model of breast cancer brain metastasis.

PubMed

Kim, Soo-Hyun; Redvers, Richard P; Chi, Lap Hing; Ling, Xiawei; Lucke, Andrew J; Reid, Robert C; Fairlie, David P; Baptista Moreno Martin, Ana Carolina; Anderson, Robin L; Denoyer, Delphine; Pouliot, Normand

2018-05-21

Breast cancer brain metastasis remains largely incurable. While several mouse models have been developed to investigate the genes and mechanisms regulating breast cancer brain metastasis, these models often lack clinical relevance since they require the use of immune-compromised mice and/or are poorly metastatic to brain from the mammary gland. We describe the development and characterisation of an aggressive brain metastatic variant of the 4T1 syngeneic model (4T1Br4) that spontaneously metastasises to multiple organs, but is selectively more metastatic to the brain from the mammary gland than parental 4T1 tumours. By immunohistochemistry, 4T1Br4 tumours and brain metastases display a triple negative phenotype, consistent with the high propensity of this breast cancer subtype to spread to brain. In vitro assays indicate that 4T1Br4 cells have an enhanced ability to adhere to or migrate across a brain-derived endothelial monolayer and greater invasive response to brain-derived soluble factors compared to 4T1 cells. These properties are likely to contribute to the brain-selectivity of 4T1Br4 tumours. Expression profiling and gene set enrichment analyses demonstrate the clinical relevance of the 4T1Br4 model at the transcriptomic level. Pathway analyses implicate tumour-intrinsic immune regulation and vascular interactions in successful brain colonisation, revealing potential therapeutic targets. Evaluation of two histone deacetylase inhibitors, SB939 and 1179.4b, shows partial efficacy against 4T1Br4 metastasis to brain and other sites in vivo and potent radio-sensitising properties in vitro The 4T1Br4 model provides a clinically relevant tool for mechanistic studies and to evaluate novel therapies against brain metastasis. © 2018. Published by The Company of Biologists Ltd.
Cellular-based modeling of oscillatory dynamics in brain networks.

PubMed

Skinner, Frances K

2012-08-01

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.
The multisensory brain and its ability to learn music.

PubMed

Zimmerman, Emily; Lahav, Amir

2012-04-01

Playing a musical instrument requires a complex skill set that depends on the brain's ability to quickly integrate information from multiple senses. It has been well documented that intensive musical training alters brain structure and function within and across multisensory brain regions, supporting the experience-dependent plasticity model. Here, we argue that this experience-dependent plasticity occurs because of the multisensory nature of the brain and may be an important contributing factor to musical learning. This review highlights key multisensory regions within the brain and discusses their role in the context of music learning and rehabilitation. © 2012 New York Academy of Sciences.
A Porcine Model of Traumatic Brain Injury via Head Rotational Acceleration

PubMed Central

Cullen, D. Kacy; Harris, James P.; Browne, Kevin D.; Wolf, John A; Duda, John E.; Meaney, David F.; Margulies, Susan S.; Smith, Douglas H.

2017-01-01

Unique from other brain disorders, traumatic brain injury (TBI) generally results from a discrete biomechanical event that induces rapid head movement. The large size and high organization of the human brain makes it particularly vulnerable to traumatic injury from rotational accelerations that can cause dynamic deformation of the brain tissue. Therefore, replicating the injury biomechanics of human TBI in animal models presents a substantial challenge, particularly with regard to addressing brain size and injury parameters. Here we present the historical development and use of a porcine model of head rotational acceleration. By scaling up the rotational forces to account for difference in brain mass between swine and humans, this model has been shown to produce the same tissue deformations and identical neuropathologies found in human TBI. The parameters of scaled rapid angular accelerations applied for the model reproduce inertial forces generated when the human head suddenly accelerates or decelerates in falls, collisions, or blunt impacts. The model uses custom-built linkage assemblies and a powerful linear actuator designed to produce purely impulsive nonimpact head rotation in different angular planes at controlled rotational acceleration levels. Through a range of head rotational kinematics, this model can produce functional and neuropathological changes across the spectrum from concussion to severe TBI. Notably, however, the model is very difficult to employ, requiring a highly skilled team for medical management, biomechanics, neurological recovery, and specialized outcome measures including neuromonitoring, neurophysiology, neuroimaging, and neuropathology. Nonetheless, while challenging, this clinically relevant model has proven valuable for identifying mechanisms of acute and progressive neuropathologies as well as for the evaluation of noninvasive diagnostic techniques and potential neuroprotective treatments following TBI. PMID:27604725
Analysis of the characteristics of the synchronous clusters in the adaptive Kuramoto network and neural network of the epileptic brain

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Kharchenko, Alexander A.; Makarov, Vladimir V.; Khramova, Marina V.; Koronovskii, Alexey A.; Pavlov, Alexey N.; Dana, Syamal K.

2016-04-01

In the paper we study the mechanisms of phase synchronization in the adaptive model network of Kuramoto oscillators and the neural network of brain by consideration of the integral characteristics of the observed networks signals. As the integral characteristics of the model network we consider the summary signal produced by the oscillators. Similar to the model situation we study the ECoG signal as the integral characteristic of neural network of the brain. We show that the establishment of the phase synchronization results in the increase of the peak, corresponding to synchronized oscillators, on the wavelet energy spectrum of the integral signals. The observed correlation between the phase relations of the elements and the integral characteristics of the whole network open the way to detect the size of synchronous clusters in the neural networks of the epileptic brain before and during seizure.
Left Brain/Right Brain Learning for Adult Education.

ERIC Educational Resources Information Center

Garvin, Barbara

1986-01-01

Contrasts and compares the theory and practice of adult education as it relates to the issue of right brain/left brain learning. The author stresses the need for a whole-brain approach to teaching and suggests that adult educators, given their philosophical directions, are the perfect potential users of this integrated system. (Editor/CT)
Docosahexaenoic acid: brain accretion and roles in neuroprotection after brain hypoxia and ischemia

PubMed Central

Mayurasakorn, Korapat; Williams, Jill J.; Ten, Vadim S.; Deckelbaum, Richard J.

2014-01-01

Purpose of review With important effects on neuronal lipid composition, neurochemical signaling and cerebrovascular pathobiology, docosahexaenoic acid (DHA), a n-3 polyunsaturated fatty acid, may emerge as a neuroprotective agent against cerebrovascular disease. This paper examines pathways for DHA accretion in brain and evidence for possible roles of DHA in prophylactic and therapeutic approaches for cerebrovascular disease. Recent findings DHA is a major n-3 fatty acid in the mammalian central nervous system and enhances synaptic activities in neuronal cells. DHA can be obtained through diet or to a limited extent via conversion from its precursor, α-linolenic acid (α-LNA). DHA attenuates brain necrosis after hypoxic ischemic injury, principally by modulating membrane biophysical properties and maintaining integrity in functions between pre-and post-synaptic areas, resulting in better stabilizing intracellular ion balance in hypoxic-ischemic insult. Additionally, DHA alleviates brain apoptosis, by inducing anti-apoptotic activities such as decreasing responses to reactive oxygen species, up-regulating anti-apoptotic protein expression, down-regulating apoptotic protein expression, and maintaining mitochondrial integrity and function. Summary DHA in brain relates to a number of efficient delivery and accretion pathways. In animal models DHA renders neuroprotection after hypoxic-ischemic injury by regulating multiple molecular pathways and gene expression. PMID:21178607
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.
Shock wave-induced brain injury in rat: novel traumatic brain injury animal model.

PubMed

Nakagawa, Atsuhiro; Fujimura, Miki; Kato, Kaoruko; Okuyama, Hironobu; Hashimoto, Tokitada; Takayama, Kazuyoshi; Tominaga, Teiji

2008-01-01

In blast wave injury and high-energy traumatic brain injury, shock waves (SW) play an important role along with cavitation phenomena. However, due to lack of reliable and reproducible technical approaches, extensive study of this type of injury has not yet been reported. The present study aims to develop reliable SW-induced brain injury model by focusing micro-explosion generated SW in the rat brain. Adult male rats were exposed to single SW focusing created by detonation of microgram order of silver azide crystals with laser irradiation at a focal point of a truncated ellipsoidal cavity of20 mm minor diameter and the major to minor diameter ratio of 1.41 after craniotomy. The pressure profile was recorded using polyvinylidene fluoride needle hydrophone. Animals were divided into three groups according to the given overpressure: Group I: Control, Group II: 12.5 +/- 2.5 MPa (high pressure), and Group III: 1.0 +/- 0.2 MPa (low pressure). Histological changes were evaluated over time by hematoxylin-eosin staining. Group II SW injuries resulted in contusional hemorrhage in reproducible manner. Group III exposure resulted in spindle-shaped changes of neurons and elongation of nucleus without marked neuronal injury. The use of SW loading by micro-explosion is useful to provide a reliable and reproducible SW-induced brain injury model in rats.
Neurodegeneration from mitochondrial insufficiency: nutrients, stem cells, growth factors, and prospects for brain rebuilding using integrative management.

PubMed

Kidd, Parris M

2005-12-01

Degenerative brain disorders (neurodegeneration) can be frustrating for both conventional and alternative practitioners. A more comprehensive, integrative approach is urgently needed. One emerging focus for intervention is brain energetics. Specifically, mitochondrial insufficiency contributes to the etiopathology of many such disorders. Electron leakages inherent to mitochondrial energetics generate reactive oxygen free radical species that may place the ultimate limit on lifespan. Exogenous toxins, such as mercury and other environmental contaminants, exacerbate mitochondrial electron leakage, hastening their demise and that of their host cells. Studies of the brain in Alzheimer's and other dementias, Down syndrome, stroke, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, Huntington's disease, Friedreich's ataxia, aging, and constitutive disorders demonstrate impairments of the mitochondrial citric acid cycle and oxidative phosphorylation (OXPHOS) enzymes. Imaging or metabolic assays frequently reveal energetic insufficiency and depleted energy reserve in brain tissue in situ. Orthomolecular nutrients involved in mitochondrial metabolism provide clinical benefit. Among these are the essential minerals and the B vitamin group; vitamins E and K; and the antioxidant and energetic cofactors alpha-lipoic acid (ALA), ubiquinone (coenzyme Q10; CoQ10), and nicotinamide adenine dinucleotide, reduced (NADH). Recent advances in the area of stem cells and growth factors encourage optimism regarding brain regeneration. The trophic nutrients acetyl L-carnitine (ALCAR), glycerophosphocholine (GPC), and phosphatidylserine (PS) provide mitochondrial support and conserve growth factor receptors; all three improved cognition in double-blind trials. The omega-3 fatty acid docosahexaenoic acid (DHA) is enzymatically combined with GPC and PS to form membrane phospholipids for nerve cell expansion. Practical recommendations are presented for integrating these
Corticonic models of brain mechanisms underlying cognition and intelligence

NASA Astrophysics Data System (ADS)

Farhat, Nabil H.

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

NASA Astrophysics Data System (ADS)

Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

2017-08-01

This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.
Patients' experiences and care needs during the diagnostic phase of an Integrated Brain Cancer Pathway: A Case Study.

PubMed

Vedelø, Tina Wang; Sørensen, Jens Christian Hedemann; Delmar, Charlotte

2018-03-31

To identify and describe patients' experiences and care needs throughout the diagnostic phase of an Integrated Brain Cancer Pathway. A malignant brain tumour is a devastating diagnosis, which may cause psychical symptoms and cognitive deficits. Studies have shown that the shock of the diagnosis, combined with the multiple symptoms, affect patients' ability to understand information and express needs of care and support. Unmet needs have been reported within this group of patients, however, the experiences and care needs of patients going through the diagnostic phase of a standardised Integrated Brain Cancer Pathway have not previously been explored. A Case Study design was used to provide detailed information of the complex needs of patients being diagnosed with a malignant brain tumour. Research interviews and direct participant observation of four patients during hospital admission, brain surgery and discharge were conducted in a Danish university hospital. Systematic text condensation was used to analyse the data material. Four major themes were identified: information needs, balancing hope and reality while trying to perceive the unknown reality of brain cancer, not knowing what to expect and participants' perceptions of the relationship with the health care providers. The analysis revealed that participants were in risk of having unmet information needs and that contextual factors seemed to cause fragmented care that led to feelings of uncertainty and loss of control. Brain tumour patients have complex care needs and experience a particular state of vulnerability during the diagnostic phase. Through personal relationships based on trust with skilled health care providers, participants experienced an existential recognition and alleviation of emotional distress. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Preoperative three-dimensional model creation of magnetic resonance brain images as a tool to assist neurosurgical planning.

PubMed

Spottiswoode, B S; van den Heever, D J; Chang, Y; Engelhardt, S; Du Plessis, S; Nicolls, F; Hartzenberg, H B; Gretschel, A

2013-01-01

Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention. Copyright © 2013 S. Karger AG, Basel.
Brain vascular heterogeneity: implications for disease pathogenesis and design of in vitro blood-brain barrier models.

PubMed

Noumbissi, Midrelle E; Galasso, Bianca; Stins, Monique F

2018-04-23

The vertebrate blood-brain barrier (BBB) is composed of cerebral microvascular endothelial cells (CEC). The BBB acts as a semi-permeable cellular interface that tightly regulates bidirectional molecular transport between blood and the brain parenchyma in order to maintain cerebral homeostasis. The CEC phenotype is regulated by a variety of factors, including cells in its immediate environment and within functional neurovascular units. The cellular composition of the brain parenchyma surrounding the CEC varies between different brain regions; this difference is clearly visible in grey versus white matter. In this review, we discuss evidence for the existence of brain vascular heterogeneity, focusing on differences between the vessels of the grey and white matter. The region-specific differences in the vasculature of the brain are reflective of specific functions of those particular brain areas. This BBB-endothelial heterogeneity may have implications for the course of pathogenesis of cerebrovascular diseases and neurological disorders involving vascular activation and dysfunction. This heterogeneity should be taken into account when developing BBB-neuro-disease models representative of specific brain areas.
Omics analysis of mouse brain models of human diseases.

PubMed

Paban, Véronique; Loriod, Béatrice; Villard, Claude; Buee, Luc; Blum, David; Pietropaolo, Susanna; Cho, Yoon H; Gory-Faure, Sylvie; Mansour, Elodie; Gharbi, Ali; Alescio-Lautier, Béatrice

2017-02-05

The identification of common gene/protein profiles related to brain alterations, if they exist, may indicate the convergence of the pathogenic mechanisms driving brain disorders. Six genetically engineered mouse lines modelling neurodegenerative diseases and neuropsychiatric disorders were considered. Omics approaches, including transcriptomic and proteomic methods, were used. The gene/protein lists were used for inter-disease comparisons and further functional and network investigations. When the inter-disease comparison was performed using the gene symbol identifiers, the number of genes/proteins involved in multiple diseases decreased rapidly. Thus, no genes/proteins were shared by all 6 mouse models. Only one gene/protein (Gfap) was shared among 4 disorders, providing strong evidence that a common molecular signature does not exist among brain diseases. The inter-disease comparison of functional processes showed the involvement of a few major biological processes indicating that brain diseases of diverse aetiologies might utilize common biological pathways in the nervous system, without necessarily involving similar molecules. Copyright © 2016 Elsevier B.V. All rights reserved.

A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease.

PubMed

Demirtaş, Murat; Falcon, Carles; Tucholka, Alan; Gispert, Juan Domingo; Molinuevo, José Luis; Deco, Gustavo

2017-01-01

Alzheimer's disease (AD) is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC) of the subjects with preclinical Alzheimer's disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer's disease (AD), the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC) strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC) in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1 - 42) total tau (t-tau) and phosphorylated tau (p-tau). CSF Aβ1 - 42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1 - 42. APOE4 carriership showed no significant correlations with the connectivity measures.
Multiclassifier fusion in human brain MR segmentation: modelling convergence.

PubMed

Heckemann, Rolf A; Hajnal, Joseph V; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2006-01-01

Segmentations of MR images of the human brain can be generated by propagating an existing atlas label volume to the target image. By fusing multiple propagated label volumes, the segmentation can be improved. We developed a model that predicts the improvement of labelling accuracy and precision based on the number of segmentations used as input. Using a cross-validation study on brain image data as well as numerical simulations, we verified the model. Fit parameters of this model are potential indicators of the quality of a given label propagation method or the consistency of the input segmentations used.
Physical Exercise Keeps the Brain Connected: Biking Increases White Matter Integrity in Patients With Schizophrenia and Healthy Controls.

PubMed

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

2015-07-01

It has been shown that learning a new skill leads to structural changes in the brain. However, it is unclear whether it is the acquisition or continuous practicing of the skill that causes this effect and whether brain connectivity of patients with schizophrenia can benefit from such practice. We examined the effect of 6 months exercise on a stationary bicycle on the brain in patients with schizophrenia and healthy controls. Biking is an endemic skill in the Netherlands and thus offers an ideal situation to disentangle the effects of learning vs practice. The 33 participating patients with schizophrenia and 48 healthy individuals were assigned to either one of two conditions, ie, physical exercise or life-as-usual, balanced for diagnosis. Diffusion tensor imaging brain scans were made prior to and after intervention. We demonstrate that irrespective of diagnosis regular physical exercise of an overlearned skill, such as bicycling, significantly increases the integrity, especially of motor functioning related, white matter fiber tracts whereas life-as-usual leads to a decrease in fiber integrity. Our findings imply that exercise of an overlearned physical skill improves brain connectivity in patients and healthy individuals. This has important implications for understanding the effect of fitness programs on the brain in both healthy subjects and patients with schizophrenia. Moreover, the outcome may even apply to the nonphysical realm. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.
A Novel Mouse Model of Penetrating Brain Injury

PubMed Central

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

2014-01-01

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

PubMed

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

2010-01-01

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

PubMed

Saidi, Maryam; Towhidkhah, Farzad; Gharibzadeh, Shahriar; Lari, Abdolaziz Azizi

2013-12-01

Humans perceive the surrounding world by integration of information through different sensory modalities. Earlier models of multisensory integration rely mainly on traditional Bayesian and causal Bayesian inferences for single causal (source) and two causal (for two senses such as visual and auditory systems), respectively. In this paper a new recurrent neural model is presented for integration of visual and proprioceptive information. This model is based on population coding which is able to mimic multisensory integration of neural centers in the human brain. The simulation results agree with those achieved by casual Bayesian inference. The model can also simulate the sensory training process of visual and proprioceptive information in human. Training process in multisensory integration is a point with less attention in the literature before. The effect of proprioceptive training on multisensory perception was investigated through a set of experiments in our previous study. The current study, evaluates the effect of both modalities, i.e., visual and proprioceptive training and compares them with each other through a set of new experiments. In these experiments, the subject was asked to move his/her hand in a circle and estimate its position. The experiments were performed on eight subjects with proprioception training and eight subjects with visual training. Results of the experiments show three important points: (1) visual learning rate is significantly more than that of proprioception; (2) means of visual and proprioceptive errors are decreased by training but statistical analysis shows that this decrement is significant for proprioceptive error and non-significant for visual error, and (3) visual errors in training phase even in the beginning of it, is much less than errors of the main test stage because in the main test, the subject has to focus on two senses. The results of the experiments in this paper is in agreement with the results of the neural model
Neuronavigation in the surgical management of brain tumors: current and future trends

PubMed Central

Orringer, Daniel A; Golby, Alexandra; Jolesz, Ferenc

2013-01-01

Neuronavigation has become an ubiquitous tool in the surgical management of brain tumors. This review describes the use and limitations of current neuronavigational systems for brain tumor biopsy and resection. Methods for integrating intraoperative imaging into neuronavigational datasets developed to address the diminishing accuracy of positional information that occurs over the course of brain tumor resection are discussed. In addition, the process of integration of functional MRI and tractography into navigational models is reviewed. Finally, emerging concepts and future challenges relating to the development and implementation of experimental imaging technologies in the navigational environment are explored. PMID:23116076
Monitoring the injured brain: registered, patient specific atlas models to improve accuracy of recovered brain saturation values

NASA Astrophysics Data System (ADS)

Clancy, Michael; Belli, Antonio; Davies, David; Lucas, Samuel J. E.; Su, Zhangjie; Dehghani, Hamid

2015-07-01

The subject of superficial contamination and signal origins remains a widely debated topic in the field of Near Infrared Spectroscopy (NIRS), yet the concept of using the technology to monitor an injured brain, in a clinical setting, poses additional challenges concerning the quantitative accuracy of recovered parameters. Using high density diffuse optical tomography probes, quantitatively accurate parameters from different layers (skin, bone and brain) can be recovered from subject specific reconstruction models. This study assesses the use of registered atlas models for situations where subject specific models are not available. Data simulated from subject specific models were reconstructed using the 8 registered atlas models implementing a regional (layered) parameter recovery in NIRFAST. A 3-region recovery based on the atlas model yielded recovered brain saturation values which were accurate to within 4.6% (percentage error) of the simulated values, validating the technique. The recovered saturations in the superficial regions were not quantitatively accurate. These findings highlight differences in superficial (skin and bone) layer thickness between the subject and atlas models. This layer thickness mismatch was propagated through the reconstruction process decreasing the parameter accuracy.
Development of a rat model for studying blast-induced traumatic brain injury.

PubMed

Cheng, Jingmin; Gu, Jianwen; Ma, Yuan; Yang, Tao; Kuang, Yongqin; Li, Bingcang; Kang, Jianyi

2010-07-15

Blast-induced traumatic brain injury (TBI) has been the predominant cause of neurotrauma in current military conflicts, and it is also emerging as a potential threat in civilian terrorism. The etiology of TBI, however, is poorly understood. Further study on the mechanisms and treatment of blast injury is urgently needed. We developed a unique rat model to simulate blast effects that commonly occur on the battlefield. An electric detonator with the equivalent of 400 mg TNT was developed as the explosive source. The detonator's peak overpressure and impulse of explosion shock determined the explosion intensity in a distance-dependent manner. Ninety-six male adult Sprague-Dawley rats were randomly divided into four groups: 5-cm, 7.5-cm, 10-cm, and control groups. The rat was fixed in a specially designed cabin with an adjustable aperture showing the frontal, parietal, and occipital parts of the head exposed to explosion; the eyes, ears, mouth, and nose were protected by the cabin. After each explosion, we assessed the physiologic, neuropathologic, and neurobehavioral consequences of blast injury. Changes of brain tissue water content and neuron-specific enolase (NSE) expression were detected. The results in the 7.5-cm group show that 87% rats developed apnea, limb seizure, poor appetite, and limpness. Diffuse subarachnoid hemorrhage and edema could be seen within the brain parenchyma, which showed a loss of integrity. Capillary damage and enlarged intercellular and vascular space in the cortex, along with a tattered nerve fiber were observed. These findings demonstrate that we have provided a reliable and reproducible blast-induced TBI model in rats. Copyright 2010 Elsevier B.V. All rights reserved.
Evaluation of laser speckle contrast imaging as an intrinsic method to monitor blood brain barrier integrity

PubMed Central

Dufour, Suzie; Atchia, Yaaseen; Gad, Raanan; Ringuette, Dene; Sigal, Iliya; Levi, Ofer

2013-01-01

The integrity of the blood brain barrier (BBB) can contribute to the development of many brain disorders. We evaluate laser speckle contrast imaging (LSCI) as an intrinsic modality for monitoring BBB disruptions through simultaneous fluorescence and LSCI with vertical cavity surface emitting lasers (VCSELs). We demonstrated that drug-induced BBB opening was associated with a relative change of the arterial and venous blood velocities. Cross-sectional flow velocity ratio (veins/arteries) decreased significantly in rats treated with BBB-opening drugs, ≤0.81 of initial values. PMID:24156049
Ethical issues when modelling brain disorders innon-human primates.

PubMed

Neuhaus, Carolyn P

2018-05-01

Non-human animal models of human diseases advance our knowledge of the genetic underpinnings of disease and lead to the development of novel therapies for humans. While mice are the most common model organisms, their usefulness is limited. Larger animals may provide more accurate and valuable disease models, but it has, until recently, been challenging to create large animal disease models. Genome editors, such as Clustered Randomised Interspersed Palindromic Repeat (CRISPR), meet some of these challenges and bring routine genome engineering of larger animals and non-human primates (NHPs) well within reach. There is growing interest in creating NHP models of brain disorders such as autism, depression and Alzheimer's, which are very difficult to model or study in other organisms, including humans. New treatments are desperately needed for this set of disorders. This paper is novel in asking: Insofar as NHPs are being considered for use as model organisms for brain disorders, can this be done ethically? The paper concludes that it cannot. Notwithstanding ongoing debate about NHPs' moral status, (1) animal welfare concerns, (2) the availability of alternative methods of studying brain disorders and (3) unmet expectations of benefit justify a stop on the creation of NHP model organisms to study brain disorders. The lure of using new genetic technologies combined with the promise of novel therapeutics presents a formidable challenge to those who call for slow, careful, and only necessary research involving NHPs. But researchers should not create macaques with social deficits or capuchin monkeys with memory deficits just because they can. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
[Effect of ginsenoside Rb1 on cerebral infarction volume and IL-1 beta in the brain tissue and sera of focal cerebral ischemia/reperfusion injury model rats].

PubMed

Liu, Jun-Wei; Ren, Ye-Long; Liu, Xu-Ling; Xia, Hong-Lian; Zhang, Hui-Ling; Jin, Shen-Hui; Dai, Qin-Xue; Wang, Jun-Lu

2013-12-01

To investigate the effect of ginsenoside Rb1 on cerebral infarction volume as well as IL-1 beta in the brain tissue and sera of focal cerebral ischemia/reperfusion (I/R) injury model rats. The I/R rat model was established by using thread according to Zea-Longa. SD rats were randomly divided into five groups, i.e., the sham-operation group, the model group, the low dose ginsenoside Rb1 (20 mg/kg) group, the medium dose ginsenoside Rb1 group (40 mg/kg), and the high dose ginsenoside Rb1 group (80 mg/kg), 12 in each group. Rats in the sham-operation group only received middle cerebral artery occlusion (MCAO) but without thread insertion. The MCAO model was prepared in the rest 4 groups, followed by MCAO2 h later. Ginsenoside Rb1 at each dose was peritoneally administrated to rats in corresponding groups immediately after cerebral ischemia. Equal volume of normal saline was administered to rats in the sham-operation group. Rats' cerebral infarction volume, integrals of neurologic defect degree, expression of IL-1 beta content in the brain tissue and sera were observed 24 h after 2-h cerebral I/R. In the model group, integrals of neurologic defect degree were improved (P < 0.01), IL-1 beta positive cells in the brain tissue increased and serum IL-1 beta content elevated (P < 0.05), when compared with the sham-operation group. In comparison of the model group, integrals of neurologic defect degree were lowered in the medium dose and high dose ginsenoside Rb1 groups (P < 0.05, P < 0.01). The cerebral infarction volume was all shrunken in each ginsenoside Rb1 group, IL-1 beta positive cells in the brain tissue decreased, and IL-1 beta content in serum reduced (P < 0.01, P < 0.05). Compared with the low dose ginsenoside Rb1 group, integrals of neurologic defect degree decreased, the cerebral infarction volume shrunken, and IL-1 beta content in serum reduced in the high dose ginsenoside Rb1 group (P < 0.01, P < 0.05). Ginsenoside Rb1 (20, 40, 80 mg/kg) might effectively
Fetal brain extracellular matrix boosts neuronal network formation in 3D bioengineered model of cortical brain tissue.

PubMed

Sood, Disha; Chwalek, Karolina; Stuntz, Emily; Pouli, Dimitra; Du, Chuang; Tang-Schomer, Min; Georgakoudi, Irene; Black, Lauren D; Kaplan, David L

2016-01-01

The extracellular matrix (ECM) constituting up to 20% of the organ volume is a significant component of the brain due to its instructive role in the compartmentalization of functional microdomains in every brain structure. The composition, quantity and structure of ECM changes dramatically during the development of an organism greatly contributing to the remarkably sophisticated architecture and function of the brain. Since fetal brain is highly plastic, we hypothesize that the fetal brain ECM may contain cues promoting neural growth and differentiation, highly desired in regenerative medicine. Thus, we studied the effect of brain-derived fetal and adult ECM complemented with matricellular proteins on cortical neurons using in vitro 3D bioengineered model of cortical brain tissue. The tested parameters included neuronal network density, cell viability, calcium signaling and electrophysiology. Both, adult and fetal brain ECM as well as matricellular proteins significantly improved neural network formation as compared to single component, collagen I matrix. Additionally, the brain ECM improved cell viability and lowered glutamate release. The fetal brain ECM induced superior neural network formation, calcium signaling and spontaneous spiking activity over adult brain ECM. This study highlights the difference in the neuroinductive properties of fetal and adult brain ECM and suggests that delineating the basis for this divergence may have implications for regenerative medicine.
Convergent models of handedness and brain lateralization

PubMed Central

Sainburg, Robert L.

2014-01-01

The pervasive nature of handedness across human history and cultures is a salient consequence of brain lateralization. This paper presents evidence that provides a structure for understanding the motor control processes that give rise to handedness. According to the Dynamic Dominance Model, the left hemisphere (in right handers) is proficient for processes that predict the effects of body and environmental dynamics, while the right hemisphere is proficient at impedance control processes that can minimize potential errors when faced with unexpected mechanical conditions, and can achieve accurate steady-state positions. This model can be viewed as a motor component for the paradigm of brain lateralization that has been proposed by Rogers et al. (MacNeilage et al., 2009) that is based upon evidence from a wide range of behaviors across many vertebrate species. Rogers proposed a left-hemisphere specialization for well-established patterns of behavior performed in familiar environmental conditions, and a right hemisphere specialization for responding to unforeseen environmental events. The dynamic dominance hypothesis provides a framework for understanding the biology of motor lateralization that is consistent with Roger's paradigm of brain lateralization. PMID:25339923
Dynamics of the brain: Mathematical models and non-invasive experimental studies

NASA Astrophysics Data System (ADS)

Toronov, V.; Myllylä, T.; Kiviniemi, V.; Tuchin, V. V.

2013-10-01

Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.
[Impact of acquired brain injury towards the community integration: employment outcome, disability and dependence two years after injury].

PubMed

Luna-Lario, P; Ojeda, N; Tirapu-Ustarroz, J; Pena, J

2016-06-16

To analyze the impact of acquired brain injury towards the community integration (professional career, disability, and dependence) in a sample of people affected by vascular, traumatic and tumor etiology acquired brain damage, over a two year time period after the original injury, and also to examine what sociodemographic variables, premorbid and injury related clinical data can predict the level of the person's integration into the community. 106 adults sample suffering from acquired brain injury who were attended by the Neuropsychology and Neuropsychiatry Department at Hospital of Navarra (Spain) affected by memory deficit as their main sequel. Differences among groups have been analyzed by using t by Student, chi squared and U by Mann-Whitney tests. 19% and 29% of the participants who were actively working before the injury got back their previous status within one and two years time respectively. 45% of the total sample were recognized disabled and 17% dependant. No relationship between sociodemographic and clinical variables and functional parameters observed were found. Acquired brain damage presents a high intensity impact on affected person's life trajectory. Nevertheless, in Spain, its consequences at sociolaboral adjustment over the the two years following the damage through functional parameters analyzed with official governmental means over a vascular, traumatic and tumor etiology sample had never been studied before.
Enhanced microglial pro-inflammatory response to lipopolysaccharide correlates with brain infiltration and blood-brain barrier dysregulation in a mouse model of telomere shortening.

PubMed

Raj, Divya D A; Moser, Jill; van der Pol, Susanne M A; van Os, Ronald P; Holtman, Inge R; Brouwer, Nieske; Oeseburg, Hisko; Schaafsma, Wandert; Wesseling, Evelyn M; den Dunnen, Wilfred; Biber, Knut P H; de Vries, Helga E; Eggen, Bart J L; Boddeke, Hendrikus W G M

2015-12-01

Microglia are a proliferative population of resident brain macrophages that under physiological conditions self-renew independent of hematopoiesis. Microglia are innate immune cells actively surveying the brain and are the earliest responders to injury. During aging, microglia elicit an enhanced innate immune response also referred to as 'priming'. To date, it remains unknown whether telomere shortening affects the proliferative capacity and induces priming of microglia. We addressed this issue using early (first-generation G1 mTerc(-/-) )- and late-generation (third-generation G3 and G4 mTerc(-/-) ) telomerase-deficient mice, which carry a homozygous deletion for the telomerase RNA component gene (mTerc). Late-generation mTerc(-/-) microglia show telomere shortening and decreased proliferation efficiency. Under physiological conditions, gene expression and functionality of G3 mTerc(-/-) microglia are comparable with microglia derived from G1 mTerc(-/-) mice despite changes in morphology. However, after intraperitoneal injection of bacterial lipopolysaccharide (LPS), G3 mTerc(-/-) microglia mice show an enhanced pro-inflammatory response. Nevertheless, this enhanced inflammatory response was not accompanied by an increased expression of genes known to be associated with age-associated microglia priming. The increased inflammatory response in microglia correlates closely with increased peripheral inflammation, a loss of blood-brain barrier integrity, and infiltration of immune cells in the brain parenchyma in this mouse model of telomere shortening. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.
Using chaotic artificial neural networks to model memory in the brain

NASA Astrophysics Data System (ADS)

Aram, Zainab; Jafari, Sajad; Ma, Jun; Sprott, Julien C.; Zendehrouh, Sareh; Pham, Viet-Thanh

2017-03-01

In the current study, a novel model for human memory is proposed based on the chaotic dynamics of artificial neural networks. This new model explains a biological fact about memory which is not yet explained by any other model: There are theories that the brain normally works in a chaotic mode, while during attention it shows ordered behavior. This model uses the periodic windows observed in a previously proposed model for the brain to store and then recollect the information.
The stress-vulnerability model how does stress impact on mental illness at the level of the brain and what are the consequences?

PubMed

Goh, Cindy; Agius, Mark

2010-06-01

The stress -vulnerability model (Zubin et al. 1977) is an extremely useful model for identifying and treating relapses of mental illness. We accept that human persons carry genetic and other predisposition to mental illness. However, the question arises as to how stress impacts on a person in order to cause mental illness to develop. Furthermore there arises the issue as to what other effects such stress has on the human body beyond the human brain. Our aim was to research and integrate the current literature in order to establish how stress impacts on the brain at the cellular level, and to establish whether there are other consequences for the human body brought about by the impact of stress on the human brain. Literature Search, using pubmed. We have identified much literature on how stress affects biological mechanisms within the brain, and how it relates to biological vulnerabilities carried by different individuals. We have identified communalities in how the interplay between stress and vulnerability occurs in different disease processes.

A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.
Combination radiotherapy in an orthotopic mouse brain tumor model.

PubMed

Kramp, Tamalee R; Camphausen, Kevin

2012-03-06

Glioblastoma multiforme (GBM) are the most common and aggressive adult primary brain tumors. In recent years there has been substantial progress in the understanding of the mechanics of tumor invasion, and direct intracerebral inoculation of tumor provides the opportunity of observing the invasive process in a physiologically appropriate environment. As far as human brain tumors are concerned, the orthotopic models currently available are established either by stereotaxic injection of cell suspensions or implantation of a solid piece of tumor through a complicated craniotomy procedure. In our technique we harvest cells from tissue culture to create a cell suspension used to implant directly into the brain. The duration of the surgery is approximately 30 minutes, and as the mouse needs to be in a constant surgical plane, an injectable anesthetic is used. The mouse is placed in a stereotaxic jig made by Stoetling (figure 1). After the surgical area is cleaned and prepared, an incision is made; and the bregma is located to determine the location of the craniotomy. The location of the craniotomy is 2 mm to the right and 1 mm rostral to the bregma. The depth is 3 mm from the surface of the skull, and cells are injected at a rate of 2 μl every 2 minutes. The skin is sutured with 5-0 PDS, and the mouse is allowed to wake up on a heating pad. From our experience, depending on the cell line, treatment can take place from 7-10 days after surgery. Drug delivery is dependent on the drug composition. For radiation treatment the mice are anesthetized, and put into a custom made jig. Lead covers the mouse's body and exposes only the brain of the mouse. The study of tumorigenesis and the evaluation of new therapies for GBM require accurate and reproducible brain tumor animal models. Thus we use this orthotopic brain model to study the interaction of the microenvironment of the brain and the tumor, to test the effectiveness of different therapeutic agents with and without
Creating Physical 3D Stereolithograph Models of Brain and Skull

PubMed Central

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

2007-01-01

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

PubMed Central

Pizzagalli, Diego A.

2014-01-01

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

PubMed Central

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

2013-01-01

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

PubMed

Rosario, Emily R; Espinoza, Laura; Kaplan, Stephanie; Khonsari, Sepehr; Thurndyke, Earl; Bustos, Melissa; Vickers, Kayla; Navarro, Brittney; Scudder, Bonnie

2017-01-01

To determine the effectiveness of a Navigation programme for patients with traumatic brain injury. Prospective programme evaluation. Inpatient rehabilitation facility and community settings. Eighteen individuals who suffered a traumatic brain injury (TBI), were between the ages of 16-70 years, and had a Rancho Score greater than IV. Patient navigation programme focused on identifying and addressing barriers to positive outcomes, including coordination of care and facilitating communication among the family and healthcare providers, psychosocial support, caregiver support, adherence to treatment, education, community resources and financial issues. Functional status, re-hospitalizations, falls, neurobehavioral symptom inventory, neuroendocrine status, activities of daily living, community integration and caregiver burden. There was a significant reduction in re-hospitalization and fall rate when comparing individuals who received navigation services and those who did not. We also observed improved adherence treatment plans and a significant increase in community integration, independence level and functional abilities. This study begins to highlight the effectiveness of a patient navigation programme for individuals with TBI. Future research with a larger sample will continue to help us refine patient navigation for chronic disabling conditions and determine its sustainability.
Using connectome-based predictive modeling to predict individual behavior from brain connectivity

PubMed Central

Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd

2017-01-01

Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017
Immortalized endothelial cell lines for in vitro blood-brain barrier models: A systematic review.

PubMed

Rahman, Nurul Adhwa; Rasil, Alifah Nur'ain Haji Mat; Meyding-Lamade, Uta; Craemer, Eva Maria; Diah, Suwarni; Tuah, Ani Afiqah; Muharram, Siti Hanna

2016-07-01

Endothelial cells play the most important role in construction of the blood-brain barrier. Many studies have opted to use commercially available, easily transfected or immortalized endothelial cell lines as in vitro blood-brain barrier models. Numerous endothelial cell lines are available, but we do not currently have strong evidence for which cell lines are optimal for establishment of such models. This review aimed to investigate the application of immortalized endothelial cell lines as in vitro blood-brain barrier models. The databases used for this review were PubMed, OVID MEDLINE, ProQuest, ScienceDirect, and SpringerLink. A narrative systematic review was conducted and identified 155 studies. As a result, 36 immortalized endothelial cell lines of human, mouse, rat, porcine and bovine origins were found for the establishment of in vitro blood-brain barrier and brain endothelium models. This review provides a summary of immortalized endothelial cell lines as a guideline for future studies and improvements in the establishment of in vitro blood-brain barrier models. It is important to establish a good and reproducible model that has the potential for multiple applications, in particular a model of such a complex compartment such as the blood-brain barrier. Copyright © 2016 Elsevier B.V. All rights reserved.
Separate Brain Circuits Support Integrative and Semantic Priming in the Human Language System.

PubMed

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

2016-07-01

Semantic priming is a crucial phenomenon to study the organization of semantic memory. A novel type of priming effect, integrative priming, has been identified behaviorally, whereby a prime word facilitates recognition of a target word when the 2 concepts can be combined to form a unitary representation. We used both functional and anatomical imaging approaches to investigate the neural substrates supporting such integrative priming, and compare them with those in semantic priming. Similar behavioral priming effects for both semantic (Bread-Cake) and integrative conditions (Cherry-Cake) were observed when compared with an unrelated condition. However, a clearly dissociated brain response was observed between these 2 types of priming. The semantic-priming effect was localized to the posterior superior temporal and middle temporal gyrus. In contrast, the integrative-priming effect localized to the left anterior inferior frontal gyrus and left anterior temporal cortices. Furthermore, fiber tractography showed that the integrative-priming regions were connected via uncinate fasciculus fiber bundle forming an integrative circuit, whereas the semantic-priming regions connected to the posterior frontal cortex via separated pathways. The results point to dissociable neural pathways underlying the 2 distinct types of priming, illuminating the neural circuitry organization of semantic representation and integration. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Angiopoietin-2 mediates blood-brain barrier impairment and colonization of triple-negative breast cancer cells in brain.

PubMed

Avraham, Hava Karsenty; Jiang, Shuxian; Fu, Yigong; Nakshatri, Harikrishna; Ovadia, Haim; Avraham, Shalom

2014-02-01

Although the incidence of breast cancer metastasis (BCM) in brain has increased significantly in triple-negative breast cancer (TNBC), the mechanisms remain elusive. Using in vivo mouse models for BCM in brain, we observed that TNBC cells crossed the blood-brain barrier (BBB), lodged in the brain microvasculature and remained adjacent to brain microvascular endothelial cells (BMECs). Breaching of the BBB in vivo by TNBCs resulted in increased BBB permeability and changes in ZO-1 and claudin-5 tight junction (TJ) protein structures. Angiopoietin-2 expression was elevated in BMECs and was correlated with BBB disruption. Secreted Ang-2 impaired TJ structures and increased BBB permeability. Treatment of mice with the neutralizing Ang-2 peptibody trebananib prevented changes in the BBB integrity and BMEC destabilization, resulting in inhibition of TNBC colonization in brain. Thus, Ang-2 is involved in initial steps of brain metastasis cascade, and inhibitors for Ang-2 may serve as potential therapeutics for brain metastasis. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
The role of right frontal brain regions in integration of spatial relation.

PubMed

Han, Jiahui; Cao, Bihua; Cao, Yunfei; Gao, Heming; Li, Fuhong

2016-06-01

Previous studies have explored the neural mechanisms of spatial reasoning on a two-dimensional (2D) plane; however, it remains unclear how spatial reasoning is conducted in a three-dimensional (3D) condition. In the present study, we presented 3D geometric objects to 16 adult participants, and asked them to process the spatial relationship between different corners of the geometric objects. In premise-1, the first two corners of a geometric shape (e.g., A vs. B) were displayed. In premise-2, the second and third corners (e.g., B vs. C) were displayed. After integrating the two premises, participants were required to infer the spatial relationship between the first and the third corners (e.g., A and C). Finally, the participants were presented with a conclusion object, and they were required to judge whether the conclusion was true or false based on their inference. The event-related potential evoked by premise-2 revealed that (1) compared with 2D spatial reasoning, 3D reasoning elicited a smaller P3b component, and (2) in the right frontal areas, increased negativities were found in the 3D condition during the N400 and late negative components (LNC). These findings imply that higher brain activity in the right frontal brain regions were related with the integration and maintenance of spatial information in working memory for reasoning. Copyright © 2016 Elsevier Ltd. All rights reserved.
Psychophysiological correlates of aggression and violence: an integrative review.

PubMed

Patrick, Christopher J

2008-08-12

This paper reviews existing psychophysiological studies of aggression and violent behaviour including research employing autonomic, electrocortical and neuroimaging measures. Robust physiological correlates of persistent aggressive behaviour evident in this literature include low baseline heart rate, enhanced autonomic reactivity to stressful or aversive stimuli, enhanced EEG slow wave activity, reduced P300 brain potential response and indications from structural and functional neuroimaging studies of dysfunction in frontocortical and limbic brain regions that mediate emotional processing and regulation. The findings are interpreted within a conceptual framework that draws on two integrative models in the literature. The first is a recently developed hierarchical model of impulse control (externalizing) problems, in which various disinhibitory syndromes including aggressive and addictive behaviours of different kinds are seen as arising from common as well as distinctive aetiologic factors. This model represents an approach to organizing these various interrelated phenotypes and investigating their common and distinctive aetiologic substrates. The other is a neurobiological model that posits impairments in affective regulatory circuits in the brain as a key mechanism for impulsive aggressive behaviour. This model provides a perspective for integrating findings from studies employing different measures that have implicated varying brain structures and physiological systems in violent and aggressive behaviour.
Hyper- and viscoelastic modeling of needle and brain tissue interaction.

PubMed

Lehocky, Craig A; Yixing Shi; Riviere, Cameron N

2014-01-01

Deep needle insertion into brain is important for both diagnostic and therapeutic clinical interventions. We have developed an automated system for robotically steering flexible needles within the brain to improve targeting accuracy. In this work, we have developed a finite element needle-tissue interaction model that allows for the investigation of safe parameters for needle steering. The tissue model implemented contains both hyperelastic and viscoelastic properties to simulate the instantaneous and time-dependent responses of brain tissue. Several needle models were developed with varying parameters to study the effects of the parameters on tissue stress, strain and strain rate during needle insertion and rotation. The parameters varied include needle radius, bevel angle, bevel tip fillet radius, insertion speed, and rotation speed. The results will guide the design of safe needle tips and control systems for intracerebral needle steering.
MR Vascular Fingerprinting in Stroke and Brain Tumors Models

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

NASA Astrophysics Data System (ADS)

Moualhi, Wafa; Ezzeddine, Zagrouba

2015-02-01

The motivation of this work is to register a tumor brain magnetic resonance (MR) image with a normal brain atlas. A normal brain atlas is deformed in order to take account of the presence of a large space occupying tumor. The method use a priori model of tumor growth assuming that the tumor grows in a radial way from a starting point. First, an affine transformation is used in order to bring the patient image and the brain atlas in a global correspondence. Second, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed combining a method derived from optical flow principles and a model for tumor growth (MTG). Results show that an automatic segmentation method of brain structures in the presence of large deformation can be provided.
77 FR 13578 - Disability and Rehabilitation Research Project; Traumatic Brain Injury Model Systems Centers

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-07

... DEPARTMENT OF EDUCATION Disability and Rehabilitation Research Project; Traumatic Brain Injury... Rehabilitation Research Project--Traumatic Brain Injury Model Systems Centers. CFDA Number: 84.133A-5. SUMMARY... for Disability and Rehabilitation Research Projects (DRRPs) to serve as Traumatic Brain Injury Model...
Fused cerebral organoids model interactions between brain regions.

PubMed

Bagley, Joshua A; Reumann, Daniel; Bian, Shan; Lévi-Strauss, Julie; Knoblich, Juergen A

2017-07-01

Human brain development involves complex interactions between different regions, including long-distance neuronal migration or formation of major axonal tracts. Different brain regions can be cultured in vitro within 3D cerebral organoids, but the random arrangement of regional identities limits the reliable analysis of complex phenotypes. Here, we describe a coculture method combining brain regions of choice within one organoid tissue. By fusing organoids of dorsal and ventral forebrain identities, we generate a dorsal-ventral axis. Using fluorescent reporters, we demonstrate CXCR4-dependent GABAergic interneuron migration from ventral to dorsal forebrain and describe methodology for time-lapse imaging of human interneuron migration. Our results demonstrate that cerebral organoid fusion cultures can model complex interactions between different brain regions. Combined with reprogramming technology, fusions should offer researchers the possibility to analyze complex neurodevelopmental defects using cells from neurological disease patients and to test potential therapeutic compounds.
A new neuroinformatics approach to personalized medicine in neurology: The Virtual Brain

PubMed Central

Falcon, Maria I.; Jirsa, Viktor; Solodkin, Ana

2017-01-01

Purpose of review An exciting advance in the field of neuroimaging is the acquisition and processing of very large data sets (so called ‘big data’), permitting large-scale inferences that foster a greater understanding of brain function in health and disease. Yet what we are clearly lacking are quantitative integrative tools to translate this understanding to the individual level to lay the basis for personalized medicine. Recent findings Here we address this challenge through a review on how the relatively new field of neuroinformatics modeling has the capacity to track brain network function at different levels of inquiry, from microscopic to macroscopic and from the localized to the distributed. In this context, we introduce a new and unique multiscale approach, The Virtual Brain (TVB), that effectively models individualized brain activity, linking large-scale (macroscopic) brain dynamics with biophysical parameters at the microscopic level. We also show how TVB modeling provides unique biological interpretable data in epilepsy and stroke. Summary These results establish the basis for a deliberate integration of computational biology and neuroscience into clinical approaches for elucidating cellular mechanisms of disease. In the future, this can provide the means to create a collection of disease-specific models that can be applied on the individual level to personalize therapeutic interventions. Video abstract http://links.lww.com/CONR/A41 PMID:27224088
A putative model of overeating and obesity based on brain-derived neurotrophic factor: direct and indirect effects.

PubMed

Ooi, Cara L; Kennedy, James L; Levitan, Robert D

2012-08-01

Increased food intake is a major contributor to the obesity epidemic in all age groups. Elucidating brain systems that drive overeating and that might serve as targets for novel prevention and treatment interventions is thus a high priority for obesity research. The authors consider 2 major pathways by which decreased activity of brain-derived neurotrophic factor (BDNF) may confer vulnerability to overeating and weight gain in an obesogenic environment. The first "direct" pathway focuses on the specific role of BDNF as a mediator of food intake control at brain areas rich in BDNF receptors, including the hypothalamus and hindbrain. It is proposed that low BDNF activity limited to this direct pathway may best explain overeating and obesity outside the context of major neuropsychiatric disturbance. A second "indirect" pathway considers the broad neurotrophic effects of BDNF on key monoamine systems that mediate mood dysregulation, impulsivity, and executive dysfunction as well as feeding behavior per se. Disruption in this pathway may best explain overeating and obesity in the context of various neuropsychiatric disturbances including mood disorders, attention-deficit disorder, and/or binge eating disorders. An integrative model that considers these potential roles of BDNF in promoting obesity is presented. The implications of this model for the early prevention and treatment of obesity are also considered.
Integration of sparse electrophysiological measurements with preoperative MRI using 3D surface estimation in deep brain stimulation surgery

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

PubMed

Chen, Yu-Jen; Liu, Chih-Min; Hsu, Yung-Chin; Lo, Yu-Chun; Hwang, Tzung-Jeng; Hwu, Hai-Gwo; Lin, Yi-Tin; Tseng, Wen-Yih Isaac

2018-01-01

A schizophrenia diagnosis relies on characteristic symptoms identified by trained physicians, and is thus prone to subjectivity. This study developed a procedure for the individualized prediction of schizophrenia based on whole-brain patterns of altered white matter tract integrity. The study comprised training (108 patients and 144 controls) and testing (60 patients and 60 controls) groups. Male and female participants were comparable in each group and were analyzed separately. All participants underwent diffusion spectrum imaging of the head, and the data were analyzed using the tract-based automatic analysis method to generate a standardized two-dimensional array of white matter tract integrity, called the connectogram. Unique patterns in the connectogram that most accurately identified schizophrenia were systematically reviewed in the training group. Then, the diagnostic performance of the patterns was individually verified in the testing group by using receiver-operating characteristic curve analysis. The performance was high in men (accuracy = 0.85) and satisfactory in women (accuracy = 0.75). In men, the pattern was located in discrete fiber tracts, as has been consistently reported in the literature; by contrast, the pattern was widespread over all tracts in women. These distinct patterns suggest that there is a higher variability in the microstructural alterations in female patients than in male patients. The individualized prediction of schizophrenia is feasible based on the different whole-brain patterns of tract integrity. The optimal masks and their corresponding regions in the fiber tracts could serve as potential imaging biomarkers for schizophrenia. Hum Brain Mapp 39:575-587, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

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

Preusser, T.

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

PubMed

Zhang, Chenyu; Lowery, Frank J; Yu, Dihua

2017-02-08

Metastasis, the spread and growth of malignant cells at secondary sites within a patient's body, accounts for > 90% of cancer-related mortality. Recently, impressive advances in novel therapies have dramatically prolonged survival and improved quality of life for many cancer patients. Sadly, incidence of brain metastatic recurrences is fast rising, and all current therapies are merely palliative. Hence, good experimental animal models are urgently needed to facilitate in-depth studies of the disease biology and to assess novel therapeutic regimens for preclinical evaluation. However, the standard in vivo metastasis assay via tail vein injection of cancer cells produces predominantly lung metastatic lesions; animals usually succumb to the lung tumor burden before any meaningful outgrowth of brain metastasis. Intracardiac injection of tumor cells produces metastatic lesions to multiple organ sites including the brain; however, the variability of tumor growth produced with this model is large, dampening its utility in evaluating therapeutic efficacy. To generate reliable and consistent animal models for brain metastasis study, here we describe a procedure for producing experimental brain metastasis in the house mouse (Mus musculus) via intracarotid injection of tumor cells. This approach allows one to produce large number of brain metastasis-bearing mice with similar growth and mortality characteristics, thus facilitating research efforts to study basic biological mechanisms and to assess novel therapeutic agents.
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
Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

PubMed Central

2016-01-01

We have developed an open software platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution and testing on multiple Graphics Processing Units (GPUs). Neurokernel provides a programming model that capitalizes upon the structural organization of the fly brain into a fixed number of functional modules to distinguish between these modules’ local information processing capabilities and the connectivity patterns that link them. By defining mandatory communication interfaces that specify how data is transmitted between models of each of these modules regardless of their internal design, Neurokernel explicitly enables multiple researchers to collaboratively model the fruit fly’s entire brain by integration of their independently developed models of its constituent processing units. We demonstrate the power of Neurokernel’s model integration by combining independently developed models of the retina and lamina neuropils in the fly’s visual system and by demonstrating their neuroinformation processing capability. We also illustrate Neurokernel’s ability to take advantage of direct GPU-to-GPU data transfers with benchmarks that demonstrate scaling of Neurokernel’s communication performance both over the number of interface ports exposed by an emulation’s constituent modules and the total number of modules comprised by an emulation. PMID:26751378
Dosha brain-types: A neural model of individual differences.

PubMed

Travis, Frederick T; Wallace, Robert Keith

2015-01-01

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

NASA Astrophysics Data System (ADS)

Wakamatsu, Hidetoshi; Gaohua, Lu

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

NASA Astrophysics Data System (ADS)

Crowther, L. J.; Hadimani, R. L.; Kanthasamy, A. G.; Jiles, D. C.

2014-05-01

Transcranial magnetic stimulation (TMS) offers the possibility of non-invasive treatment of brain disorders in humans. Studies on animals can allow rapid progress of the research including exploring a variety of different treatment conditions. Numerical calculations using animal models are needed to help design suitable TMS coils for use in animal experiments, in particular, to estimate the electric field induced in animal brains. In this paper, we have implemented a high-resolution anatomical MRI-derived mouse model consisting of 50 tissue types to accurately calculate induced electric field in the mouse brain. Magnetic field measurements have been performed on the surface of the coil and compared with the calculations in order to validate the calculated magnetic and induced electric fields in the brain. Results show how the induced electric field is distributed in a mouse brain and allow investigation of how this could be improved for TMS studies using mice. The findings have important implications in further preclinical development of TMS for treatment of human diseases.
Transdiagnostic Associations Between Functional Brain Network Integrity and Cognition.

PubMed

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

2017-06-01

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

PubMed

Al-Shehri, Abdulghani; Favretto, Marco E; Ioannou, Panayiotis V; Romero, Ignacio A; Couraud, Pierre-Olivier; Weksler, Babette Barbash; Parker, Terry L; Kallinteri, Paraskevi

2015-03-01

Owing to restricted access of pharmacological agents into the brain due to blood brain barrier (BBB) there is a need: 1. to develop a more representative 3-D-co-culture model of tumor-BBB interaction to investigate drug and nanoparticle transport into the brain for diagnostic and therapeutic evaluation. 2. to address the lack of new alternative methods to animal testing according to replacement-reduction-refinement principles. In this work, in vitro BBB-medulloblastoma 3-D-co-culture models were established using immortalized human primary brain endothelial cells (hCMEC/D3). hCMEC/D3 cells were cultured in presence and in absence of two human medulloblastoma cell lines on Transwell membranes. In vitro models were characterized for BBB formation, zonula occludens-1 expression and permeability to dextran. Transferrin receptors (Tfr) expressed on hCMEC/D3 were exploited to facilitate arsonoliposome (ARL) permeability through the BBB to the tumor by covalently attaching an antibody specific to human Tfr. The effect of anticancer ARLs on hCMEC/D3 was assessed. In vitro BBB and BBB-tumor co-culture models were established successfully. BBB permeability was affected by the presence of tumor aggregates as suggested by increased permeability of ARLs. There was a 6-fold and 8-fold increase in anti-Tfr-ARL uptake into VC312R and BBB-DAOY co-culture models, respectively, compared to plain ARLs. The three-dimensional models might be appropriate models to study the transport of various drugs and nanocarriers (liposomes and immunoarsonoliposomes) through the healthy and diseased BBB. The immunoarsonoliposomes can be potentially used as anticancer agents due to good tolerance of the in vitro BBB model to their toxic effect.
Adolescent brain development in normality and psychopathology

PubMed Central

LUCIANA, MONICA

2014-01-01

Since this journal’s inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical–cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology–context interactions, represent the field’s most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled. PMID:24342843
Adolescent brain development in normality and psychopathology.

PubMed

Luciana, Monica

2013-11-01

Since this journal's inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical-cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology-context interactions, represent the field's most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled.
Enabling model customization and integration

NASA Astrophysics Data System (ADS)

Park, Minho; Fishwick, Paul A.

2003-09-01

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

ERIC Educational Resources Information Center

Inocian, Reynaldo B.

2015-01-01

This study analyzes teaching strategies among the eight books in Principles and Methods of Teaching recommended for use in the College of Teacher Education in the Philippines. It seeks to answer the following objectives: (1) identify the most commonly used teaching strategies congruent with the integrated arts-based teaching (IAT) and (2) design…
Assessment of Cognitive Function in the Water Maze Task: Maximizing Data Collection and Analysis in Animal Models of Brain Injury.

PubMed

Whiting, Mark D; Kokiko-Cochran, Olga N

2016-01-01

Animal models play a critical role in understanding the biomechanical, pathophysiological, and behavioral consequences of traumatic brain injury (TBI). In preclinical studies, cognitive impairment induced by TBI is often assessed using the Morris water maze (MWM). Frequently described as a hippocampally dependent spatial navigation task, the MWM is a highly integrative behavioral task that requires intact functioning in numerous brain regions and involves an interdependent set of mnemonic and non-mnemonic processes. In this chapter, we review the special considerations involved in using the MWM in animal models of TBI, with an emphasis on maximizing the degree of information extracted from performance data. We include a theoretical framework for examining deficits in discrete stages of cognitive function and offer suggestions for how to make inferences regarding the specific nature of TBI-induced cognitive impairment. The ultimate goal is more precise modeling of the animal equivalents of the cognitive deficits seen in human TBI.
Integrative Understanding of Emergent Brain Properties, Quantum Brain Hypotheses, and Connectome Alterations in Dementia are Key Challenges to Conquer Alzheimer's Disease.

PubMed

Kuljiš, Rodrigo O

2010-01-01

The biological substrate for cognition remains a challenge as much as defining this function of living beings. Here, we examine some of the difficulties to understand normal and disordered cognition in humans. We use aspects of Alzheimer's disease and related disorders to illustrate how the wealth of information at many conceptually separate, even intellectually decoupled, physical scales - in particular at the Molecular Neuroscience versus Systems Neuroscience/Neuropsychology levels - presents a challenge in terms of true interdisciplinary integration towards a coherent understanding. These unresolved dilemmas include critically the as yet untested quantum brain hypothesis, and the embryonic attempts to develop and define the so-called connectome in humans and in non-human models of disease. To mitigate these challenges, we propose a scheme incorporating the vast array of scales of the space and time (space-time) manifold from at least the subatomic through cognitive-behavioral dimensions of inquiry, to achieve a new understanding of both normal and disordered cognition, that is essential for a new era of progress in the Generative Sciences and its application to translational efforts for disease prevention and treatment.
Integrated analytical techniques with high sensitivity for studying brain translocation and potential impairment induced by intranasally instilled copper nanoparticles.

PubMed

Bai, Ru; Zhang, Lili; Liu, Ying; Li, Bai; Wang, Liming; Wang, Peng; Autrup, Herman; Beer, Christiane; Chen, Chunying

2014-04-07

Health impacts of inhalation exposure to engineered nanomaterials have attracted increasing attention. In this paper, integrated analytical techniques with high sensitivity were used to study the brain translocation and potential impairment induced by intranasally instilled copper nanoparticles (CuNPs). Mice were exposed to CuNPs in three doses (1, 10, 40 mg/kg bw). The body weight of mice decreased significantly in the 10 and 40 mg/kg group (p<0.05) but recovered slightly within exposure duration. Inductively coupled plasma mass spectrometry (ICP-MS) analysis showed that CuNPs could enter the brain. Altered distribution of some important metal elements was observed by synchrotron radiation X-ray fluorescence (SRXRF). H&E staining and immunohistochemical analysis showed that CuNPs produced damages to nerve cells and astrocyte might be the one of the potential targets of CuNPs. The changes of neurotransmitter levels in different brain regions demonstrate that the dysfunction occurred in exposed groups. These data indicated that CuNPs could enter the brain after nasal inhalation and induced damages to the central nervous system (CNS). Integration of effective analytical techniques for systematic investigations is a promising direction to better understand the biological activities of nanomaterials. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
integrated Earth System Model

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

Jones, Andew; Di Vittorio, Alan; Collins, William

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human-Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human-Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems.« less
Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

PubMed

Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

2013-10-01

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread.

PubMed

Swan, Amanda; Hillen, Thomas; Bowman, John C; Murtha, Albert D

2018-05-01

Gliomas are primary brain tumours arising from the glial cells of the nervous system. The diffuse nature of spread, coupled with proximity to critical brain structures, makes treatment a challenge. Pathological analysis confirms that the extent of glioma spread exceeds the extent of the grossly visible mass, seen on conventional magnetic resonance imaging (MRI) scans. Gliomas show faster spread along white matter tracts than in grey matter, leading to irregular patterns of spread. We propose a mathematical model based on Diffusion Tensor Imaging, a new MRI imaging technique that offers a methodology to delineate the major white matter tracts in the brain. We apply the anisotropic diffusion model of Painter and Hillen (J Thoer Biol 323:25-39, 2013) to data from 10 patients with gliomas. Moreover, we compare the anisotropic model to the state-of-the-art Proliferation-Infiltration (PI) model of Swanson et al. (Cell Prolif 33:317-329, 2000). We find that the anisotropic model offers a slight improvement over the standard PI model. For tumours with low anisotropy, the predictions of the two models are virtually identical, but for patients whose tumours show higher anisotropy, the results differ. We also suggest using the data from the contralateral hemisphere to further improve the model fit. Finally, we discuss the potential use of this model in clinical treatment planning.
Community-integrated brain injury rehabilitation: Treatment models and challenges for civilian, military, and veteran populations.

PubMed

Trudel, Tina M; Nidiffer, F Don; Barth, Jeffrey T

2007-01-01

Traumatic brain injury (TBI) is a major health problem in civilian, military, and veteran populations. Individuals experiencing moderate to severe TBI require a continuum of care involving acute hospitalization and postacute rehabilitation, including community reintegration and, one would hope, a return home to function as a productive member of the community. In the military, the goal is to help individuals with TBI return to active duty or make an optimal return to civilian life if the extent of their injuries necessitates a "medical board" discharge. Whether civilian, military, or veteran with TBI, individuals who move beyond the need to live in a facility must be reintegrated back into the community. This article discusses four treatment models for community reintegration, reviews treatment standardization and outcome issues, and describes a manualized rehabilitation pilot program designed to provide community reintegration and return to duty/work for civilians, veterans, and military personnel with TBI.
Open source integrated modeling environment Delta Shell

NASA Astrophysics Data System (ADS)

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

2012-04-01

In the last decade, integrated modelling has become a very popular topic in environmental modelling since it helps solving problems, which is difficult to model using a single model. However, managing complexity of integrated models and minimizing time required for their setup remains a challenging task. The integrated modelling environment Delta Shell simplifies this task. The software components of Delta Shell are easy to reuse separately from each other as well as a part of integrated environment that can run in a command-line or a graphical user interface mode. The most components of the Delta Shell are developed using C# programming language and include libraries used to define, save and visualize various scientific data structures as well as coupled model configurations. Here we present two examples showing how Delta Shell simplifies process of setting up integrated models from the end user and developer perspectives. The first example shows coupling of a rainfall-runoff, a river flow and a run-time control models. The second example shows how coastal morphological database integrates with the coastal morphological model (XBeach) and a custom nourishment designer. Delta Shell is also available as open-source software released under LGPL license and accessible via http://oss.deltares.nl.
HMGB1 a-Box Reverses Brain Edema and Deterioration of Neurological Function in a Traumatic Brain Injury Mouse Model.

PubMed

Yang, Lijun; Wang, Feng; Yang, Liang; Yuan, Yunchao; Chen, Yan; Zhang, Gengshen; Fan, Zhenzeng

2018-01-01

Traumatic brain injury (TBI) is a complex neurological injury in young adults lacking effective treatment. Emerging evidences suggest that inflammation contributes to the secondary brain injury following TBI, including breakdown of the blood brain barrier (BBB), subsequent edema and neurological deterioration. High mobility group box-1 (HMGB1) has been identified as a key cytokine in the inflammation reaction following TBI. Here, we investigated the therapeutic efficacy of HMGB1 A-box fragment, an antagonist competing with full-length HMGB1 for receptor binding, against TBI. TBI was induced by controlled cortical impact (CCI) in adult male mice. HMGB1 A-box fragment was given intravenously at 2 mg/kg/day for 3 days after CCI. HMGB1 A-box-treated CCI mice were compared with saline-treated CCI mice and sham mice in terms of BBB disruption evaluated by Evan's blue extravasation, brain edema by brain water content, cell death by propidium iodide staining, inflammation by Western blot and ELISA assay for cytokine productions, as well as neurological functions by the modified Neurological Severity Score, wire grip and beam walking tests. HMGB1 A-box reversed brain damages in the mice following TBI. It significantly reduced brain edema by protecting integrity of the BBB, ameliorated cell degeneration, and decreased expression of pro-inflammatory cytokines released in injured brain after TBI. These cellular and molecular effects were accompanied by improved behavioral performance in TBI mice. Notably, HMGB1 A-box blocked IL-1β-induced HMGB1 release, and preferentially attenuated TLR4, Myd88 and P65 in astrocyte cultures. Our data suggest that HMGB1 is involved in CCI-induced TBI, which can be inhibited by HMGB1 A-box fragment. Therefore, HMGB1 A-box fragment may have therapeutic potential for the secondary brain damages in TBI. © 2018 The Author(s). Published by S. Karger AG, Basel.
MR Vascular Fingerprinting in Stroke and Brain Tumors Models

PubMed Central

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

2016-01-01

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases. PMID:27883015
Dynamic Bayesian network modeling for longitudinal brain morphometry

PubMed Central

Chen, Rong; Resnick, Susan M; Davatzikos, Christos; Herskovits, Edward H

2011-01-01

Identifying interactions among brain regions from structural magnetic-resonance images presents one of the major challenges in computational neuroanatomy. We propose a Bayesian data-mining approach to the detection of longitudinal morphological changes in the human brain. Our method uses a dynamic Bayesian network to represent evolving inter-regional dependencies. The major advantage of dynamic Bayesian network modeling is that it can represent complicated interactions among temporal processes. We validated our approach by analyzing a simulated atrophy study, and found that this approach requires only a small number of samples to detect the ground-truth temporal model. We further applied dynamic Bayesian network modeling to a longitudinal study of normal aging and mild cognitive impairment — the Baltimore Longitudinal Study of Aging. We found that interactions among regional volume-change rates for the mild cognitive impairment group are different from those for the normal-aging group. PMID:21963916
I-123 iomazenil single photon emission computed tomography for detecting loss of neuronal integrity in patients with traumatic brain injury.

PubMed

Abiko, Kagari; Ikoma, Katsunori; Shiga, Tohru; Katoh, Chietsugu; Hirata, Kenji; Kuge, Yuji; Kobayashi, Kentaro; Tamaki, Nagara

2017-12-01

Traumatic brain injury (TBI) causes brain dysfunction in many patients. Using C-11 flumazenil (FMZ) positron emission tomography (PET), we have detected and reported the loss of neuronal integrity, leading to brain dysfunction in TBI patients. Similarly to FMZ PET, I-123 iomazenil (IMZ) single photon emission computed tomography (SPECT) is widely used to determine the distribution of the benzodiazepine receptor (BZR) in the brain cortex. The purpose of this study is to examine whether IMZ SPECT is as useful as FMZ PET for evaluating the loss of neuronal integrity in TBI patients. The subjects of this study were seven patients who suffered from neurobehavioral disability. They underwent IMZ SPECT and FMZ PET. Nondisplaceable binding potential (BP ND ) was calculated from FMZ PET images. The uptake of IMZ was evaluated on the basis of lesion-to-pons ratio (LPR). The locations of low uptake levels were visually evaluated both in IMZ SPECT and FMZ PET images. We compared FMZ BP ND and (LPR-1) of IMZ SPECT. In the visual assessment, FMZ BP ND decreased in 11 regions. In IMZ SPECT, low uptake levels were observed in eight of the 11 regions. The rate of concordance between FMZ PET and IMZ SPECT was 72.7%. The mean values IMZ (LPR-1) (1.95 ± 1.01) was significantly lower than that of FMZ BP ND (2.95 ± 0.80 mL/mL). There was good correlation between FMZ BP ND and IMZ (LPR-1) (r = 0.80). IMZ SPECT findings were almost the same as FMZ PET findings in TBI patients. The results indicated that IMZ SPECT is useful for evaluating the loss of neuronal integrity. Because IMZ SPECT can be performed in various facilities, IMZ SPECT may become widely adopted for evaluating the loss of neuronal integrity.
Modeling of light distribution in the brain for topographical imaging

NASA Astrophysics Data System (ADS)

Okada, Eiji; Hayashi, Toshiyuki; Kawaguchi, Hiroshi

2004-07-01

Multi-channel optical imaging system can obtain a topographical distribution of the activated region in the brain cortex by a simple mapping algorithm. Near-infrared light is strongly scattered in the head and the volume of tissue that contributes to the change in the optical signal detected with source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. We report theoretical investigations on the spatial resolution of the topographic imaging of the brain activity. The head model for the theoretical study consists of five layers that imitate the scalp, skull, subarachnoid space, gray matter and white matter. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The source-detector pairs are one dimensionally arranged on the surface of the model and the distance between the adjoining source-detector pairs are varied from 4 mm to 32 mm. The change in detected intensity caused by the absorption change is obtained by Monte Carlo simulation. The position of absorption change is reconstructed by the conventional mapping algorithm and the reconstruction algorithm using the spatial sensitivity profiles. We discuss the effective interval between the source-detector pairs and the choice of reconstruction algorithms to improve the topographic images of brain activity.
Probing the extracellular diffusion of antibodies in brain using in vivo integrative optical imaging and ex vivo fluorescence imaging.

PubMed

Wolak, Daniel J; Pizzo, Michelle E; Thorne, Robert G

2015-01-10

Antibody-based therapeutics exhibit great promise in the treatment of central nervous system (CNS) disorders given their unique customizable properties. Although several clinical trials have evaluated therapeutic antibodies for treatment of CNS disorders, success to date has likely been limited in part due to complex issues associated with antibody delivery to the brain and antibody distribution within the CNS compartment. Major obstacles to effective CNS delivery of full length immunoglobulin G (IgG) antibodies include transport across the blood-brain and blood-cerebrospinal fluid barriers. IgG diffusion within brain extracellular space (ECS) may also play a role in limiting central antibody distribution; however, IgG transport in brain ECS has not yet been explored using established in vivo methods. Here, we used real-time integrative optical imaging to measure the diffusion properties of fluorescently labeled, non-targeted IgG after pressure injection in both free solution and in adult rat neocortex in vivo, revealing IgG diffusion in free medium is ~10-fold greater than in brain ECS. The pronounced hindered diffusion of IgG in brain ECS is likely due to a number of general factors associated with the brain microenvironment (e.g. ECS volume fraction and geometry/width) but also molecule-specific factors such as IgG size, shape, charge and specific binding interactions with ECS components. Co-injection of labeled IgG with an excess of unlabeled Fc fragment yielded a small yet significant increase in the IgG effective diffusion coefficient in brain, suggesting that binding between the IgG Fc domain and endogenous Fc-specific receptors may contribute to the hindered mobility of IgG in brain ECS. Importantly, local IgG diffusion coefficients from integrative optical imaging were similar to those obtained from ex vivo fluorescence imaging of transport gradients across the pial brain surface following controlled intracisternal infusions in anesthetized animals. Taken
Probing the extracellular diffusion of antibodies in brain using in vivo integrative optical imaging and ex vivo fluorescence imaging

PubMed Central

Wolak, Daniel J.; Pizzo, Michelle E.; Thorne, Robert G.

2014-01-01

Antibody-based therapeutics exhibit great promise in the treatment of central nervous system (CNS) disorders given their unique customizable properties. Although several clinical trials have evaluated therapeutic antibodies for treatment of CNS disorders, success to date has likely been limited in part due to complex issues associated with antibody delivery to the brain and antibody distribution within the CNS compartment. Major obstacles to effective CNS delivery of full length immunoglobulin G (IgG) antibodies include transport across the blood-brain and blood-cerebrospinal fluid barriers. IgG diffusion within brain extracellular space (ECS) may also play a role in limiting central antibody distribution; however, IgG transport in brain ECS has not yet been explored using established in vivo methods. Here, we used real-time integrative optical imaging to measure the diffusion properties of fluorescently labeled, non-targeted IgG after pressure injection in both free solution and in adult rat neocortex in vivo, revealing IgG diffusion in free medium is ~10-fold greater than in brain ECS. The pronounced hindered diffusion of IgG in brain ECS is likely due to a number of general factors associated with the brain microenvironment (e.g. ECS volume fraction and geometry/width) but also molecule-specific factors such as IgG size, shape, charge and specific binding interactions with ECS components. Co-injection of labeled IgG with an excess of unlabeled Fc fragment yielded a small yet significant increase in the IgG effective diffusion coefficient in brain, suggesting that binding between the IgG Fc domain and endogenous Fc-specific receptors may contribute to the hindered mobility of IgG in brain ECS. Importantly, local IgG diffusion coefficients from integrative optical imaging were similar to those obtained from ex vivo fluorescence imaging of transport gradients across the pial brain surface following controlled intracisternal infusions in anesthetized animals. Taken
TVB-EduPack—An Interactive Learning and Scripting Platform for The Virtual Brain

PubMed Central

Matzke, Henrik; Schirner, Michael; Vollbrecht, Daniel; Rothmeier, Simon; Llarena, Adalberto; Rojas, Raúl; Triebkorn, Paul; Domide, Lia; Mersmann, Jochen; Solodkin, Ana; Jirsa, Viktor K.; McIntosh, Anthony Randal; Ritter, Petra

2015-01-01

The Virtual Brain (TVB; thevirtualbrain.org) is a neuroinformatics platform for full brain network simulation based on individual anatomical connectivity data. The framework addresses clinical and neuroscientific questions by simulating multi-scale neural dynamics that range from local population activity to large-scale brain function and related macroscopic signals like electroencephalography and functional magnetic resonance imaging. TVB is equipped with a graphical and a command-line interface to create models that capture the characteristic biological variability to predict the brain activity of individual subjects. To enable researchers from various backgrounds a quick start into TVB and brain network modeling in general, we developed an educational module: TVB-EduPack. EduPack offers two educational functionalities that seamlessly integrate into TVB's graphical user interface (GUI): (i) interactive tutorials introduce GUI elements, guide through the basic mechanics of software usage and develop complex use-case scenarios; animations, videos and textual descriptions transport essential principles of computational neuroscience and brain modeling; (ii) an automatic script generator records model parameters and produces input files for TVB's Python programming interface; thereby, simulation configurations can be exported as scripts that allow flexible customization of the modeling process and self-defined batch- and post-processing applications while benefitting from the full power of the Python language and its toolboxes. This article covers the implementation of TVB-EduPack and its integration into TVB architecture. Like TVB, EduPack is an open source community project that lives from the participation and contribution of its users. TVB-EduPack can be obtained as part of TVB from thevirtualbrain.org. PMID:26635597
Integrating brain, behavior, and phylogeny to understand the evolution of sensory systems in birds

PubMed Central

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

2015-01-01

The comparative anatomy of sensory systems has played a major role in developing theories and principles central to evolutionary neuroscience. This includes the central tenet of many comparative studies, the principle of proper mass, which states that the size of a neural structure reflects its processing capacity. The size of structures within the sensory system is not, however, the only salient variable in sensory evolution. Further, the evolution of the brain and behavior are intimately tied to phylogenetic history, requiring studies to integrate neuroanatomy with behavior and phylogeny to gain a more holistic view of brain evolution. Birds have proven to be a useful group for these studies because of widespread interest in their phylogenetic relationships and a wealth of information on the functional organization of most of their sensory pathways. In this review, we examine the principle of proper mass in relation differences in the sensory capabilities among birds. We discuss how neuroanatomy, behavior, and phylogeny can be integrated to understand the evolution of sensory systems in birds providing evidence from visual, auditory, and somatosensory systems. We also consider the concept of a “trade-off,” whereby one sensory system (or subpathway within a sensory system), may be expanded in size, at the expense of others, which are reduced in size. PMID:26321905
Move me, astonish me… delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

PubMed

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

2017-07-01

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

PubMed

Van Elderen, Saskia S G C; Zhang, Qian; Sigurdsson, Sigudur; Haight, Thaddeus J; Lopez, Oscar; Eiriksdottir, Gudny; Jonsson, Palmi; de Jong, Laura; Harris, Tamara B; Garcia, Melissa; Gudnason, Vilmundar; van Buchem, Mark A; Launer, Lenore J

2016-01-01

Total brain volume is an integrated measure of health and may be an independent indicator of mortality risk independent of any one clinical or subclinical disease state. We investigate the association of brain volume to total and cause-specific mortality in a large nondemented stroke-free community-based cohort. The analysis includes 3,543 men and women (born 1907-1935) participating in the Age, Gene, Environment Susceptibility-Reykjavik Study. Participants with a known brain-related high risk for mortality (cognitive impairment or stroke) were excluded from these analyses. Quantitative estimates of total brain volume, white matter, white matter lesions, total gray matter (GM; cortical GM and subcortical GM separately), and focal cerebral vascular disease were generated from brain magnetic resonance imaging. Brain atrophy was expressed as brain tissue volume divided by total intracranial volume, yielding a percentage. Mean follow-up duration was 7.2 (0-10) years, with 647 deaths. Cox regression was used to analyze the association of mortality to brain atrophy, adjusting for demographics, cardiovascular risk factors, and cerebral vascular disease. Reduced risk of mortality was significantly associated with higher total brain volume (hazard ratio, 95% confidence interval = 0.71, 0.65-0.78), white matter (0.85, 0.78-0.93), total GM (0.74, 0.68-0.81), and cortical GM (0.78, 0.70-0.87). Overall, the associations were similar for cardiovascular and noncardiovascular-related deaths. Independent of multiple risk factors and cerebral vascular damage, global brain volume predicts mortality in a large nondemented stroke-free community-dwelling older cohort. Total brain volume may be an integrated measure reflecting a range of health and with further investigation could be a useful clinical tool when assessing risk for mortality. Published by Oxford University Press on behalf of the Gerontological Society of America 2014.
Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

PubMed Central

Robinson, Jennifer; Calhoun, Vince

2018-01-01

Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339
Brain systems underlying susceptibility to helplessness and depression.

PubMed

Shumake, J; Gonzalez-Lima, F

2003-09-01

There has been a relative lack of research into the neurobiological predispositions that confer vulnerability to depression. This article reviews functional brain mappings from a genetic animal model, the congenitally helpless rat, which is predisposed to develop learned helplessness. Neurometabolic findings from this model are integrated with the neuroscientific literature from other animal models of depression as well as depressed humans. Changes in four major brain systems are suggested to underlie susceptibility to helplessness and possibly depression: (a) an unbalanced prefrontal-cingulate cortical system, (b) a dissociated hypothalamic-pituitary-adrenal axis, (c) a dissociated septal-hippocampal system, and (d) a hypoactive brain reward system, as exemplified by a hypermetabolic habenula-interpeduncular nucleus pathway and a hypometabolic ventral tegmental area-striatum pathway. Functional interconnections and causal relationships among these systems are considered and further experiments are suggested, with theoretical attention to how an abnormality in any one system could affect the others.
Differences in amyloid-β clearance across mouse and human blood-brain barrier models: kinetic analysis and mechanistic modeling.

PubMed

Qosa, Hisham; Abuasal, Bilal S; Romero, Ignacio A; Weksler, Babette; Couraud, Pierre-Oliver; Keller, Jeffrey N; Kaddoumi, Amal

2014-04-01

Alzheimer's disease (AD) has a characteristic hallmark of amyloid-β (Aβ) accumulation in the brain. This accumulation of Aβ has been related to its faulty cerebral clearance. Indeed, preclinical studies that used mice to investigate Aβ clearance showed that efflux across blood-brain barrier (BBB) and brain degradation mediate efficient Aβ clearance. However, the contribution of each process to Aβ clearance remains unclear. Moreover, it is still uncertain how species differences between mouse and human could affect Aβ clearance. Here, a modified form of the brain efflux index method was used to estimate the contribution of BBB and brain degradation to Aβ clearance from the brain of wild type mice. We estimated that 62% of intracerebrally injected (125)I-Aβ40 is cleared across BBB while 38% is cleared by brain degradation. Furthermore, in vitro and in silico studies were performed to compare Aβ clearance between mouse and human BBB models. Kinetic studies for Aβ40 disposition in bEnd3 and hCMEC/D3 cells, representative in vitro mouse and human BBB models, respectively, demonstrated 30-fold higher rate of (125)I-Aβ40 uptake and 15-fold higher rate of degradation by bEnd3 compared to hCMEC/D3 cells. Expression studies showed both cells to express different levels of P-glycoprotein and RAGE, while LRP1 levels were comparable. Finally, we established a mechanistic model, which could successfully predict cellular levels of (125)I-Aβ40 and the rate of each process. Established mechanistic model suggested significantly higher rates of Aβ uptake and degradation in bEnd3 cells as rationale for the observed differences in (125)I-Aβ40 disposition between mouse and human BBB models. In conclusion, current study demonstrates the important role of BBB in the clearance of Aβ from the brain. Moreover, it provides insight into the differences between mouse and human BBB with regards to Aβ clearance and offer, for the first time, a mathematical model that describes
Differences in amyloid-β clearance across mouse and human blood-brain barrier models: Kinetic analysis and mechanistic modeling

PubMed Central

Qosa, Hisham; Abuasal, Bilal S.; Romero, Ignacio A.; Weksler, Babette; Couraud, Pierre-Oliver; Keller, Jeffrey N.; Kaddoumi, Amal

2014-01-01

Alzheimer’s disease (AD) has a characteristic hallmark of amyloid-β (Aβ) accumulation in the brain. This accumulation of Aβ has been related to its faulty cerebral clearance. Indeed, preclinical studies that used mice to investigate Aβ clearance showed that efflux across blood-brain barrier (BBB) and brain degradation mediate efficient Aβ clearance. However, the contribution of each process to Aβ clearance remains unclear. Moreover, it is still uncertain how species differences between mouse and human could affect Aβ clearance. Here, a modified form of the brain efflux index method was used to estimate the contribution of BBB and brain degradation to Aβ clearance from the brain of wild type mice. We estimated that 62% of intracerebrally injected 125I-Aβ40 is cleared across BBB while 38% is cleared by brain degradation. Furthermore, in vitro and in silico studies were performed to compare Aβ clearance between mouse and human BBB models. Kinetic studies for Aβ40 disposition in bEnd3 and hCMEC/D3 cells, representative in vitro mouse and human BBB models, respectively, demonstrated 30-fold higher rate of 125I-Aβ40 uptake and 15-fold higher rate of degradation by bEnd3 compared to hCMEC/D3 cells. Expression studies showed both cells to express different levels of P-glycoprotein and RAGE, while LRP1 levels were comparable. Finally, we established a mechanistic model, which could successfully predict cellular levels of 125I-Aβ40 and the rate of each process. Established mechanistic model suggested significantly higher rates of Aβ uptake and degradation in bEnd3 cells as rationale for the observed differences in 125I-Aβ40 disposition between mouse and human BBB models. In conclusion, current study demonstrates the important role of BBB in the clearance of Aβ from the brain. Moreover, it provides insight into the differences between mouse and human BBB with regards to Aβ clearance and offer, for the first time, a mathematical model that describes A�
An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites.

PubMed

Jadi, Monika P; Behabadi, Bardia F; Poleg-Polsky, Alon; Schiller, Jackie; Mel, Bartlett W

2014-05-01

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based "technology" that underlies the brain's remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or "neuron," yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees.

Hierarchical random cellular neural networks for system-level brain-like signal processing.

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.
Iron overload prevents oxidative damage to rat brain after chlorpromazine administration.

PubMed

Piloni, Natacha E; Caro, Andres A; Puntarulo, Susana

2018-05-15

The hypothesis tested is that Fe administration leads to a response in rat brain modulating the effects of later oxidative challenges such as chlorpromazine (CPZ) administration. Either a single dose (acute Fe overload) or 6 doses every second day (sub-chronic Fe overload) of 500 or 50 mg Fe-dextran/kg, respectively, were injected intraperitoneally (ip) to rats. A single dose of 10 mg CPZ/kg was injected ip 8 h after Fe treatment. DNA integrity was evaluated by quantitative PCR, lipid radical (LR · ) generation rate by electron paramagnetic resonance (EPR), and catalase (CAT) activity by UV spectrophotometry in isolated brains. The maximum increase in total Fe brain was detected after 6 or 2 h in the acute and sub-chronic Fe overload model, respectively. Mitochondrial and nuclear DNA integrity decreased after acute Fe overload at the time of maximal Fe content; the decrease in DNA integrity was lower after sub-chronic than after acute Fe overload. CPZ administration increased LR · generation rate in control rat brain after 1 and 2 h; however, CPZ administration after acute or sub-chronic Fe overload did not affect LR · generation rate. CPZ treatment did not affect CAT activity after 1-4 h neither in control rats nor in acute Fe-overloaded rats. However, CPZ administration to rats treated sub-chronically with Fe showed increased brain CAT activity after 2 or 4 h, as compared to control values. Fe supplementation prevented brain damage in both acute and sub-chronic models of Fe overload by selectively activating antioxidant pathways.
[Establishment of MDCK-pHaMDR cell model and standard operation procedure for assessing blood-brain barrier permeability of chemical components of traditional Chinese medicine].

PubMed

Yang, Yan-Fang; Wu, Ni; Yang, Xiu-Wei

2016-07-01

To establish MDCK-pHaMDR cell model and standard operation procedure for assessing the blood-brain barrier permeability of chemical components of traditional Chinese medicine. MDCK-pHaMDR cell model was evaluated by determining the morphology features, transepithelial electrical resistance, bidirectional transport and intracellular accumulation of Rhodamine 123 and the apparent permeability of positive control drugs caffeine and atenolol. The MDCK-pHaMDR cell model had satisfactory integrity and tightness, and stable expression of P-gp. In addition, the transport results of the positive control drugs were consistent with the reported values in literature. All the parameters tested of the MDCK-pHaMDR cell model were consistent with the requirements, so the model can be used to study the blood-brain barrier permeability of chemical components of traditional Chinese medicine. Copyright© by the Chinese Pharmaceutical Association.
Rapamycin alleviates brain edema after focal cerebral ischemia reperfusion in rats.

PubMed

Guo, Wei; Feng, Guoying; Miao, Yanying; Liu, Guixiang; Xu, Chunsheng

2014-06-01

Brain edema is a major consequence of cerebral ischemia reperfusion. However, few effective therapeutic options are available for retarding the brain edema progression after cerebral ischemia. Recently, rapamycin has been shown to produce neuroprotective effects in rats after cerebral ischemia reperfusion. Whether rapamycin could alleviate this brain edema injury is still unclear. In this study, the rat stroke model was induced by a 1-h left transient middle cerebral artery occlusion using an intraluminal filament, followed by 48 h of reperfusion. The effects of rapamycin (250 μg/kg body weight, intraperitoneal; i.p.) on brain edema progression were evaluated. The results showed that rapamycin treatment significantly reduced the infarct volume, the water content of the brain tissue and the Evans blue extravasation through the blood-brain barrier (BBB). Rapamycin treatment could improve histological appearance of the brain tissue, increased the capillary lumen space and maintain the integrity of BBB. Rapamycin also inhibited matrix metalloproteinase 9 (MMP9) and aquaporin 4 (AQP4) expression. These data imply that rapamycin could improve brain edema progression after reperfusion injury through maintaining BBB integrity and inhibiting MMP9 and AQP4 expression. The data of this study provide a new possible approach for improving brain edema after cerebral ischemia reperfusion by administration of rapamycin.
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.
Integrated Cox's model for predicting survival time of glioblastoma multiforme.

PubMed

Ai, Zhibing; Li, Longti; Fu, Rui; Lu, Jing-Min; He, Jing-Dong; Li, Sen

2017-04-01

Glioblastoma multiforme is the most common primary brain tumor and is highly lethal. This study aims to figure out signatures for predicting the survival time of patients with glioblastoma multiforme. Clinical information, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism array data of patients with glioblastoma multiforme were retrieved from The Cancer Genome Atlas. Patients were separated into two groups by using 1 year as a cutoff, and a logistic regression model was used to figure out any variables that can predict whether the patient was able to live longer than 1 year. Furthermore, Cox's model was used to find out features that were correlated with the survival time. Finally, a Cox model integrated the significant clinical variables, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism was built. Although the classification method failed, signatures of clinical features, messenger RNA expression levels, and microRNA expression levels were figured out by using Cox's model. However, no single-nucleotide polymorphisms related to prognosis were found. The selected clinical features were age at initial diagnosis, Karnofsky score, and race, all of which had been suggested to correlate with survival time. Both of the two significant microRNAs, microRNA-221 and microRNA-222, were targeted to p27 Kip1 protein, which implied the important role of p27 Kip1 on the prognosis of glioblastoma multiforme patients. Our results suggested that survival modeling was more suitable than classification to figure out prognostic biomarkers for patients with glioblastoma multiforme. An integrated model containing clinical features, messenger RNA levels, and microRNA expression levels was built, which has the potential to be used in clinics and thus to improve the survival status of glioblastoma multiforme patients.
Audio-tactile integration and the influence of musical training.

PubMed

Kuchenbuch, Anja; Paraskevopoulos, Evangelos; Herholz, Sibylle C; Pantev, Christo

2014-01-01

Perception of our environment is a multisensory experience; information from different sensory systems like the auditory, visual and tactile is constantly integrated. Complex tasks that require high temporal and spatial precision of multisensory integration put strong demands on the underlying networks but it is largely unknown how task experience shapes multisensory processing. Long-term musical training is an excellent model for brain plasticity because it shapes the human brain at functional and structural levels, affecting a network of brain areas. In the present study we used magnetoencephalography (MEG) to investigate how audio-tactile perception is integrated in the human brain and if musicians show enhancement of the corresponding activation compared to non-musicians. Using a paradigm that allowed the investigation of combined and separate auditory and tactile processing, we found a multisensory incongruency response, generated in frontal, cingulate and cerebellar regions, an auditory mismatch response generated mainly in the auditory cortex and a tactile mismatch response generated in frontal and cerebellar regions. The influence of musical training was seen in the audio-tactile as well as in the auditory condition, indicating enhanced higher-order processing in musicians, while the sources of the tactile MMN were not influenced by long-term musical training. Consistent with the predictive coding model, more basic, bottom-up sensory processing was relatively stable and less affected by expertise, whereas areas for top-down models of multisensory expectancies were modulated by training.
Serum extravasation and cytoskeletal alterations following traumatic brain injury in rats. Comparison of lateral fluid percussion and cortical impact models.

PubMed

Hicks, R R; Baldwin, S A; Scheff, S W

1997-01-01

Disruption of the blood-brain barrier (BBB) and neuronal cytoskeletal damage were evaluated in two commonly used rat models of traumatic brain injury. Adult rats received a lateral cortical impact (CI) or lateral fluid percussion (FP) injury of mild or moderate severity or a sham procedure. Six hours after trauma, the brains were removed and analyzed with immunocytochemical techniques for alterations in the serum protein, IgG, and the cytoskeletal protein, microtubule-associated protein 2 (MAP2). Both models induced profound alterations in these proteins in the ipsilateral cortex and hippocampus compared to sham-injured controls. Following an injury of moderate severity, the CI injury resulted in greater IgG extravasation in the cortex and hippocampus than the FP injury. Conversely, after a mild injury, IgG extravasation in the hippocampus was greater for FP than CI. All of the animals in the CI group and most of the FP group showed a loss of MAP2 in the hippocampus. The specific subregions within the cortex and hippocampus that were affected by the injury varied between models, despite having identical impact sites. These data demonstrate that there are both similarities and differences between a CI and FP injury on vascular and neuronal cystoskeletal integrity, which should be considered when utilizing these animal models to study selected features of human head injury.
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.
Program evaluation of an Integrated Basic Science Medical Curriculum in Shiraz Medical School, Using CIPP Evaluation Model

PubMed Central

ROOHOLAMINI, AZADEH; AMINI, MITRA; BAZRAFKAN, LEILA; DEHGHANI, MOHAMMAD REZA; ESMAEILZADEH, ZOHREH; NABEIEI, PARISA; REZAEE, RITA; KOJURI, JAVAD

2017-01-01

Introduction: In recent years curriculum reform and integration was done in many medical schools. The integrated curriculum is a popular concept all over the world. In Shiraz medical school, the reform was initiated by stablishing the horizontal basic science integration model and Early Clinical Exposure (ECE) for undergraduate medical education. The purpose of this study was to provide the required data for the program evaluation of this curriculum for undergraduate medical students, using CIPP program evaluation model. Methods: This study is an analytic descriptive and triangulation mixed method study which was carried out in Shiraz Medical School in 2012, based on the views of professors of basic sciences courses and first and second year medical students. The study evaluated the quality of the relationship between basic sciences and clinical courses and the method of presenting such courses based on the Context, Input, Process and Product (CIPP) model. The tools for collecting data, both quantitatively and qualitatively, were some questionnaires, content analysis of portfolios, semi- structured interview and brain storming sessions. For quantitative data analysis, SPSS software, version 14, was used. Results: In the context evaluation by modified DREEM questionnaire, 77.75%of the students believed that this educational system encourages them to actively participate in classes. Course schedule and atmosphere of class were reported suitable by 87.81% and 83.86% of students. In input domain that was measured by a researcher made questionnaire, the facilities for education were acceptable except for shortage of cadavers. In process evaluation, the quality of integrated modules presentation and Early Clinical Exposure (ECE) was good from the students’ viewpoint. In product evaluation, students’ brain storming, students’ portfolio and semi-structured interview with faculties were done, showing some positive aspects of integration and some areas that need
Amphiphilic HPMA-LMA copolymers increase the transport of Rhodamine 123 across a BBB model without harming its barrier integrity.

PubMed

Hemmelmann, Mirjam; Metz, Verena V; Koynov, Kaloian; Blank, Kerstin; Postina, Rolf; Zentel, Rudolf

2012-10-28

The successful non-invasive treatment of diseases associated with the central nervous system (CNS) is generally limited by poor brain permeability of various developed drugs. The blood-brain barrier (BBB) prevents the passage of therapeutics to their site of action. Polymeric drug delivery systems are promising solutions to effectively transport drugs into the brain. We recently showed that amphiphilic random copolymers based on the hydrophilic p(N-(2-hydroxypropyl)-methacrylamide), pHPMA, possessing randomly distributed hydrophobic p(laurylmethacrylate), pLMA, are able to mediate delivery of domperidone into the brain of mice in vivo. To gain further insight into structure-property relations, a library of carefully designed polymers based on p(HPMA) and p(LMA) was synthesized and tested applying an in vitro BBB model which consisted of human brain microvascular endothelial cells (HBMEC). Our model drug Rhodamine 123 (Rh123) exhibits, like domperidone, a low brain permeability since both substances are recognized by efflux transporters at the BBB. Transport studies investigating the impact of the polymer architecture in relation to the content of hydrophobic LMA revealed that random p(HPMA)-co-p(LMA) having 10mol% LMA is the most auspicious system. The copolymer significantly increased the permeability of Rh123 across the HBMEC monolayer whereas transcytosis of the polymer was very low. Further investigations on the mechanism of transport showed that integrity and barrier function of the BBB model were not harmed by the polymer. According to our results, p(HPMA)-co-p(LMA) copolymers are a promising delivery system for neurological therapeutics and their application might open alternative treatment strategies. Copyright © 2012 Elsevier B.V. All rights reserved.
Brain Death and Human Organismal Integration: A Symposium on the Definition of Death

PubMed Central

Moschella, Melissa

2016-01-01

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

PubMed Central

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

2016-01-01

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes. PMID:27808095
A simulation model for analysing brain structure deformations.

PubMed

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

2003-12-21

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

PubMed

Surbeck, Werner; Killeen, Tim; Vetter, Johannes; Hildebrandt, Gerhard

2018-06-01

Since the early days of modern neuroscience, psychological models of brain function have been a key component in the development of new knowledge. These models aim to provide a framework that allows the integration of discoveries derived from the fundamental disciplines of neuroscience, including anatomy and physiology, as well as clinical neurology and psychiatry. During the initial stages of his career, Sigmund Freud (1856-1939), became actively involved in these nascent fields with a burgeoning interest in functional neuroanatomy. In contrast to his contemporaries, Freud was convinced that cognition could not be localised to separate modules and that the brain processes cognition not in a merely serial manner but in a parallel and dynamic fashion-anticipating fundamental aspects of current network theories of brain function. This article aims to shed light on Freud's seminal, yet oft-overlooked, early work on functional neuroanatomy and his reasons for finally abandoning the conventional neuroscientific "brain-based" reference frame in order to conceptualise the mind from a purely psychological perspective.
Authentic Integration: a model for integrating mathematics and science in the classroom

NASA Astrophysics Data System (ADS)

Treacy, Páraic; O'Donoghue, John

2014-07-01

Attempts at integrating mathematics and science have been made previously but no definitive, widely adopted teaching model has been developed to date. Research suggests that hands-on, practical, student-centred tasks should form a central element when designing an effective model for the integration of mathematics and science. Aided by this research, the author created a new model entitled 'Authentic Integration' which caters for the specific needs of integration of mathematics and science. This model requires that each lesson be based around a rich task which relates to the real world and ensures that hands-on group work, inquiry, and discussion are central to the lesson. It was found that Authentic Integration, when applied in four Irish post-primary schools, positively affected pupil understanding. The teachers who completed the intervention displayed a very positive attitude towards the approach, intimating that they would continue to implement the practice in their classrooms.
Design of a framework for modeling, integration and simulation of physiological models.

PubMed

Erson, E Zeynep; Cavuşoğlu, M Cenk

2012-09-01

Multiscale modeling and integration of physiological models carry challenges due to the complex nature of physiological processes. High coupling within and among scales present a significant challenge in constructing and integrating multiscale physiological models. In order to deal with such challenges in a systematic way, there is a significant need for an information technology framework together with related analytical and computational tools that will facilitate integration of models and simulations of complex biological systems. Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM) is an information technology framework providing the tools to facilitate development, integration and simulation of integrated models of human physiology. Phy-SIM brings software level solutions to the challenges raised by the complex nature of physiological systems. The aim of Phy-SIM, and this paper is to lay some foundation with the new approaches such as information flow and modular representation of the physiological models. The ultimate goal is to enhance the development of both the models and the integration approaches of multiscale physiological processes and thus this paper focuses on the design approaches that would achieve such a goal. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
A new model for diffuse brain injury by rotational acceleration: I model, gross appearance, and astrocytosis.

PubMed

Gutierrez, E; Huang, Y; Haglid, K; Bao, F; Hansson, H A; Hamberger, A; Viano, D

2001-03-01

Rapid head rotation is a major cause of brain damage in automobile crashes and falls. This report details a new model for rotational acceleration about the center of mass of the rabbit head. This allows the study of brain injury without translational acceleration of the head. Impact from a pneumatic cylinder was transferred to the skull surface to cause a half-sine peak acceleration of 2.1 x 10(5) rad/s2 and 0.96-ms pulse duration. Extensive subarachnoid hemorrhages and small focal bleedings were observed in the brain tissue. A pronounced reactive astrogliosis was found 8-14 days after trauma, both as networks around the focal hemorrhages and more diffusely in several brain regions. Astrocytosis was prominent in the gray matter of the cerebral cortex, layers II-V, and in the granule cell layer and around the axons of the pyramidal neurons in the hippocampus. The nuclei of cranial nerves, such as the hypoglossal and facial nerves, also showed intense astrocytosis. The new model allows study of brain injuries from head rotation in the absence of translational influences.
Collagen-based brain microvasculature model in vitro using three-dimensional printed template

PubMed Central

Kim, Jeong Ah; Kim, Hong Nam; Im, Sun-Kyoung; Chung, Seok

2015-01-01

We present an engineered three-dimensional (3D) in vitro brain microvasculature system embedded within the bulk of a collagen matrix. To create a hydrogel template for the functional brain microvascular structure, we fabricated an array of microchannels made of collagen I using microneedles and a 3D printed frame. By culturing mouse brain endothelial cells (bEnd.3) on the luminal surface of cylindrical collagen microchannels, we reconstructed an array of brain microvasculature in vitro with circular cross-sections. We characterized the barrier function of our brain microvasculature by measuring transendothelial permeability of 40 kDa fluorescein isothiocyanate-dextran (Stoke's radius of ∼4.5 nm), based on an analytical model. The transendothelial permeability decreased significantly over 3 weeks of culture. We also present the disruption of the barrier function with a hyperosmotic mannitol as well as a subsequent recovery over 4 days. Our brain microvasculature model in vitro, consisting of system-in-hydrogel combined with the widely emerging 3D printing technique, can serve as a useful tool not only for fundamental studies associated with blood-brain barrier in physiological and pathological settings but also for pharmaceutical applications. PMID:25945141
Functional integration changes in regional brain glucose metabolism from childhood to adulthood.

PubMed

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

2016-08-01

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

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

PubMed

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

2010-01-01

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

PubMed

de Groot, Jack; Vernooij-Dassen, Myrra; Hoedemaekers, Cornelia; Hoitsma, Andries; Smeets, Wim; van Leeuwen, Evert

2012-06-27

Deciding about the organ donation of one's brain-dead beloved often occurs in an unexpected and delicate situation. We explored the decision making of the relatives of potential brain-dead donors, its evaluation, and the factors influencing decision making. We used the integrative review method. Our search included 10 databases. Inclusion criteria were presence of the donation request or the subsequent decision process. Three authors independently assessed the eligibility of identified articles. Content analysis of 70 included articles led to three themes: decision, evaluation, and support. We extracted results and recommendations concerning these three themes. The timing of the request and understandable information influence the decision. The relatives evaluate their decision differently: in case of refusal, approximately one third regret their decision, and in case of consent, approximately one tenth mention regret. The relatives are often ambivalent about their values (protection, altruism, and respect) and the deceased's wishes, not wanting additional suffering either for their beloved or for themselves. Support is mainly focused on increasing consent rates and less on satisfaction with the decision. Evaluation of decision making by the relatives of potential brain-dead donors reveals possibilities for improving the decision process. Special skills of the requester, attention to the circumstances, and unconditional support for the relatives might prevent the relatives' regret about refusal and unnecessary loss of organs. We hypothesize that support in exploring the relatives' values and the deceased's wishes can lead to stable decisions. This hypothesis deserves further investigation.
Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

PubMed

Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

2017-10-01

Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.
Describing the Neuron Axons Network of the Human Brain by Continuous Flow Models

NASA Astrophysics Data System (ADS)

Hizanidis, J.; Katsaloulis, P.; Verganelakis, D. A.; Provata, A.

2014-12-01

The multifractal spectrum Dq (Rényi dimensions) is used for the analysis and comparison between the Neuron Axons Network (NAN) of healthy and pathological human brains because it conveys information about the statistics in many scales, from the very rare to the most frequent network configurations. Comparison of the Fractional Anisotropy Magnetic Resonance Images between healthy and pathological brains is performed with and without noise reduction. Modelling the complex structure of the NAN in the human brain is undertaken using the dynamics of the Lorenz model in the chaotic regime. The Lorenz multifractal spectra capture well the human brain characteristics in the large negative q's which represent the rare network configurations. In order to achieve a closer approximation in the positive part of the spectrum (q > 0) two independent modifications are considered: a) redistribution of the dense parts of the Lorenz model's phase space into their neighbouring areas and b) inclusion of additive uniform noise in the Lorenz model. Both modifications, independently, drive the Lorenz spectrum closer to the human NAN one in the positive q region without destroying the already good correspondence of the negative spectra. The modelling process shows that the unmodified Lorenz model in its full chaotic regime has a phase space distribution with high fluctuations in its dense parts, while the fluctuations in the human brain NAN are smoother. The induced modifications (phase space redistribution or additive noise) moderate the fluctuations only in the positive part of the Lorenz spectrum leading to a faithful representation of the human brain axons network in all scales.
"Neuro-semeiotics" and "free-energy minimization" suggest a unified perspective for integrative brain actions: focus on receptor heteromers and Roamer type of volume transmission.

PubMed

Agnati, Luigi F; Guidolin, Diego; Marcoli, Manuela; Genedani, Susanna; Borroto-Escuela, Dasiel; Maura, Guido; Fuxe, Kjell

2014-01-01

Two far-reaching theoretical approaches, namely "Neuro-semeiotics" (NS) and "Free-energy Minimization" (FEM), have been recently proposed as frames within which to put forward heuristic hypotheses on integrative brain actions. In the present paper these two theoretical approaches are briefly discussed in the perspective of a recent model of brain architecture and information handling based on what we suggest calling Jacob's tinkering principle, whereby "to create is to recombine!". The NS and FEM theoretical approaches will be discussed from the perspective both of the Roamer-Type Volume Transmission (especially exosome-mediated) of intercellular communication and of the impact of receptor oligomers and Receptor-Receptor Interactions (RRIs) on signal recognition/decoding processes. In particular, the Bio-semeiotics concept of "adaptor" will be used to analyze RRIs as an important feature of NS. Furthermore, the concept of phenotypic plasticity of cells will be introduced in view of the demonstration of the possible transfer of receptors (i.e., adaptors) into a computational network via exosomes (see also Appendix). Thus, Jacob's tinkering principle will be proposed as a theoretical basis for some learning processes both at the network level (Turing-like type of machine) and at the molecular level as a consequence of both the plastic changes in the adaptors caused by the allosteric interactions in the receptor oligomers and the intercellular transfer of receptors. Finally, on the basis of NS and FEM theories, a unified perspective for integrative brain actions will be proposed.
Application of Texture Analysis to Study Small Vessel Disease and Blood-Brain Barrier Integrity.

PubMed

Valdés Hernández, Maria Del C; González-Castro, Victor; Chappell, Francesca M; Sakka, Eleni; Makin, Stephen; Armitage, Paul A; Nailon, William H; Wardlaw, Joanna M

2017-01-01

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

NASA Astrophysics Data System (ADS)

Ye, Yan; Li, Xiaoping; Wu, Tiecheng; Li, Zhe; Xie, Wenwen

2015-12-01

Deep brain activity is conventionally recorded with surgical implantation of electrodes. During the neurosurgery, brain tissue damage and the consequent side effects to patients are inevitably incurred. In order to eliminate undesired risks, we propose that deep brain activity should be measured using the noninvasive scalp electroencephalography (EEG) technique. However, the deeper the neuronal activity is located, the noisier the corresponding scalp EEG signals are. Thus, the present study aims to evaluate whether deep brain activity could be observed from EEG recordings. In the experiment, a three-layer cylindrical head model was constructed to mimic a human head. A single dipole source (sine wave, 10 Hz, altering amplitudes) was embedded inside the model to simulate neuronal activity. When the dipole source was activated, surface potential was measured via electrodes attached on the top surface of the model and raw data were recorded for signal analysis. Results show that the dipole source activity positioned at 66 mm depth in the model, equivalent to the depth of deep brain structures, is clearly observed from surface potential recordings. Therefore, it is highly possible that deep brain activity could be observed from EEG recordings and deep brain activity could be measured using the noninvasive scalp EEG technique.
Brain lactate kinetics: Modeling evidence for neuronal lactate uptake upon activation.

PubMed

Aubert, Agnès; Costalat, Robert; Magistretti, Pierre J; Pellerin, Luc

2005-11-08

A critical issue in brain energy metabolism is whether lactate produced within the brain by astrocytes is taken up and metabolized by neurons upon activation. Although there is ample evidence that neurons can efficiently use lactate as an energy substrate, at least in vitro, few experimental data exist to indicate that it is indeed the case in vivo. To address this question, we used a modeling approach to determine which mechanisms are necessary to explain typical brain lactate kinetics observed upon activation. On the basis of a previously validated model that takes into account the compartmentalization of energy metabolism, we developed a mathematical model of brain lactate kinetics, which was applied to published data describing the changes in extracellular lactate levels upon activation. Results show that the initial dip in the extracellular lactate concentration observed at the onset of stimulation can only be satisfactorily explained by a rapid uptake within an intraparenchymal cellular compartment. In contrast, neither blood flow increase, nor extracellular pH variation can be major causes of the lactate initial dip, whereas tissue lactate diffusion only tends to reduce its amplitude. The kinetic properties of monocarboxylate transporter isoforms strongly suggest that neurons represent the most likely compartment for activation-induced lactate uptake and that neuronal lactate utilization occurring early after activation onset is responsible for the initial dip in brain lactate levels observed in both animals and humans.
The blood-brain barrier as a target in traumatic brain injury treatment.

PubMed

Thal, Serge C; Neuhaus, Winfried

2014-11-01

Traumatic brain injury (TBI) is one of the most frequent causes of death in the young population. Several clinical trials have unsuccessfully focused on direct neuroprotective therapies. Recently immunotherapeutic strategies shifted into focus of translational research in acute CNS diseases. Cross-talk between activated microglia and blood-brain barrier (BBB) could initiate opening of the BBB and subsequent recruitment of systemic immune cells and mediators into the brain. Stabilization of the BBB after TBI could be a promising strategy to limit neuronal inflammation, secondary brain damage and acute neurodegeneration. This review provides an overview on the pathophysiology of TBI and brain edema formation including definitions and classification of TBI, current clinical treatment strategies, as well as current understanding on the underlying cellular processes. A summary of in vivo and in vitro models to study different aspects of TBI is presented. Three mechanisms proposed for stabilization of the BBB, myosin light chain kinases, glucocorticoid receptors and peroxisome proliferator-activated receptors are reviewed for their influence on barrier-integrity and outcome after TBI. In conclusion, the BBB is recommended as a promising target for the treatment of traumatic brain injury, and it is suggested that a combination of BBB stabilization and neuroprotectants may improve therapeutic success. Copyright © 2015 IMSS. Published by Elsevier Inc. All rights reserved.
Animal models of traumatic brain injury

PubMed Central

Xiong, Ye; Mahmood, Asim; Chopp, Michael

2014-01-01

Traumatic brain injury (TBI) is a leading cause of mortality and morbidity in both civilian life and the battlefield worldwide. Survivors of TBI frequently experience long-term disabling changes in cognition, sensorimotor function and personality. Over the past three decades, animal models have been developed to replicate the various aspects of human TBI, to better understand the underlying pathophysiology and to explore potential treatments. Nevertheless, promising neuroprotective drugs, which were identified to be effective in animal TBI models, have all failed in phase II or phase III clinical trials. This failure in clinical translation of preclinical studies highlights a compelling need to revisit the current status of animal models of TBI and therapeutic strategies. PMID:23329160
Low resolution brain electromagnetic tomography in a realistic geometry head model: a simulation study

NASA Astrophysics Data System (ADS)

Ding, Lei; Lai, Yuan; He, Bin

2005-01-01

It is of importance to localize neural sources from scalp recorded EEG. Low resolution brain electromagnetic tomography (LORETA) has received considerable attention for localizing brain electrical sources. However, most such efforts have used spherical head models in representing the head volume conductor. Investigation of the performance of LORETA in a realistic geometry head model, as compared with the spherical model, will provide useful information guiding interpretation of data obtained by using the spherical head model. The performance of LORETA was evaluated by means of computer simulations. The boundary element method was used to solve the forward problem. A three-shell realistic geometry (RG) head model was constructed from MRI scans of a human subject. Dipole source configurations of a single dipole located at different regions of the brain with varying depth were used to assess the performance of LORETA in different regions of the brain. A three-sphere head model was also used to approximate the RG head model, and similar simulations performed, and results compared with the RG-LORETA with reference to the locations of the simulated sources. Multi-source localizations were discussed and examples given in the RG head model. Localization errors employing the spherical LORETA, with reference to the source locations within the realistic geometry head, were about 20-30 mm, for four brain regions evaluated: frontal, parietal, temporal and occipital regions. Localization errors employing the RG head model were about 10 mm over the same four brain regions. The present simulation results suggest that the use of the RG head model reduces the localization error of LORETA, and that the RG head model based LORETA is desirable if high localization accuracy is needed.
Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

PubMed

Kriegeskorte, Nikolaus

2015-11-24

Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.
Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

PubMed Central

Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

2014-01-01

Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412
A model to predict progression in brain-injured patients.

PubMed

Tommasino, N; Forteza, D; Godino, M; Mizraji, R; Alvarez, I

2014-11-01

The study of brain death (BD) epidemiology and the acute brain injury (ABI) progression profile is important to improve public health programs, organ procurement strategies, and intensive care unit (ICU) protocols. The purpose of this study was to analyze the ABI progression profile among patients admitted to ICUs with a Glasgow Coma Score (GCS) ≤8, as well as establishing a prediction model of probability of death and BD. This was a retrospective analysis of prospective data that included all brain-injured patients with GCS ≤8 admitted to a total of four public and private ICUs in Uruguay (N = 1447). The independent predictor factors of death and BD were studied using logistic regression analysis. A hierarchical model consisting of 2 nested logit regression models was then created. With these models, the probabilities of death, BD, and death by cardiorespiratory arrest were analyzed. In the first regression, we observed that as the GCS decreased and age increased, the probability of death rose. Each additional year of age increased the probability of death by 0.014. In the second model, however, BD risk decreased with each year of age. The presence of swelling, mass effect, and/or space-occupying lesion increased BD risk for the same given GCS. In the presence of injuries compatible with intracranial hypertension, age behaved as a protective factor that reduced the probability of BD. Based on the analysis of the local epidemiology, a model to predict the probability of death and BD can be developed. The organ potential donation of a country, region, or hospital can be predicted on the basis of this model, customizing it to each specific situation.
Integrated system for point cloud reconstruction and simulated brain shift validation using tracked surgical microscope

NASA Astrophysics Data System (ADS)

Yang, Xiaochen; Clements, Logan W.; Luo, Ma; Narasimhan, Saramati; Thompson, Reid C.; Dawant, Benoit M.; Miga, Michael I.

2017-03-01

Intra-operative soft tissue deformation, referred to as brain shift, compromises the application of current imageguided surgery (IGS) navigation systems in neurosurgery. A computational model driven by sparse data has been used as a cost effective method to compensate for cortical surface and volumetric displacements. Stereoscopic microscopes and laser range scanners (LRS) are the two most investigated sparse intra-operative imaging modalities for driving these systems. However, integrating these devices in the clinical workflow to facilitate development and evaluation requires developing systems that easily permit data acquisition and processing. In this work we present a mock environment developed to acquire stereo images from a tracked operating microscope and to reconstruct 3D point clouds from these images. A reconstruction error of 1 mm is estimated by using a phantom with a known geometry and independently measured deformation extent. The microscope is tracked via an attached tracking rigid body that facilitates the recording of the position of the microscope via a commercial optical tracking system as it moves during the procedure. Point clouds, reconstructed under different microscope positions, are registered into the same space in order to compute the feature displacements. Using our mock craniotomy device, realistic cortical deformations are generated. Our experimental results report approximately 2mm average displacement error compared with the optical tracking system. These results demonstrate the practicality of using tracked stereoscopic microscope as an alternative to LRS to collect sufficient intraoperative information for brain shift correction.
The brain as a system of nested but partially overlapping networks. Heuristic relevance of the model for brain physiology and pathology.

PubMed

Agnati, L F; Guidolin, D; Fuxe, K

2007-01-01

A new model of the brain organization is proposed. The model is based on the assumption that a global molecular network enmeshes the entire central nervous system. Thus, brain extra-cellular and intra-cellular molecular networks are proposed to communicate at the level of special plasma membrane regions (e.g., the lipid rafts) where horizontal molecular networks can represent input/output regions allowing the cell to have informational exchanges with the extracellular environment. Furthermore, some "pervasive signals" such as field potentials, pressure waves and thermal gradients that affect large parts of the brain cellular and molecular networks are discussed. Finally, at least two learning paradigms are analyzed taking into account the possible role of Volume Transmission: the so-called model of "temporal difference learning" and the "Turing B-unorganised machine". The relevance of this new view of brain organization for a deeper understanding of some neurophysiological and neuropathological aspects of its function is briefly discussed.
Integrating Conceptual Knowledge within and across Representational Modalities

ERIC Educational Resources Information Center

McNorgan, Chris; Reid, Jackie; McRae, Ken

2011-01-01

Research suggests that concepts are distributed across brain regions specialized for processing information from different sensorimotor modalities. Multimodal semantic models fall into one of two broad classes differentiated by the assumed hierarchy of convergence zones over which information is integrated. In shallow models, communication within-…
Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

PubMed

Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F

2014-02-01

A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.
A mathematical model for human brain cooling during cold-water near-drowning.

PubMed

Xu, X; Tikuisis, P; Giesbrecht, G

1999-01-01

A two-dimensional mathematical model was developed to estimate the contributions of different mechanisms of brain cooling during cold-water near-drowning. Mechanisms include 1) conductive heat loss through tissue to the water at the head surface and in the upper airway and 2) circulatory cooling to aspirated water via the lung and via venous return from the scalp. The model accounts for changes in boundary conditions, blood circulation, respiratory ventilation of water, and head size. Results indicate that conductive heat loss through the skull surface or the upper airways is minimal, although a small child-sized head will conductively cool faster than a large adult-sized head. However, ventilation of cold water may provide substantial brain cooling through circulatory cooling. Although it seems that water breathing is required for rapid "whole" brain cooling, it is possible that conductive cooling may provide some advantage by cooling the brain cortex peripherally and the brain stem centrally via the upper airway.
Intact blood-brain barrier transport of small molecular drugs in animal models of amyloid beta and alpha-synuclein pathology.

PubMed

Gustafsson, Sofia; Lindström, Veronica; Ingelsson, Martin; Hammarlund-Udenaes, Margareta; Syvänen, Stina

2018-01-01

Pathophysiological impairment of the neurovascular unit, including the integrity and dynamics of the blood-brain barrier (BBB), has been denoted both a cause and consequence of neurodegenerative diseases. Pathological impact on BBB drug delivery has also been debated. The aim of the present study was to investigate BBB drug transport, by determining the unbound brain-to-plasma concentration ratio (K p,uu,brain ), in aged AβPP-transgenic mice, α-synuclein transgenic mice, and wild type mice. Mice were dosed with a cassette of five compounds, including digoxin, levofloxacin (1 mg/kg, s.c.), paliperidone, oxycodone, and diazepam (0.25 mg/kg, s.c.). Brain and blood were collected at 0.5, 1, or 3 h after dosage. Drug concentrations were measured using LC-MS/MS. The total brain-to-plasma concentration ratio was calculated and equilibrium dialysis was used to determine the fraction of unbound drug in brain and plasma for all compounds. Together, these three measures were used to determine the K p,uu,brain value. Despite Aβ or α-synuclein pathology in the current animal models, no difference was observed in the extent of drug transport across the BBB compared to wild type animals for any of the compounds investigated. Hence, the present study shows that the concept of a leaking barrier within neurodegenerative conditions has to be interpreted with caution when estimating drug transport into the brain. The capability of the highly dynamic BBB to regulate brain drug exposure still seems to be intact despite the presence of pathology. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

BrainFrame: a node-level heterogeneous accelerator platform for neuron simulations

NASA Astrophysics Data System (ADS)

Smaragdos, Georgios; Chatzikonstantis, Georgios; Kukreja, Rahul; Sidiropoulos, Harry; Rodopoulos, Dimitrios; Sourdis, Ioannis; Al-Ars, Zaid; Kachris, Christoforos; Soudris, Dimitrios; De Zeeuw, Chris I.; Strydis, Christos

2017-12-01

Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. Approach. In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU, a NVidia GP-GPU and a Maxeler Dataflow Engine. The PyNN software framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different experiment instances of a state-of-the-art neuron model, representing the inferior-olivary nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal-network dimensions but also different network-connectivity densities, which can drastically affect the workload’s performance characteristics. Main results. The combined use of different HPC technologies demonstrates that BrainFrame is better able to cope with the modeling diversity encountered in realistic experiments while at the same time running on significantly lower energy budgets. Our performance analysis clearly shows that the model directly affects performance and all three technologies are required to cope with all the model use cases. Significance. The BrainFrame framework is designed to transparently configure and select the appropriate back-end accelerator technology for use per simulation run. The PyNN integration provides a familiar bridge to the vast number of models already available. Additionally, it gives a clear roadmap for extending the platform
BrainFrame: a node-level heterogeneous accelerator platform for neuron simulations.

PubMed

Smaragdos, Georgios; Chatzikonstantis, Georgios; Kukreja, Rahul; Sidiropoulos, Harry; Rodopoulos, Dimitrios; Sourdis, Ioannis; Al-Ars, Zaid; Kachris, Christoforos; Soudris, Dimitrios; De Zeeuw, Chris I; Strydis, Christos

2017-12-01

The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU, a NVidia GP-GPU and a Maxeler Dataflow Engine. The PyNN software framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different experiment instances of a state-of-the-art neuron model, representing the inferior-olivary nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal-network dimensions but also different network-connectivity densities, which can drastically affect the workload's performance characteristics. The combined use of different HPC technologies demonstrates that BrainFrame is better able to cope with the modeling diversity encountered in realistic experiments while at the same time running on significantly lower energy budgets. Our performance analysis clearly shows that the model directly affects performance and all three technologies are required to cope with all the model use cases. The BrainFrame framework is designed to transparently configure and select the appropriate back-end accelerator technology for use per simulation run. The PyNN integration provides a familiar bridge to the vast number of models already available. Additionally, it gives a clear roadmap for extending the platform support beyond the proof of concept, with improved
A physical multifield model predicts the development of volume and structure in the human brain

NASA Astrophysics Data System (ADS)

Rooij, Rijk de; Kuhl, Ellen

2018-03-01

The prenatal development of the human brain is characterized by a rapid increase in brain volume and a development of a highly folded cortex. At the cellular level, these events are enabled by symmetric and asymmetric cell division in the ventricular regions of the brain followed by an outwards cell migration towards the peripheral regions. The role of mechanics during brain development has been suggested and acknowledged in past decades, but remains insufficiently understood. Here we propose a mechanistic model that couples cell division, cell migration, and brain volume growth to accurately model the developing brain between weeks 10 and 29 of gestation. Our model accurately predicts a 160-fold volume increase from 1.5 cm3 at week 10 to 235 cm3 at week 29 of gestation. In agreement with human brain development, the cortex begins to form around week 22 and accounts for about 30% of the total brain volume at week 29. Our results show that cell division and coupling between cell density and volume growth are essential to accurately model brain volume development, whereas cell migration and diffusion contribute mainly to the development of the cortex. We demonstrate that complex folding patterns, including sinusoidal folds and creases, emerge naturally as the cortex develops, even for low stiffness contrasts between the cortex and subcortex.
Phosphorylated recombinant HSP27 protects the brain and attenuates blood-brain barrier disruption following stroke in mice receiving intravenous tissue-plasminogen activator.

PubMed

Shimada, Yoshiaki; Shimura, Hideki; Tanaka, Ryota; Yamashiro, Kazuo; Koike, Masato; Uchiyama, Yasuo; Urabe, Takao; Hattori, Nobutaka

2018-01-01

Loss of integrity of the blood-brain barrier (BBB) in ischemic stroke victims initiates a devastating cascade of events causing brain damage. Maintaining the BBB is important to preserve brain function in ischemic stroke. Unfortunately, recombinant tissue plasminogen activator (tPA), the only effective fibrinolytic treatment at the acute stage of ischemic stroke, also injures the BBB and increases the risk of brain edema and secondary hemorrhagic transformation. Thus, it is important to identify compounds that maintain BBB integrity in the face of ischemic injury in patients with stroke. We previously demonstrated that intravenously injected phosphorylated recombinant heat shock protein 27 (prHSP27) protects the brains of mice with transient middle cerebral artery occlusion (tMCAO), an animal stroke-model. Here, we determined whether prHSP27, in addition to attenuating brain injury, also decreases BBB damage in hyperglycemic tMCAO mice that had received tPA. After induction of hyperglycemia and tMCAO, we examined 4 treatment groups: 1) bovine serum albumin (BSA), 2) prHSP27, 3) tPA, 4) tPA plus prHSP27. We examined the effects of prHSP27 by comparing the BSA and prHSP27 groups and the tPA and tPA plus prHSP27 groups. Twenty-four hours after injection, prHSP27 reduced infarct volume, brain swelling, neurological deficits, the loss of microvessel proteins and endothelial cell walls, and mortality. It also reduced the rates of hemorrhagic transformation, extravasation of endogenous IgG, and MMP-9 activity, signs of BBB damage. Therefore, prHSP27 injection attenuated brain damage and preserved the BBB in tPA-injected, hyperglycemic tMCAO experimental stroke-model mice, in which the BBB is even more severely damaged than in simple tMCAO mice. The attenuation of brain damage and BBB disruption in the presence of tPA suggests the effectiveness of prHSP27 and tPA as a combination therapy. prHSP27 may be a novel therapeutic agent for ischemic stroke patients whose BBBs are
Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468
Brain anatomical networks in early human brain development.

PubMed

Fan, Yong; Shi, Feng; Smith, Jeffrey Keith; Lin, Weili; Gilmore, John H; Shen, Dinggang

2011-02-01

Recent neuroimaging studies have demonstrated that human brain networks have economic small-world topology and modular organization, enabling efficient information transfer among brain regions. However, it remains largely unknown how the small-world topology and modular organization of human brain networks emerge and develop. Using longitudinal MRI data of 28 healthy pediatric subjects, collected at their ages of 1 month, 1 year, and 2 years, we analyzed development patterns of brain anatomical networks derived from morphological correlations of brain regional volumes. The results show that the brain network of 1-month-olds has the characteristically economic small-world topology and nonrandom modular organization. The network's cost efficiency increases with the brain development to 1 year and 2 years, so does the modularity, providing supportive evidence for the hypothesis that the small-world topology and the modular organization of brain networks are established during early brain development to support rapid synchronization and information transfer with minimal rewiring cost, as well as to balance between local processing and global integration of information. Copyright © 2010. Published by Elsevier Inc.
Integrable discrete PT symmetric model.

PubMed

Ablowitz, Mark J; Musslimani, Ziad H

2014-09-01

An exactly solvable discrete PT invariant nonlinear Schrödinger-like model is introduced. It is an integrable Hamiltonian system that exhibits a nontrivial nonlinear PT symmetry. A discrete one-soliton solution is constructed using a left-right Riemann-Hilbert formulation. It is shown that this pure soliton exhibits unique features such as power oscillations and singularity formation. The proposed model can be viewed as a discretization of a recently obtained integrable nonlocal nonlinear Schrödinger equation.
Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons.

PubMed

Maex, Reinoud; Gutkin, Boris

2017-07-01

Inhibitory interneurons interconnected via electrical and chemical (GABA A receptor) synapses form extensive circuits in several brain regions. They are thought to be involved in timing and synchronization through fast feedforward control of principal neurons. Theoretical studies have shown, however, that whereas self-inhibition does indeed reduce response duration, lateral inhibition, in contrast, may generate slow response components through a process of gradual disinhibition. Here we simulated a circuit of interneurons (stellate and basket cells) of the molecular layer of the cerebellar cortex and observed circuit time constants that could rise, depending on parameter values, to >1 s. The integration time scaled both with the strength of inhibition, vanishing completely when inhibition was blocked, and with the average connection distance, which determined the balance between lateral and self-inhibition. Electrical synapses could further enhance the integration time by limiting heterogeneity among the interneurons and by introducing a slow capacitive current. The model can explain several observations, such as the slow time course of OFF-beam inhibition, the phase lag of interneurons during vestibular rotation, or the phase lead of Purkinje cells. Interestingly, the interneuron spike trains displayed power that scaled approximately as 1/ f at low frequencies. In conclusion, stellate and basket cells in cerebellar cortex, and interneuron circuits in general, may not only provide fast inhibition to principal cells but also act as temporal integrators that build a very short-term memory. NEW & NOTEWORTHY The most common function attributed to inhibitory interneurons is feedforward control of principal neurons. In many brain regions, however, the interneurons are densely interconnected via both chemical and electrical synapses but the function of this coupling is largely unknown. Based on large-scale simulations of an interneuron circuit of cerebellar cortex, we
Integrated semiconductor optical sensors for chronic, minimally-invasive imaging of brain function.

PubMed

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

2006-01-01

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

PubMed

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.
LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8 months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. PMID:25541188
Intervention and societal costs of residential community reintegration for patients with acquired brain injury: a cost-analysis of the Brain Integration Programme.

PubMed

van Heugten, Caroline M; Geurtsen, Gert J; Derksen, R Elze; Martina, Juan D; Geurts, Alexander C H; Evers, Silvia M A A

2011-06-01

The objective of this study was to examine the intervention costs of a residential community reintegration programme for patients with acquired brain injury and to compare the societal costs before and after treatment. A cost-analysis was performed identifying costs of healthcare, informal care, and productivity losses. The costs in the year before the Brain Integration Programme (BIP) were compared with the costs in the year after the BIP using the following cost categories: care consumption, caregiver support, productivity losses. Dutch guidelines were used for cost valuation. Thirty-three cases participated (72% response). Mean age was 29.8 years, 59% traumatic brain injury. The BIP costs were €68,400. The informal care and productivity losses reduced significantly after BIP (p < 0.05), while healthcare consumption increased significantly (p < 0.05). The societal costs per patient were €48,449. After BIP these costs were €39,773; a significant reduction (p < 0.05). Assuming a stable situation the break-even point is after 8 years. The reduction in societal costs after the BIP advocates the allocation of resources and, from an economic perspective, favours reimbursement of the BIP costs by healthcare insurance companies. However, this cost-analysis is limited as it does not relate costs to clinical effectiveness. :
The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

PubMed

Başar, Erol; Düzgün, Aysel

2016-05-01

Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Transcallosal transfer of information and functional asymmetry of the human brain.

PubMed

Nowicka, Anna; Tacikowski, Pawel

2011-01-01

The corpus callosum is the largest commissure in the brain and acts as a "bridge" of nerve fibres connecting the two cerebral hemispheres. It plays a crucial role in interhemispheric integration and is responsible for normal communication and cooperation between the two hemispheres. Evolutionary pressures guiding brain size are accompanied by reduced interhemispheric and enhanced intrahemispheric connectivity. Some lines of evidence suggest that the speed of transcallosal conduction is limited in large brains (e.g., in humans), thus favouring intrahemispheric processing and brain lateralisation. Patterns of directional symmetry/asymmetry of transcallosal transfer time may be related to the degree of brain lateralisation. Neural network modelling and electrophysiological studies on interhemispheric transmission provide data supporting this supposition.
The Exercising Brain: Changes in Functional Connectivity Induced by an Integrated Multimodal Cognitive and Whole-Body Coordination Training

PubMed Central

Demirakca, Traute; Cardinale, Vita; Dehn, Sven; Ruf, Matthias; Ende, Gabriele

2016-01-01

This study investigated the impact of “life kinetik” training on brain plasticity in terms of an increased functional connectivity during resting-state functional magnetic resonance imaging (rs-fMRI). The training is an integrated multimodal training that combines motor and cognitive aspects and challenges the brain by introducing new and unfamiliar coordinative tasks. Twenty-one subjects completed at least 11 one-hour-per-week “life kinetik” training sessions in 13 weeks as well as before and after rs-fMRI scans. Additionally, 11 control subjects with 2 rs-fMRI scans were included. The CONN toolbox was used to conduct several seed-to-voxel analyses. We searched for functional connectivity increases between brain regions expected to be involved in the exercises. Connections to brain regions representing parts of the default mode network, such as medial frontal cortex and posterior cingulate cortex, did not change. Significant connectivity alterations occurred between the visual cortex and parts of the superior parietal area (BA7). Premotor area and cingulate gyrus were also affected. We can conclude that the constant challenge of unfamiliar combinations of coordination tasks, combined with visual perception and working memory demands, seems to induce brain plasticity expressed in enhanced connectivity strength of brain regions due to coactivation. PMID:26819776
An overview of the model integration process: From pre-integration assessment to testing

EPA Science Inventory

Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for buildin...
Lateral Fluid Percussion: Model of Traumatic Brain Injury in Mice

PubMed Central

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

2011-01-01

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

PubMed

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

2011-08-22

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

PubMed

Meng, Qingying; Ying, Zhe; Noble, Emily; Zhao, Yuqi; Agrawal, Rahul; Mikhail, Andrew; Zhuang, Yumei; Tyagi, Ethika; Zhang, Qing; Lee, Jae-Hyung; Morselli, Marco; Orozco, Luz; Guo, Weilong; Kilts, Tina M; Zhu, Jun; Zhang, Bin; Pellegrini, Matteo; Xiao, Xinshu; Young, Marian F; Gomez-Pinilla, Fernando; Yang, Xia

2016-05-01

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Diffusion in Brain Extracellular Space

PubMed Central

Syková, Eva; Nicholson, Charles

2009-01-01

Diffusion in the extracellular space (ECS) of the brain is constrained by the volume fraction and the tortuosity and a modified diffusion equation represents the transport behavior of many molecules in the brain. Deviations from the equation reveal loss of molecules across the blood-brain barrier, through cellular uptake, binding or other mechanisms. Early diffusion measurements used radiolabeled sucrose and other tracers. Presently, the real-time iontophoresis (RTI) method is employed for small ions and the integrative optical imaging (IOI) method for fluorescent macromolecules, including dextrans or proteins. Theoretical models and simulations of the ECS have explored the influence of ECS geometry, effects of dead-space microdomains, extracellular matrix and interaction of macromolecules with ECS channels. Extensive experimental studies with the RTI method employing the cation tetramethylammonium (TMA) in normal brain tissue show that the volume fraction of the ECS typically is about 20% and the tortuosity about 1.6 (i.e. free diffusion coefficient of TMA is reduced by 2.6), although there are regional variations. These parameters change during development and aging. Diffusion properties have been characterized in several interventions, including brain stimulation, osmotic challenge and knockout of extracellular matrix components. Measurements have also been made during ischemia, in models of Alzheimer's and Parkinson's diseases and in human gliomas. Overall, these studies improve our conception of ECS structure and the roles of glia and extracellular matrix in modulating the ECS microenvironment. Knowledge of ECS diffusion properties are valuable in contexts ranging from understanding extrasynaptic volume transmission to the development of paradigms for drug delivery to the brain. PMID:18923183

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling

PubMed Central

Hagmann, Patric; Deco, Gustavo

2015-01-01

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model’s prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information. PMID:26317432
Brain lactate kinetics: Modeling evidence for neuronal lactate uptake upon activation

PubMed Central

Aubert, Agnès; Costalat, Robert; Magistretti, Pierre J.; Pellerin, Luc

2005-01-01

A critical issue in brain energy metabolism is whether lactate produced within the brain by astrocytes is taken up and metabolized by neurons upon activation. Although there is ample evidence that neurons can efficiently use lactate as an energy substrate, at least in vitro, few experimental data exist to indicate that it is indeed the case in vivo. To address this question, we used a modeling approach to determine which mechanisms are necessary to explain typical brain lactate kinetics observed upon activation. On the basis of a previously validated model that takes into account the compartmentalization of energy metabolism, we developed a mathematical model of brain lactate kinetics, which was applied to published data describing the changes in extracellular lactate levels upon activation. Results show that the initial dip in the extracellular lactate concentration observed at the onset of stimulation can only be satisfactorily explained by a rapid uptake within an intraparenchymal cellular compartment. In contrast, neither blood flow increase, nor extracellular pH variation can be major causes of the lactate initial dip, whereas tissue lactate diffusion only tends to reduce its amplitude. The kinetic properties of monocarboxylate transporter isoforms strongly suggest that neurons represent the most likely compartment for activation-induced lactate uptake and that neuronal lactate utilization occurring early after activation onset is responsible for the initial dip in brain lactate levels observed in both animals and humans. PMID:16260743
Early Alterations of Brain Cellular Energy Homeostasis in Huntington Disease Models*

PubMed Central

Mochel, Fanny; Durant, Brandon; Meng, Xingli; O'Callaghan, James; Yu, Hua; Brouillet, Emmanuel; Wheeler, Vanessa C.; Humbert, Sandrine; Schiffmann, Raphael; Durr, Alexandra

2012-01-01

Brain energy deficit has been a suggested cause of Huntington disease (HD), but ATP depletion has not reliably been shown in preclinical models, possibly because of the immediate post-mortem changes in cellular energy metabolism. To examine a potential role of a low energy state in HD, we measured, for the first time in a neurodegenerative model, brain levels of high energy phosphates using microwave fixation, which instantaneously inactivates brain enzymatic activities and preserves in vivo levels of analytes. We studied HD transgenic R6/2 mice at ages 4, 8, and 12 weeks. We found significantly increased creatine and phosphocreatine, present as early as 4 weeks for phosphocreatine, preceding motor system deficits and decreased ATP levels in striatum, hippocampus, and frontal cortex of R6/2 mice. ATP and phosphocreatine concentrations were inversely correlated with the number of CAG repeats. Conversely, in mice injected with 3-nitroproprionic acid, an acute model of brain energy deficit, both ATP and phosphocreatine were significantly reduced. Increased creatine and phosphocreatine in R6/2 mice was associated with decreased guanidinoacetate N-methyltransferase and creatine kinase, both at the protein and RNA levels, and increased phosphorylated AMP-dependent protein kinase (pAMPK) over AMPK ratio. In addition, in 4-month-old knock-in HdhQ111/+ mice, the earliest metabolic alterations consisted of increased phosphocreatine in the frontal cortex and increased the pAMPK/AMPK ratio. Altogether, this study provides the first direct evidence of chronic alteration in homeostasis of high energy phosphates in HD models in the earliest stages of the disease, indicating possible reduced utilization of the brain phosphocreatine pool. PMID:22123819
Netrin-1 Preserves Blood-Brain Barrier Integrity Through Deleted in Colorectal Cancer/Focal Adhesion Kinase/RhoA Signaling Pathway Following Subarachnoid Hemorrhage in Rats.

PubMed

Xie, Zongyi; Enkhjargal, Budbazar; Reis, Cesar; Huang, Lei; Wan, Weifeng; Tang, Jiping; Cheng, Yuan; Zhang, John H

2017-05-19

Netrin-1 (NTN-1) has been established to be a novel intrinsic regulator of blood-brain barrier (BBB) maintenance. This study was carried out to investigate the potential roles of exogenous NTN-1 in preserving BBB integrity after experimental subarachnoid hemorrhage (SAH) as well as the underlying mechanisms of its protective effects. A total of 309 male Sprague-Dawley rats were subjected to an endovascular perforation model of SAH. Recombinant NTN-1 was administered intravenously 1 hour after SAH induction. NTN-1 small interfering RNA or Deleted in Colorectal Cancer small interfering RNA was administered intracerebroventricular at 48 hours before SAH. Focal adhesion kinase inhibitor was administered by intraperitoneal injection at 1 hour prior to SAH. Neurological scores, brain water content, BBB permeability, RhoA activity, Western blot, and immunofluorescence staining were evaluated. The expression of endogenous NTN-1 and its receptor Deleted in Colorectal Cancer were increased after SAH. Administration of exogenous NTN-1 significantly reduced brain water content and BBB permeability and ameliorated neurological deficits at 24 and 72 hours after SAH. Exogenous NTN-1 treatment significantly promoted phosphorylated focal adhesion kinase activation and inhibited RhoA activity, as well as upregulated the expression of ZO-1 and Occludin. Conversely, depletion of endogenous NTN-1 aggravated BBB breakdown and neurological impairments at 24 hours after SAH. The protective effects of NTN-1 at 24 hours after SAH were also abolished by pretreatment with Deleted in Colorectal Cancer small interfering RNA and focal adhesion kinase inhibitor. NTN-1 treatment preserved BBB integrity and improved neurological functions through a Deleted in Colorectal Cancer/focal adhesion kinase/RhoA signaling pathway after SAH. Thus, NTN-1 may serve as a promising treatment to alleviate early brain injury following SAH. © 2017 The Authors. Published on behalf of the American Heart
Do anesthetics harm the developing human brain? An integrative analysis of animal and human studies.

PubMed

Lin, Erica P; Lee, Jeong-Rim; Lee, Christopher S; Deng, Meng; Loepke, Andreas W

Anesthetics that permit surgical procedures and stressful interventions have been found to cause structural brain abnormalities and functional impairment in immature animals, generating extensive concerns among clinicians, parents, and government regulators regarding the safe use of these drugs in young children. Critically important questions remain, such as the exact age at which the developing brain is most vulnerable to the effects of anesthetic exposure, whether a particular age exists beyond which anesthetics are devoid of long-term effects on the brain, and whether any specific exposure duration exists that does not lead to deleterious effects. Accordingly, the present analysis attempts to put the growing body of animal studies, which we identified to include >440 laboratory studies to date, into a translational context, by integrating the preclinical data on brain structure and function with clinical results attained from human neurocognitive studies, which currently exceed 30 studies. Our analysis demonstrated no clear exposure duration threshold below which no structural injury or subsequent cognitive abnormalities occurred. Animal data did not clearly identify a specific age beyond which anesthetic exposure did not cause any structural or functional abnormalities. Several potential mitigating strategies were found, however, no general anesthetic was identified that consistently lacked neurodegenerative properties and could be recommended over other anesthetics. It therefore is imperative, to expand efforts to devise safer anesthetic techniques and mitigating strategies, even before long-term alterations in brain development are unequivocally confirmed to occur in millions of young children undergoing anesthesia every year. Copyright © 2016 Elsevier Inc. All rights reserved.
Investigating Causality Between Interacting Brain Areas with Multivariate Autoregressive Models of MEG Sensor Data

PubMed Central

Michalareas, George; Schoffelen, Jan-Mathijs; Paterson, Gavin; Gross, Joachim

2013-01-01

Abstract In this work, we investigate the feasibility to estimating causal interactions between brain regions based on multivariate autoregressive models (MAR models) fitted to magnetoencephalographic (MEG) sensor measurements. We first demonstrate the theoretical feasibility of estimating source level causal interactions after projection of the sensor-level model coefficients onto the locations of the neural sources. Next, we show with simulated MEG data that causality, as measured by partial directed coherence (PDC), can be correctly reconstructed if the locations of the interacting brain areas are known. We further demonstrate, if a very large number of brain voxels is considered as potential activation sources, that PDC as a measure to reconstruct causal interactions is less accurate. In such case the MAR model coefficients alone contain meaningful causality information. The proposed method overcomes the problems of model nonrobustness and large computation times encountered during causality analysis by existing methods. These methods first project MEG sensor time-series onto a large number of brain locations after which the MAR model is built on this large number of source-level time-series. Instead, through this work, we demonstrate that by building the MAR model on the sensor-level and then projecting only the MAR coefficients in source space, the true casual pathways are recovered even when a very large number of locations are considered as sources. The main contribution of this work is that by this methodology entire brain causality maps can be efficiently derived without any a priori selection of regions of interest. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc. PMID:22328419
Hypomyelination, memory impairment, and blood-brain barrier permeability in a model of sleep apnea.

PubMed

Kim, Lenise Jihe; Martinez, Denis; Fiori, Cintia Zappe; Baronio, Diego; Kretzmann, Nélson Alexandre; Barros, Helena Maria Tannhauser

2015-02-09

We investigated the effect of intermittent hypoxia, mimicking sleep apnea, on axonal integrity, blood-brain barrier permeability, and cognitive function of mice. Forty-seven C57BL mice were exposed to intermittent or sham hypoxia, alternating 30s of progressive hypoxia and 30s of reoxigenation, during 8h/day. The axonal integrity in cerebellum was evaluated by transmission electron microscopy. Short- and long-term memories were assessed by novel object recognition test. The levels of endothelin-1 were measured by ELISA. Blood-brain barrier permeability was quantified by Evans Blue dye. After 14 days, animals exposed to intermittent hypoxia showed hypomyelination in cerebellum white matter and higher serum levels of endothelin-1. The short and long-term memories in novel object recognition test was impaired in the group exposed to intermittent hypoxia as compared to controls. Blood-brain barrier permeability was similar between the groups. These results indicated that hypomyelination and impairment of short- and long-term working memories occurred in C57BL mice after 14 days of intermittent hypoxia mimicking sleep apnea. Copyright © 2014 Elsevier B.V. All rights reserved.
In vitro blood-brain barrier models: current and perspective technologies.

PubMed

Naik, Pooja; Cucullo, Luca

2012-04-01

Even in the 21st century, studies aimed at characterizing the pathological paradigms associated with the development and progression of central nervous system diseases are primarily performed in laboratory animals. However, limited translational significance, high cost, and labor to develop the appropriate model (e.g., transgenic or inbred strains) have favored parallel in vitro approaches. In vitro models are of particular interest for cerebrovascular studies of the blood-brain barrier (BBB), which plays a critical role in maintaining the brain homeostasis and neuronal functions. Because the BBB dynamically responds to many events associated with rheological and systemic impairments (e.g., hypoperfusion), including the exposure of potentially harmful xenobiotics, the development of more sophisticated artificial systems capable of replicating the vascular properties of the brain microcapillaries are becoming a major focus in basic, translational, and pharmaceutical research. In vitro BBB models are valuable and easy to use supporting tools that can precede and complement animal and human studies. In this article, we provide a detailed review and analysis of currently available in vitro BBB models ranging from static culture systems to the most advanced flow-based and three-dimensional coculture apparatus. We also discuss recent and perspective developments in this ever expanding research field. Copyright © 2011 Wiley Periodicals, Inc.
Brain coordination dynamics: True and false faces of phase synchrony and metastability

PubMed Central

Tognoli, Emmanuelle; Kelso, J.A. Scott

2009-01-01

Understanding the coordination of multiple parts in a complex system such as the brain is a fundamental challenge. We present a theoretical model of cortical coordination dynamics that shows how brain areas may cooperate (integration) and at the same time retain their functional specificity (segregation). This model expresses a range of desirable properties that the brain is known to exhibit, including self-organization, multi-functionality, metastability and switching. Empirically, the model motivates a thorough investigation of collective phase relationships among brain oscillations in neurophysiological data. The most serious obstacle to interpreting coupled oscillations as genuine evidence of inter-areal coordination in the brain stems from volume conduction of electrical fields. Spurious coupling due to volume conduction gives rise to zero-lag (inphase) and antiphase synchronization whose magnitude and persistence obscure the subtle expression of real synchrony. Through forward modeling and the help of a novel colorimetric method, we show how true synchronization can be deciphered from continuous EEG patterns. Developing empirical efforts along the lines of continuous EEG analysis constitutes a major response to the challenge of understanding how different brain areas work together. Key predictions of cortical coordination dynamics can now be tested thereby revealing the essential modus operandi of the intact living brain. PMID:18938209
High Intensity Focused Ultrasound: A Novel Model of Mild Traumatic Brain Injury

DTIC Science & Technology

2013-11-07

RE, Melo B, Christensen B, Ngo L-A, Monette G, Bradbury C. 2008. Measuring premorbid IQ in traumatic brain injury: An examination of the validity of...High Intensity Focused Ultrasound: A Novel Model of Mild Traumatic Brain Injury by Brendan J. Finton Thesis...Mild Traumatic Brain Injury" is appropriately acknowledged and, beyond brief excerpts, is with the permission of the copyright owner. Brendan J
Genetic mouse models of brain ageing and Alzheimer's disease.

PubMed

Bilkei-Gorzo, Andras

2014-05-01

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

PubMed

Schoenfeld-Tacher, Regina M; Horn, Timothy J; Scheviak, Tyler A; Royal, Kenneth D; Hudson, Lola C

Physical specimens are essential to the teaching of veterinary anatomy. While fresh and fixed cadavers have long been the medium of choice, plastinated specimens have gained widespread acceptance as adjuncts to dissection materials. Even though the plastination process increases the durability of specimens, these are still derived from animal tissues and require periodic replacement if used by students on a regular basis. This study investigated the use of three-dimensional additively manufactured (3D AM) models (colloquially referred to as 3D-printed models) of the canine brain as a replacement for plastinated or formalin-fixed brains. The models investigated were built based on a micro-MRI of a single canine brain and have numerous practical advantages, such as durability, lower cost over time, and reduction of animal use. The effectiveness of the models was assessed by comparing performance among students who were instructed using either plastinated brains or 3D AM models. This study used propensity score matching to generate similar pairs of students. Pairings were based on gender and initial anatomy performance across two consecutive classes of first-year veterinary students. Students' performance on a practical neuroanatomy exam was compared, and no significant differences were found in scores based on the type of material (3D AM models or plastinated specimens) used for instruction. Students in both groups were equally able to identify neuroanatomical structures on cadaveric material, as well as respond to questions involving application of neuroanatomy knowledge. Therefore, we postulate that 3D AM canine brain models are an acceptable alternative to plastinated specimens in teaching veterinary neuroanatomy.
Pig Brain Mitochondria as a Biological Model for Study of Mitochondrial Respiration.

PubMed

Fišar, Z; Hroudová, J

2016-01-01

Oxidative phosphorylation is a key process of intracellular energy transfer by which mitochondria produce ATP. Isolated mitochondria serve as a biological model for understanding the mitochondrial respiration control, effects of various biologically active substances, and pathophysiology of mitochondrial diseases. The aim of our study was to evaluate pig brain mitochondria as a proper biological model for investigation of activity of the mitochondrial electron transport chain. Oxygen consumption rates of isolated pig brain mitochondria were measured using high-resolution respirometry. Mitochondrial respiration of crude mitochondrial fraction, mitochondria purified in sucrose gradient, and mitochondria purified in Percoll gradient were assayed as a function of storage time. Oxygen flux and various mitochondrial respiratory control ratios were not changed within two days of mitochondria storage on ice. Leak respiration was found higher and Complex I-linked respiration lower in purified mitochondria compared to the crude mitochondrial fraction. Damage to both outer and inner mitochondrial membrane caused by the isolation procedure was the greatest after purification in a sucrose gradient. We confirmed that pig brain mitochondria can serve as a biological model for investigation of mitochondrial respiration. The advantage of this biological model is the stability of respiratory parameters for more than 48 h and the possibility to isolate large amounts of mitochondria from specific brain areas without the need to kill laboratory animals. We suggest the use of high-resolution respirometry of pig brain mitochondria for research of the neuroprotective effects and/or mitochondrial toxicity of new medical drugs.
Data and Model Integration Promoting Interdisciplinarity

NASA Astrophysics Data System (ADS)

Koike, T.

2014-12-01

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

PubMed

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

2017-01-01

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.
Integration of Multidisciplinary Sensory Data:

PubMed Central

Miller, Perry L.; Nadkarni, Prakash; Singer, Michael; Marenco, Luis; Hines, Michael; Shepherd, Gordon

2001-01-01

The paper provides an overview of neuroinformatics research at Yale University being performed as part of the national Human Brain Project. This research is exploring the integration of multidisciplinary sensory data, using the olfactory system as a model domain. The neuroinformatics activities fall into three main areas: 1) building databases and related tools that support experimental olfactory research at Yale and can also serve as resources for the field as a whole, 2) using computer models (molecular models and neuronal models) to help understand data being collected experimentally and to help guide further laboratory experiments, 3) performing basic neuroinformatics research to develop new informatics technologies, including a flexible data model (EAV/CR, entity-attribute-value with classes and relationships) designed to facilitate the integration of diverse heterogeneous data within a single unifying framework. PMID:11141511
Endothelium-targeted overexpression of heat shock protein 27 ameliorates blood–brain barrier disruption after ischemic brain injury

PubMed Central

Jiang, Xiaoyan; Zhang, Lili; Pu, Hongjian; Hu, Xiaoming; Zhang, Wenting; Cai, Wei; Gao, Yanqin; Leak, Rehana K.; Keep, Richard F.; Bennett, Michael V. L.; Chen, Jun

2017-01-01

The damage borne by the endothelial cells (ECs) forming the blood–brain barrier (BBB) during ischemic stroke and other neurological conditions disrupts the structure and function of the neurovascular unit and contributes to poor patient outcomes. We recently reported that structural aberrations in brain microvascular ECs—namely, uncontrolled actin polymerization and subsequent disassembly of junctional proteins, are a possible cause of the early onset BBB breach that arises within 30–60 min of reperfusion after transient focal ischemia. Here, we investigated the role of heat shock protein 27 (HSP27) as a direct inhibitor of actin polymerization and protectant against BBB disruption after ischemia/reperfusion (I/R). Using in vivo and in vitro models, we found that targeted overexpression of HSP27 specifically within ECs—but not within neurons—ameliorated BBB impairment 1–24 h after I/R. Mechanistically, HSP27 suppressed I/R-induced aberrant actin polymerization, stress fiber formation, and junctional protein translocation in brain microvascular ECs, independent of its protective actions against cell death. By preserving BBB integrity after I/R, EC-targeted HSP27 overexpression attenuated the infiltration of potentially destructive neutrophils and macrophages into brain parenchyma, thereby improving long-term stroke outcome. Notably, early poststroke administration of HSP27 attached to a cell-penetrating transduction domain (TAT-HSP27) rapidly elevated HSP27 levels in brain microvessels and ameliorated I/R-induced BBB disruption and subsequent neurological deficits. Thus, the present study demonstrates that HSP27 can function at the EC level to preserve BBB integrity after I/R brain injury. HSP27 may be a therapeutic agent for ischemic stroke and other neurological conditions involving BBB breakdown. PMID:28137866
Transforming Research and Clinical Knowledge in Traumatic Brain Injury

DTIC Science & Technology

2016-12-01

Szuflita, N., Orman, J., and Schwab, K. (2010). Advancing integrated research in psychological health and traumatic brain injury: common data ele- ments...Szuflita N, Orman J, et al. Advancing Integrated Research in Psychological Health and Traumatic Brain Injury: Common Data Elements. Arch Phys Med Rehabil...R, Gleason T, et al. Advancing integrated research in psychological health and traumatic brain injury: common data elements. Arch Phys Med Rehabil
SU-E-T-549: Modeling Relative Biological Effectiveness of Protons for Radiation Induced Brain Necrosis

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

Mirkovic, D; Peeler, C; Grosshans, D

Purpose: To develop a model of the relative biological effectiveness (RBE) of protons as a function of dose and linear energy transfer (LET) for induction of brain necrosis using clinical data. Methods: In this study, treatment planning information was exported from a clinical treatment planning system (TPS) and used to construct a detailed Monte Carlo model of the patient and the beam delivery system. The physical proton dose and LET were computed in each voxel of the patient volume using Monte Carlo particle transport. A follow-up magnetic resonance imaging (MRI) study registered to the treatment planning CT was used tomore » determine the region of the necrosis in the brain volume. Both, the whole brain and the necrosis volumes were segmented from the computed tomography (CT) dataset using the contours drawn by a physician and the corresponding voxels were binned with respect to dose and LET. The brain necrosis probability was computed as a function of dose and LET by dividing the total volume of all necrosis voxels with a given dose and LET with the corresponding total brain volume resulting in a set of NTCP-like curves (probability as a function of dose parameterized by LET). Results: The resulting model shows dependence on both dose and LET indicating the weakness of the constant RBE model for describing the brain toxicity. To the best of our knowledge the constant RBE model is currently used in all clinical applications which may Result in increased rate of brain toxicities in patients treated with protons. Conclusion: Further studies are needed to develop more accurate brain toxicity models for patients treated with protons and other heavy ions.« less
A mathematical model of endovascular heat transfer for human brain cooling

NASA Astrophysics Data System (ADS)

Salsac, Anne-Virginie; Lasheras, Juan Carlos; Yon, Steven; Magers, Mike; Dobak, John

2000-11-01

Selective cooling of the brain has been shown to exhibit protective effects in cerebral ischemia, trauma, and spinal injury/ischemia. A multi-compartment, unsteady thermal model of the response of the human brain to endovascular cooling is discussed and its results compared to recent experimental data conducted with sheep and other mammals. The model formulation is based on the extension of the bioheat equation, originally proposed by Pennes(1) and later modified by Wissler(2), Stolwijk(3) and Werner and Webb(4). The temporal response of the brain temperature and that of the various body compartments to the cooling of the blood flowing through the common carotid artery is calculated under various scenarios. The effect of the boundary conditions as well as the closure assumptions used in the model, i.e. perfusion rate, metabolism heat production, etc. on the cooling rate of the brain are systematically investigated. (1) Pennes H. H., “Analysis of tissue and arterial blood temperature in the resting forearm.” J. Appl. Physiol. 1: 93-122, 1948. (2) Wissler E. H., “Steady-state temperature distribution in man”, J. Appl. Physiol., 16: 764-740, 1961. (3) Stolwick J. A. J., “Mathematical model of thermoregulation” in “Physiological and behavioral temperature regulation”, edited by J. D. Hardy, A. P. Gagge and A. J. Stolwijk, Charles C. Thomas Publisher, Springfiels, Ill., 703-721, 1971. (4) Werner J., Webb P., “A six-cylinder model of human thermoregulation for general use on personal computers”, Ann. Physiol. Anthrop., 12(3): 123-134, 1993.

System integration of wind and solar power in integrated assessment models: A cross-model evaluation of new approaches

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

Pietzcker, Robert C.; Ueckerdt, Falko; Carrara, Samuel

Mitigation-Process Integrated Assessment Models (MP-IAMs) are used to analyze long-term transformation pathways of the energy system required to achieve stringent climate change mitigation targets. Due to their substantial temporal and spatial aggregation, IAMs cannot explicitly represent all detailed challenges of integrating the variable renewable energies (VRE) wind and solar in power systems, but rather rely on parameterized modeling approaches. In the ADVANCE project, six international modeling teams have developed new approaches to improve the representation of power sector dynamics and VRE integration in IAMs. In this study, we qualitatively and quantitatively evaluate the last years' modeling progress and study themore » impact of VRE integration modeling on VRE deployment in IAM scenarios. For a comprehensive and transparent qualitative evaluation, we first develop a framework of 18 features of power sector dynamics and VRE integration. We then apply this framework to the newly-developed modeling approaches to derive a detailed map of strengths and limitations of the different approaches. For the quantitative evaluation, we compare the IAMs to the detailed hourly-resolution power sector model REMIX. We find that the new modeling approaches manage to represent a large number of features of the power sector, and the numerical results are in reasonable agreement with those derived from the detailed power sector model. Updating the power sector representation and the cost and resources of wind and solar substantially increased wind and solar shares across models: Under a carbon price of 30$/tCO2 in 2020 (increasing by 5% per year), the model-average cost-minimizing VRE share over the period 2050-2100 is 62% of electricity generation, 24%-points higher than with the old model version.« less
The Brain-Targeted Teaching Model for 21st-Century Schools

ERIC Educational Resources Information Center

Hardiman, Mariale

2012-01-01

"The Brain-Targeted Teaching Model for 21st-Century Schools" serves as a bridge between research and practice by providing a cohesive, proven, and usable model of effective instruction. Compatible with other professional development programs, this model shows how to apply relevant research from educational and cognitive neuroscience to classroom…
Sensitivity analysis of brain morphometry based on MRI-derived surface models

NASA Astrophysics Data System (ADS)

Klein, Gregory J.; Teng, Xia; Schoenemann, P. T.; Budinger, Thomas F.

1998-07-01

Quantification of brain structure is important for evaluating changes in brain size with growth and aging and for characterizing neurodegeneration disorders. Previous quantification efforts using ex vivo techniques suffered considerable error due to shrinkage of the cerebrum after extraction from the skull, deformation of slices during sectioning, and numerous other factors. In vivo imaging studies of brain anatomy avoid these problems and allow repetitive studies following progression of brain structure changes due to disease or natural processes. We have developed a methodology for obtaining triangular mesh models of the cortical surface from MRI brain datasets. The cortex is segmented from nonbrain tissue using a 2D region-growing technique combined with occasional manual edits. Once segmented, thresholding and image morphological operations (erosions and openings) are used to expose the regions between adjacent surfaces in deep cortical folds. A 2D region- following procedure is then used to find a set of contours outlining the cortical boundary on each slice. The contours on all slices are tiled together to form a closed triangular mesh model approximating the cortical surface. This model can be used for calculation of cortical surface area and volume, as well as other parameters of interest. Except for the initial segmentation of the cortex from the skull, the technique is automatic and requires only modest computation time on modern workstations. Though the use of image data avoids many of the pitfalls of ex vivo and sectioning techniques, our MRI-based technique is still vulnerable to errors that may impact the accuracy of estimated brain structure parameters. Potential inaccuracies include segmentation errors due to incorrect thresholding, missed deep sulcal surfaces, falsely segmented holes due to image noise and surface tiling artifacts. The focus of this paper is the characterization of these errors and how they affect measurements of cortical surface
Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

PubMed

Voss, Michelle W; Weng, Timothy B; Burzynska, Agnieszka Z; Wong, Chelsea N; Cooke, Gillian E; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P; Olson, Erin A; McAuley, Edward; Kramer, Arthur F

2016-05-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.
Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

PubMed Central

Voss, Michelle W.; Weng, Timothy B.; Burzynska, Agnieszka Z.; Wong, Chelsea N.; Cooke, Gillian E.; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P.; Olson, Erin A.; McAuley, Edward; Kramer, Arthur F.

2015-01-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the Default Mode Network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. PMID:26493108
An automatic rat brain extraction method based on a deformable surface model.

PubMed

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.
AlzPharm: integration of neurodegeneration data using RDF.

PubMed

Lam, Hugo Y K; Marenco, Luis; Clark, Tim; Gao, Yong; Kinoshita, June; Shepherd, Gordon; Miller, Perry; Wu, Elizabeth; Wong, Gwendolyn T; Liu, Nian; Crasto, Chiquito; Morse, Thomas; Stephens, Susie; Cheung, Kei-Hoi

2007-05-09

Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web
AlzPharm: integration of neurodegeneration data using RDF

PubMed Central

Lam, Hugo YK; Marenco, Luis; Clark, Tim; Gao, Yong; Kinoshita, June; Shepherd, Gordon; Miller, Perry; Wu, Elizabeth; Wong, Gwendolyn T; Liu, Nian; Crasto, Chiquito; Morse, Thomas; Stephens, Susie; Cheung, Kei-Hoi

2007-01-01

Background Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. Results We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. Conclusion Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results
Evaluation of brain targeting and mucosal integrity of nasally administrated nanostructured carriers of a CNS active drug, clonazepam.

PubMed

Abdel-Bar, Hend Mohamed; Abdel-Reheem, Amal Youssef; Awad, Gehanne Abdel Samie; Mortada, Nahed Daoud

2013-01-01

The aim of the study was to target clonazepam, a CNS active drug, to the brain through the non-invasive intranasal (in) route using of nanocarriers with proven safety in clonazepam nanocarriers were prepared by mixing isopropyl myristate, Tween 80, Cremophor EL or lecithin, polyethylene glycol 200, propylene glycol or ethanol in different ratios with water. in-vitro characterization of the nanocarriers was done by various methods including: polarized light microscopy, particle size determination, viscosity measurements and drug release studies. in-vivo study comparing intranasal and intravenous administration was performed. The drug targeting efficiency (DTE %) and direct nose to brain transport percentage (DTP %) were calculated and nasal integrity assessment was carried out. The obtained formulae had particle size below 100 nm favoring rapid direct nose to brain transport and the time for 100% drug release (T100%) depended on systems composition. Plasma Tmax of clonazepam nanostructured carriers varied from 10-30 min., while their brain Tmax did not exceed 10 min, in comparison with 30 min for iv solution. Although there was no significant difference (p>0.05) between the plasma AUC0-∞ of the different tested nanocarriers and intravenous one, the increase in brain AUC 0 -∞ of different nasal formulations in comparison to that of iv administration (3.6 -7.2 fold) confirms direct nose to brain transport via olfactory region. Furthermore, DTE and DTP% confirmed brain targeting of clonazepam following intranasal administration. The results confirmed that intranasal nanocarriers were proved to be safe alternative for iv clonazepam delivery with rapid nose to brain transport.
Vocational rehabilitation after traumatic brain injury: models and services.

PubMed

Tyerman, Andy

2012-01-01

A recent systematic review suggests that around 40% of people with traumatic brain injury (TBI) return to work (RTW). Yet in the U.K. currently only a small minority of people with TBI receive vocational rehabilitation (VR) to enable a RTW. Agencies with an interest in developing such services are likely to favour different models of VR. The primary objective of this paper was to review models of specialist VR after TBI and their outcomes to inform service development across relevant agencies. A literature review on VR after TBI was undertaken in MEDLINE, EMBASE and PsychINFO (from 1967 to date). Papers reporting models of VR were selected for more detailed consideration. Illustrative examples of VR models are outlined: brain injury rehabilitation programmes with added VR elements, VR models adapted for TBI, case coordination/resource facilitation models, and consumer-directed models. Models differ, both within and across these four broad categories, in provision of core TBI rehabilitation, work preparation, work trials and supported placements. Methodological variation limits direct comparison of outcomes across models with few comparative or controlled studies. There is evidence to support the benefits of a wide range of models of specialist VR after TBI. However, there remains a need for controlled studies to inform service development and more evidence on cost-effectiveness to inform funding decisions.
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…
Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult.

PubMed

Paolini, Brielle M; Laurienti, Paul J; Simpson, Sean L; Burdette, Jonathan H; Lyday, Robert G; Rejeski, W Jack

2015-01-01

Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL) remain popular, the rate of success is highly variable. Clearly, self-regulation of eating behavior is a challenge and patterns of activity across the brain may be an important determinant of success. The current study prospectively examined whether integration across the Hot-State Brain Network of Appetite (HBN-A) predicts WL after 6-months of treatment in older adults. Our metric for network integration was global efficiency (GE). The present work is a sub-study (n = 56) of an ongoing randomized clinical trial involving WL. Imaging involved a baseline food-cue visualization functional MRI (fMRI) scan following an overnight fast. Using graph theory to build functional brain networks, we demonstrated that regions of the HBN-A (insula, anterior cingulate cortex (ACC), superior temporal pole (STP), amygdala and the parahippocampal gyrus) were highly integrated as evidenced by the results of a principal component analysis (PCA). After accounting for known correlates of WL (baseline weight, age, sex, and self-regulatory efficacy) and treatment condition, which together contributed 36.9% of the variance in WL, greater GE in the HBN-A was associated with an additional 19% of the variance. The ACC of the HBN-A was the primary driver of this effect, accounting for 14.5% of the variance in WL when entered in a stepwise regression following the covariates, p = 0.0001. The HBN-A is comprised of limbic regions important in the processing of emotions and visceral sensations and the ACC is key for translating such processing into behavioral consequences. The improved integration of these regions may enhance awareness of body and emotional states leading to more successful self-regulation and to greater WL. This is the first study among older adults to prospectively demonstrate that, following an overnight fast, GE of the HBN-A during a food visualization task is predictive of
Quantitative analysis of nanoparticle transport through in vitro blood-brain barrier models

PubMed Central

Åberg, Christoffer

2016-01-01

ABSTRACT Nanoparticle transport through the blood-brain barrier has received much attention of late, both from the point of view of nano-enabled drug delivery, as well as due to concerns about unintended exposure of nanomaterials to humans and other organisms. In vitro models play a lead role in efforts to understand the extent of transport through the blood-brain barrier, but unique features of the nanoscale challenge their direct adaptation. Here we highlight some of the differences compared to molecular species when utilizing in vitro blood-brain barrier models for nanoparticle studies. Issues that may arise with transwell systems are discussed, together with some potential alternative methodologies. We also briefly review the biomolecular corona concept and its importance for how nanoparticles interact with the blood-brain barrier. We end with considering future directions, including indirect effects and application of shear and fluidics-technologies. PMID:27141425
Optimizing Experimental Design for Comparing Models of Brain Function

PubMed Central

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

2011-01-01

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

NASA Technical Reports Server (NTRS)

Wozny, Michael J.

1987-01-01

The workshop on the Integration of Finite Element Modeling with Geometric Modeling was held on 12 May 1987. It was held to discuss the geometric modeling requirements of the finite element modeling process and to better understand the technical aspects of the integration of these two areas. The 11 papers are presented except for one for which only the abstract is given.
Deep Brain Stimulation

PubMed Central

Lyketsos, Constantine G.; Pendergrass, Jo Cara; Lozano, Andres M.

2012-01-01

Recent studies have identified an association between memory deficits and defects of the integrated neuronal cortical areas known collectively as the default mode network. It is conceivable that the amyloid deposition or other molecular abnormalities seen in patients with Alzheimer’s disease may interfere with this network and disrupt neuronal circuits beyond the localized brain areas. Therefore, Alzheimer’s disease may be both a degenerative disease and a broader system-level disorder affecting integrated neuronal pathways involved in memory. In this paper, we describe the rationale and provide some evidence to support the study of deep brain stimulation of the hippocampal fornix as a novel treatment to improve neuronal circuitry within these integrated networks and thereby sustain memory function in early Alzheimer’s disease. PMID:23346514
Modular Architecture for Integrated Model-Based Decision Support.

PubMed

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.
Random-Walk Model of Diffusion in Three Dimensions in Brain Extracellular Space: Comparison with Microfiberoptic Photobleaching Measurements

PubMed Central

Jin, Songwan; Zador, Zsolt; Verkman, A. S.

2008-01-01

Diffusion through the extracellular space (ECS) in brain is important in drug delivery, intercellular communication, and extracellular ionic buffering. The ECS comprises ∼20% of brain parenchymal volume and contains cell-cell gaps ∼50 nm. We developed a random-walk model to simulate macromolecule diffusion in brain ECS in three dimensions using realistic ECS dimensions. Model inputs included ECS volume fraction (α), cell size, cell-cell gap geometry, intercellular lake (expanded regions of brain ECS) dimensions, and molecular size of the diffusing solute. Model output was relative solute diffusion in water versus brain ECS (Do/D). Experimental Do/D for comparison with model predictions was measured using a microfiberoptic fluorescence photobleaching method involving stereotaxic insertion of a micron-size optical fiber into mouse brain. Do/D for the small solute calcein in different regions of brain was in the range 3.0–4.1, and increased with brain cell swelling after water intoxication. Do/D also increased with increasing size of the diffusing solute, particularly in deep brain nuclei. Simulations of measured Do/D using realistic α, cell size and cell-cell gap required the presence of intercellular lakes at multicell contact points, and the contact length of cell-cell gaps to be least 50-fold smaller than cell size. The model accurately predicted Do/D for different solute sizes. Also, the modeling showed unanticipated effects on Do/D of changing ECS and cell dimensions that implicated solute trapping by lakes. Our model establishes the geometric constraints to account quantitatively for the relatively modest slowing of solute and macromolecule diffusion in brain ECS. PMID:18469079
Random-walk model of diffusion in three dimensions in brain extracellular space: comparison with microfiberoptic photobleaching measurements.

PubMed

Jin, Songwan; Zador, Zsolt; Verkman, A S

2008-08-01

Diffusion through the extracellular space (ECS) in brain is important in drug delivery, intercellular communication, and extracellular ionic buffering. The ECS comprises approximately 20% of brain parenchymal volume and contains cell-cell gaps approximately 50 nm. We developed a random-walk model to simulate macromolecule diffusion in brain ECS in three dimensions using realistic ECS dimensions. Model inputs included ECS volume fraction (alpha), cell size, cell-cell gap geometry, intercellular lake (expanded regions of brain ECS) dimensions, and molecular size of the diffusing solute. Model output was relative solute diffusion in water versus brain ECS (D(o)/D). Experimental D(o)/D for comparison with model predictions was measured using a microfiberoptic fluorescence photobleaching method involving stereotaxic insertion of a micron-size optical fiber into mouse brain. D(o)/D for the small solute calcein in different regions of brain was in the range 3.0-4.1, and increased with brain cell swelling after water intoxication. D(o)/D also increased with increasing size of the diffusing solute, particularly in deep brain nuclei. Simulations of measured D(o)/D using realistic alpha, cell size and cell-cell gap required the presence of intercellular lakes at multicell contact points, and the contact length of cell-cell gaps to be least 50-fold smaller than cell size. The model accurately predicted D(o)/D for different solute sizes. Also, the modeling showed unanticipated effects on D(o)/D of changing ECS and cell dimensions that implicated solute trapping by lakes. Our model establishes the geometric constraints to account quantitatively for the relatively modest slowing of solute and macromolecule diffusion in brain ECS.
Modeling integrated biomass gasification business concepts

Treesearch

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

2011-01-01

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

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