State-related functional integration and functional segregation brain networks in schizophrenia.

Science.gov (United States)

Yu, Qingbao; Sui, Jing; Kiehl, Kent A; Pearlson, Godfrey; Calhoun, Vince D

2013-11-01

Altered topological properties of brain connectivity networks have emerged as important features of schizophrenia. The aim of this study was to investigate how the state-related modulations to graph measures of functional integration and functional segregation brain networks are disrupted in schizophrenia. Firstly, resting state and auditory oddball discrimination (AOD) fMRI data of healthy controls (HCs) and schizophrenia patients (SZs) were decomposed into spatially independent components (ICs) by group independent component analysis (ICA). Then, weighted positive and negative functional integration (inter-component networks) and functional segregation (intra-component networks) brain networks were built in each subject. Subsequently, connectivity strength, clustering coefficient, and global efficiency of all brain networks were statistically compared between groups (HCs and SZs) in each state and between states (rest and AOD) within group. We found that graph measures of negative functional integration brain network and several positive functional segregation brain networks were altered in schizophrenia during AOD task. The metrics of positive functional integration brain network and one positive functional segregation brain network were higher during the resting state than during the AOD task only in HCs. These findings imply that state-related characteristics of both functional integration and functional segregation brain networks are impaired in schizophrenia which provides new insight into the altered brain performance in this brain disorder. © 2013.

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

Science.gov (United States)

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.

Imatinib preserves blood-brain barrier integrity following experimental subarachnoid hemorrhage in rats.

Science.gov (United States)

Zhan, Yan; Krafft, Paul R; Lekic, Tim; Ma, Qingyi; Souvenir, Rhonda; Zhang, John H; Tang, Jiping

2015-01-01

Blood-brain barrier (BBB) disruption and consequent edema formation contribute to the development of early brain injury following subarachnoid hemorrhage (SAH). Various cerebrovascular insults result in increased platelet-derived growth factor receptor (PDGFR)-α stimulation, which has been linked to BBB breakdown and edema formation. This study examines whether imatinib, a PDGFR inhibitor, can preserve BBB integrity in a rat endovascular perforation SAH model. Imatinib (40 or 120 mg/kg) or a vehicle was administered intraperitoneally at 1 hr after SAH induction. BBB leakage, brain edema, and neurological deficits were evaluated. Total and phosphorylated protein expressions of PDGFR-α, c-Src, c-Jun N-terminal kinase (JNK), and c-Jun were measured, and enzymatic activities of matrix metalloproteinase (MMP)-2 and MMP-9 were determined in the injured brain. Imatinib treatment significantly ameliorated BBB leakage and edema formation 24 hr after SAH, which was paralleled by improved neurological functions. Decreased brain expressions of phosphorylated PDGFR-α, c-Src, JNK, and c-Jun as well as reduced MMP-9 activities were found in treated animals. PDGFR-α inhibition preserved BBB integrity following experimental SAH; however, the protective mechanisms remain to be elucidated. Targeting PDGFR-α signaling might be advantageous to ameliorate early brain injury following SAH. © 2014 Wiley Periodicals, Inc.

Human midsagittal brain shape variation: patterns, allometry and integration

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

2010-01-01

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

Cognitive Models as Bridge between Brain and Behavior.

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Love, Bradley C

2016-04-01

How can disparate neural and behavioral measures be integrated? Turner and colleagues propose joint modeling as a solution. Joint modeling mutually constrains the interpretation of brain and behavioral measures by exploiting their covariation structure. Simultaneous estimation allows for more accurate prediction than would be possible by considering these measures in isolation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Nano-Modeling and Computation in Bio and Brain Dynamics

Directory of Open Access Journals (Sweden)

Paolo Di Sia

2016-04-01

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

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

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T. K. Das

2014-01-01

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

Brain activity patterns uniquely supporting visual feature integration after traumatic brain injury

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Anjali eRaja Beharelle

2011-12-01

Full Text Available Traumatic brain injury (TBI patients typically respond more slowly and with more variability than controls during tasks of attention requiring speeded reaction time. These behavioral changes are attributable, at least in part, to diffuse axonal injury (DAI, which affects integrated processing in distributed systems. Here we use a multivariate method sensitive to distributed neural activity to compare brain activity patterns of patients with chronic phase moderate-to-severe TBI to those of controls during performance on a visual feature-integration task assessing complex attentional processes that has previously shown sensitivity to TBI. The TBI patients were carefully screened to be free of large focal lesions that can affect performance and brain activation independently of DAI. The task required subjects to hold either one or three features of a target in mind while suppressing responses to distracting information. In controls, the multi-feature condition activated a distributed network including limbic, prefrontal, and medial temporal structures. TBI patients engaged this same network in the single-feature and baseline conditions. In multi-feature presentations, TBI patients alone activated additional frontal, parietal, and occipital regions. These results are consistent with neuroimaging studies using tasks assessing different cognitive domains, where increased spread of brain activity changes was associated with TBI. Our results also extend previous findings that brain activity for relatively moderate task demands in TBI patients is similar to that associated with of high task demands in controls.

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

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Cristiano eCuppini

2011-05-01

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

The Functional Segregation and Integration Model: Mixture Model Representations of Consistent and Variable Group-Level Connectivity in fMRI

DEFF Research Database (Denmark)

Churchill, Nathan William; Madsen, Kristoffer Hougaard; Mørup, Morten

2016-01-01

flexibility: they only estimate segregated structure and do not model interregional functional connectivity, nor do they account for network variability across voxels or between subjects. To address these issues, this letter develops the functional segregation and integration model (FSIM). This extension......The brain consists of specialized cortical regions that exchange information between each other, reflecting a combination of segregated (local) and integrated (distributed) processes that define brain function. Functional magnetic resonance imaging (fMRI) is widely used to characterize...... brain regions where network expression predicts subject age in the experimental data. Thus, the FSIM is effective at summarizing functional connectivity structure in group-level fMRI, with applications in modeling the relationships between network variability and behavioral/demographic variables....

Comparison of two integration methods for dynamic causal modeling of electrophysiological data.

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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

Finding influential nodes for integration in brain networks using optimal percolation theory.

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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.

Models of neural dynamics in brain information processing - the developments of 'the decade'

International Nuclear Information System (INIS)

Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B; Ivanitskii, Genrikh R

2002-01-01

Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

Whole brain helical Tomotherapy with integrated boost for brain metastases in patients with malignant melanoma–a randomized trial

International Nuclear Information System (INIS)

Hauswald, Henrik; Habl, Gregor; Krug, David; Kehle, Denise; Combs, Stephanie E; Bermejo, Justo Lorenzo; Debus, Jürgen; Sterzing, Florian

2013-01-01

Patients with malignant melanoma may develop brain metastases during the course of the disease, requiring radiotherapeutic treatment. In patients with 1–3 brain metastases, radiosurgery has been established as a treatment option besides surgery. For patients with 4 or more brain metastases, whole brain radiotherapy is considered the standard treatment. In certain patients with brain metastases, radiation treatment using whole brain helical Tomotherapy with integrated boost and hippocampal-sparing may improve prognosis of these patients. The present prospective, randomized two-armed trial aims to exploratory investigate the treatment response to conventional whole brain radiotherapy applying 30 Gy in 10 fractions versus whole brain helical Tomotherapy applying 30 Gy in 10 fractions with an integrated boost of 50 Gy to the brain metastases as well as hippocampal-sparing in patients with brain metastases from malignant melanoma. The main inclusion criteria include magnetic resonance imaging confirmed brain metastases from a histopathologically confirmed malignant melanoma in patients with a minimum age of 18 years. The main exclusion criteria include a previous radiotherapy of the brain and not having recovered from acute high-grade toxicities of prior therapies. The primary endpoint is treatment-related toxicity. Secondary endpoints include imaging response, local and loco-regional progression-free survival, overall survival and quality of life

Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

Directory of Open Access Journals (Sweden)

Jill X O'Reilly

2013-09-01

Full Text Available A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI we showed that activity in two brain systems (typically associated with reward learning and motor control could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.

Brain Network Modelling

DEFF Research Database (Denmark)

Andersen, Kasper Winther

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

Multiscale modeling and simulation of brain blood flow

Energy Technology Data Exchange (ETDEWEB)

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

2016-02-15

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

Brain/MINDS: brain-mapping project in Japan

Science.gov (United States)

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

Brain/MINDS: brain-mapping project in Japan.

Science.gov (United States)

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-05-19

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.

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

Science.gov (United States)

2015-12-22

AFRL-AFOSR-VA-TR-2016-0037 An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States Adrian Lee UNIVERSITY OF WASHINGTON...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.

Science.gov (United States)

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…

Models of neural dynamics in brain information processing - the developments of 'the decade'

Energy Technology Data Exchange (ETDEWEB)

Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B [Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation); Ivanitskii, Genrikh R [Institute for Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation)

2002-10-31

Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

Science.gov (United States)

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

2015-08-01

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

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

DEFF Research Database (Denmark)

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

2014-01-01

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

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

Science.gov (United States)

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

2014-02-01

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

Functional brain networks underlying detection and integration of disconfirmatory evidence.

Science.gov (United States)

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

2015-05-15

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

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

Science.gov (United States)

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

2018-06-01

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.

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

Science.gov (United States)

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

2015-03-01

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

Schizophrenia: an integrated sociodevelopmental-cognitive model

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Zude Zhu

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

An integrated brain-behavior model for working memory.

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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

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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.

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

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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

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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.

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.

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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.

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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.

Recurrent network models for perfect temporal integration of fluctuating correlated inputs.

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Hiroshi Okamoto

2009-06-01

Full Text Available Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.

Endothelial β-Catenin Signaling Is Required for Maintaining Adult Blood-Brain Barrier Integrity and Central Nervous System Homeostasis.

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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

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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.

The modulation of neural gain facilitates a transition between functional segregation and integration in the brain.

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Shine, James M; Aburn, Matthew J; Breakspear, Michael; Poldrack, Russell A

2018-01-29

Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain directed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal 'rich club' regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain. © 2018, Shine et al.

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

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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.

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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

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

Directory of Open Access Journals (Sweden)

Silvia eSánchez-Ramón

2016-02-01

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

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

Science.gov (United States)

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

The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition.

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Cohen, Jessica R; D'Esposito, Mark

2016-11-30

A critical feature of the human brain that gives rise to complex cognition is its ability to reconfigure its network structure dynamically and adaptively in response to the environment. Existing research probing task-related reconfiguration of brain network structure has concluded that, although there are many similarities in network structure during an intrinsic, resting state and during the performance of a variety of cognitive tasks, there are meaningful differences as well. In this study, we related intrinsic, resting state network organization to reconfigured network organization during the performance of two tasks: a sequence tapping task, which is thought to probe motor execution and likely engages a single brain network, and an n-back task, which is thought to probe working memory and likely requires coordination across multiple networks. We implemented graph theoretical analyses using functional connectivity data from fMRI scans to calculate whole-brain measures of network organization in healthy young adults. We focused on quantifying measures of network segregation (modularity, system segregation, local efficiency, number of provincial hub nodes) and measures of network integration (global efficiency, number of connector hub nodes). Using these measures, we found converging evidence that local, within-network communication is critical for motor execution, whereas integrative, between-network communication is critical for working memory. These results confirm that the human brain has the remarkable ability to reconfigure its large-scale organization dynamically in response to current cognitive demands and that interpreting reconfiguration in terms of network segregation and integration may shed light on the optimal network structures underlying successful cognition. The dynamic nature of the human brain gives rise to the wide range of behaviors and cognition of which humans are capable. We collected fMRI data from healthy young adults and measured large

Early amplitude‐integrated electroencephalography for monitoring neonates at high risk for brain injury

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Gabriel Fernando Todeschi Variane

2017-09-01

Conclusion: This study supports previous results and demonstrates the utility of amplitude‐integrated electroencephalography for monitoring brain function and predicting early outcome in the studied groups of infants at high risk for brain injury.

Central Artery Stiffness, Baroreflex Sensitivity, and Brain White Matter Neuronal Fiber Integrity in Older Adults

OpenAIRE

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 cog...

A competitive integration model of exogenous and endogenous eye movements

NARCIS (Netherlands)

Meeter, M.; van der Stigchel, S.; Theeuwes, J.

2010-01-01

We present a model of the eye movement system in which the programming of an eye movement is the result of the competitive integration of information in the superior colliculi (SC). This brain area receives input from occipital cortex, the frontal eye fields, and the dorsolateral prefrontal cortex,

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

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Jürgen Rybak

2010-07-01

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

Dynamic monitoring of blood-brain barrier integrity using water exchange index (WEI) during mannitol and CO2 challenges in mouse brain.

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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.

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

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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.

Science.gov (United States)

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.

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

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

2017-12-01

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

Reduced integration and improved segregation of functional brain networks in Alzheimer's disease.

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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.

A prospective study to evaluate a new residential community reintegration programme for severe chronic brain injury: the Brain Integration Programme.

Science.gov (United States)

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.

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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.

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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

A mathematical model of brain glucose homeostasis

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Kimura Hidenori

2009-11-01

Full Text Available Abstract Background The physiological fact that a stable level of brain glucose is more important than that of blood glucose suggests that the ultimate goal of the glucose-insulin-glucagon (GIG regulatory system may be homeostasis of glucose concentration in the brain rather than in the circulation. Methods In order to demonstrate the relationship between brain glucose homeostasis and blood hyperglycemia in diabetes, a brain-oriented mathematical model was developed by considering the brain as the controlled object while the remaining body as the actuator. After approximating the body compartmentally, the concentration dynamics of glucose, as well as those of insulin and glucagon, are described in each compartment. The brain-endocrine crosstalk, which regulates blood glucose level for brain glucose homeostasis together with the peripheral interactions among glucose, insulin and glucagon, is modeled as a proportional feedback control of brain glucose. Correlated to the brain, long-term effects of psychological stress and effects of blood-brain-barrier (BBB adaptation to dysglycemia on the generation of hyperglycemia are also taken into account in the model. Results It is shown that simulation profiles obtained from the model are qualitatively or partially quantitatively consistent with clinical data, concerning the GIG regulatory system responses to bolus glucose, stepwise and continuous glucose infusion. Simulations also revealed that both stress and BBB adaptation contribute to the generation of hyperglycemia. Conclusion Simulations of the model of a healthy person under long-term severe stress demonstrated that feedback control of brain glucose concentration results in elevation of blood glucose level. In this paper, we try to suggest that hyperglycemia in diabetes may be a normal outcome of brain glucose homeostasis.

Functional integrity in children with anoxic brain injury from drowning.

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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.

Integrative structure modeling with the Integrative Modeling Platform.

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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.

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

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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.

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

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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.

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

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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.

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Cedric E Ginestet

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

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

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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

Theory and practice in sport psychology and motor behaviour needs to be constrained by integrative modelling of brain and behaviour.

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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.

Markers for blood-brain barrier integrity: how appropriate is Evans blue in the 21st century and what are the alternatives?

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Norman Ruthven Saunders

2015-10-01

Full Text Available 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 19th-Century. Their use 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 20th-Century was an important advance because its reaction product can be visualized at the electron microscopical level. Advantages and disadvantages 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, visualisable dextrans and radiolabelled molecules currently seems to be the most appropriate approach for qualitative and quantitative assessment of barrier integrity.

Brain Dynamics An Introduction to Models and Simualtions

CERN Document Server

Haken, Hermann

2008-01-01

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

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

International Nuclear Information System (INIS)

Christensen, D.

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-15

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

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

Science.gov (United States)

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.

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

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Laura Fanea

2012-01-01

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

ADRB2, brain white matter integrity and cognitive ageing in the Lothian Birth Cohort 1936.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2015-01-01

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

Reduced integration and improved segregation of functional brain networks in Alzheimer’s disease

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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.

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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.

Central Artery Stiffness, Baroreflex Sensitivity, and Brain White Matter Neuronal Fiber Integrity in Older Adults

Science.gov (United States)

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

Breaking symmetry: the zebrafish as a model for understanding left-right asymmetry in the developing brain.

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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

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Christof Seiler

2017-12-01

Full Text Available 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.

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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

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Jose Víctor Orón Semper

2016-08-01

Full Text Available 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.

Model brain based learning (BBL and whole brain teaching (WBT in learning

Directory of Open Access Journals (Sweden)

Baiq Sri Handayani

2017-08-01

Full Text Available The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL and the model of Whole Brain Teaching (WBT. The purposes of this article are to obtain information related to (1 the brain’s natural learning system, (2 analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3 explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1 the brain’s natural learning system are: (a the nerves in each hemisphere do not work independently, (b doing more activities can connect more brain nerves, (c the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2 the characteristics of BBL and WBT are: (a BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3 the typical

Experiences of giving and receiving care in traumatic brain injury: An integrative review.

Science.gov (United States)

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

Development of an experimental model of brain tissue heterotopia in the lung

Science.gov (United States)

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

Model integration and a theory of models

OpenAIRE

Dolk, Daniel R.; Kottemann, Jeffrey E.

1993-01-01

Model integration extends the scope of model management to include the dimension of manipulation as well. This invariably leads to comparisons with database theory. Model integration is viewed from four perspectives: Organizational, definitional, procedural, and implementational. Strategic modeling is discussed as the organizational motivation for model integration. Schema and process integration are examined as the logical and manipulation counterparts of model integr...

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

Science.gov (United States)

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

2016-01-01

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

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

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Giorgio Gorini

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

Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data.

Science.gov (United States)

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

2009-01-01

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.

Distributed XQuery-based integration and visualization of multimodality brain mapping data

Directory of Open Access Journals (Sweden)

Landon T Detwiler

2009-01-01

Full Text Available 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.

Bayesian Modelling of Functional Whole Brain Connectivity

DEFF Research Database (Denmark)

Røge, Rasmus

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

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan

2017-03-27

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

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert; Ombao, Hernando

2017-01-01

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

BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology.

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Matthew Caldwell

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

Mathematical modeling of human glioma growth based on brain topological structures: study of two clinical cases.

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Cecilia Suarez

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

Synthesis and deposition of basement membrane proteins by primary brain capillary endothelial cells in a murine model of the blood-brain barrier.

Science.gov (United States)

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.

Three-dimensional visualization of functional brain tissue and functional magnetic resonance imaging-integrated neuronavigation in the resection of brain tumor adjacent to motor cortex

International Nuclear Information System (INIS)

Han Tong; Cui Shimin; Tong Xiaoguang; Liu Li; Xue Kai; Liu Meili; Liang Siquan; Zhang Yunting; Zhi Dashi

2011-01-01

Objective: To assess the value of three -dimensional visualization of functional brain tissue and the functional magnetic resonance imaging (fMRI)-integrated neuronavigation in the resection of brain tumor adjacent to motor cortex. Method: Sixty patients with tumor located in the central sulcus were enrolled. Thirty patients were randomly assigned to function group and 30 to control group. Patients in function group underwent fMRI to localize the functional brain tissues. Then the function information was transferred to the neurosurgical navigator. The patients in control group underwent surgery with navigation without function information. The therapeutic effect, excision rate. improvement of motor function, and survival quality during follow-up were analyzed. Result: All patients in function group were accomplished visualization of functional brain tissues and fMRI-integrated neuronavigation. The locations of tumors, central sulcus and motor cortex were marked during the operation. The fMRI -integrated information played a great role in both pre- and post-operation. Pre-operation: designing the location of the skin flap and window bone, determining the relationship between the tumor and motor cortex, and designing the pathway for the resection. Post- operation: real-time navigation of relationship between the tumor and motor cortex, assisting to localize the motor cortex using interoperation ultra-sound for correcting the displacement by the CSF outflow and collapsing tumor. The patients in the function group had better results than the patients in the control group in therapeutic effect (u=2.646, P=0.008), excision rate (χ = 7.200, P<0.01), improvement of motor function (u=2.231, P=0.026), and survival quality (KPS u c = 2.664, P=0.008; Zubrod -ECOG -WHO u c =2.135, P=0.033). Conclusions: Using preoperative three -dimensional visualization of cerebral function tissue and the fMRI-integrated neuronavigation technology, combining intraoperative accurate

In vitro models of the blood-brain barrier

DEFF Research Database (Denmark)

Helms, Hans Christian Cederberg; Abbott, N Joan; Burek, Malgorzata

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...

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

Science.gov (United States)

Scripp, Lawrence; Gilbert, Josh

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Filipa L Cardoso

Full Text Available 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.

The Center for Integrated Molecular Brain Imaging (Cimbi) database

DEFF Research Database (Denmark)

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

2016-01-01

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

Modeling noninvasive neurostimulation in epilepsy as stochastic interference in brain networks.

Science.gov (United States)

Stamoulis, Catherine; Chang, Bernard S

2013-05-01

Noninvasive brain stimulation is one of very few potential therapies for medically refractory epilepsy. However, its efficacy remains suboptimal and its therapeutic value has not been consistently assessed. This is in part due to the nonoptimized spatio-temporal application of stimulation protocols for seizure prevention or arrest, and incomplete knowledge of the neurodynamics of seizure evolution. Through simulations, this study investigated electroencephalography (EEG)-guided, stochastic interference with aberrantly coordinated neuronal networks, to prevent seizure onset or interrupt a propagating partial seizure, and prevent it from spreading to large areas of the brain. Brain stimulation was modeled as additive white or band-limited noise, and simulations using real EEGs and data generated from a network of integrate-and-fire neuronal ensembles were used to quantify spatio-temporal noise effects. It was shown that additive stochastic signals (noise) may destructively interfere with network dynamics and decrease or abolish synchronization associated with progressively coupled networks. Furthermore, stimulation parameters, particularly amplitude and spatio-temporal application, may be optimized based on patient-specific neurodynamics estimated directly from noninvasive EEGs.

The integral biologically effective dose to predict brain stem toxicity of hypofractionated stereotactic radiotherapy

International Nuclear Information System (INIS)

Clark, Brenda G.; Souhami, Luis; Pla, Conrado; Al-Amro, Abdullah S.; Bahary, Jean-Paul; Villemure, Jean-Guy; Caron, Jean-Louis; Olivier, Andre; Podgorsak, Ervin B.

1998-01-01

Purpose: The aim of this work was to develop a parameter for use during fractionated stereotactic radiotherapy treatment planning to aid in the determination of the appropriate treatment volume and fractionation regimen that will minimize risk of late damage to normal tissue. Materials and Methods: We have used the linear quadratic model to assess the biologically effective dose at the periphery of stereotactic radiotherapy treatment volumes that impinge on the brain stem. This paper reports a retrospective study of 77 patients with malignant and benign intracranial lesions, treated between 1987 and 1995, with the dynamic rotation technique in 6 fractions over a period of 2 weeks, to a total dose of 42 Gy prescribed at the 90% isodose surface. From differential dose-volume histograms, we evaluated biologically effective dose-volume histograms and obtained an integral biologically-effective dose (IBED) in each case. Results: Of the 77 patients in the study, 36 had target volumes positioned so that the brain stem received more than 1% of the prescribed dose, and 4 of these, all treated for meningioma, developed serious late damage involving the brain stem. Other than type of lesion, the only significant variable was the volume of brain stem exposed. An analysis of the IBEDs received by these 36 patients shows evidence of a threshold value for late damage to the brain stem consistent with similar thresholds that have been determined for external beam radiotherapy. Conclusions: We have introduced a new parameter, the IBED, that may be used to represent the fractional effective dose to structures such as the brain stem that are partially irradiated with stereotactic dose distributions. The IBED is easily calculated prior to treatment and may be used to determine appropriate treatment volumes and fractionation regimens minimizing possible toxicity to normal tissue

Computational Intelligence in a Human Brain Model

Directory of Open Access Journals (Sweden)

Viorel Gaftea

2016-06-01

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

A revised dosimetric model of the adult head and brain

International Nuclear Information System (INIS)

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

1996-01-01

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

Modeling Brain Circuitry over a Wide Range of Scales

Directory of Open Access Journals (Sweden)

Pascal eFua

2015-04-01

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

Modeling brain circuitry over a wide range of scales.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Science.gov (United States)

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.

Meditation is associated with increased brain network integration.

Science.gov (United States)

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

Rounding of abrupt phase transitions in brain networks

International Nuclear Information System (INIS)

Martín, Paula Villa; Moretti, Paolo; Muñoz, Miguel A

2015-01-01

The observation of critical-like behavior in cortical networks represents a major step forward in elucidating how the brain manages information. Understanding the origin and functionality of critical-like dynamics, as well as its robustness, is a major challenge in contemporary neuroscience. Here, we present an extensive numerical study of a family of simple dynamical models, which describe activity propagation in brain networks through the integration of different neighboring spiking potentials, mimicking basic neural interactions. The requirement of signal integration may lead to discontinuous phase transitions in networks that are well described by the mean-field approximation, thus preventing the emergence of critical points in such systems. Brain networks, however, are finite dimensional and exhibit a heterogeneous hierarchical structure that cannot be encoded in mean-field models. Here we propose that, as a consequence of the presence of such a heterogeneous substrate with its concomitant structural disorder, critical-like features may emerge even in the presence of integration. These conclusions may prove significant in explaining the observation of traits of critical behavior in large-scale measurements of brain activity. (paper)

Brain network segregation and integration during an epoch-related working memory fMRI experiment.

Science.gov (United States)

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.

Modeling energy-economy interactions using integrated models

International Nuclear Information System (INIS)

Uyterlinde, M.A.

1994-06-01

Integrated models are defined as economic energy models that consist of several submodels, either coupled by an interface module, or embedded in one large model. These models can be used for energy policy analysis. Using integrated models yields the following benefits. They provide a framework in which energy-economy interactions can be better analyzed than in stand-alone models. Integrated models can represent both energy sector technological details, as well as the behaviour of the market and the role of prices. Furthermore, the combination of modeling methodologies in one model can compensate weaknesses of one approach with strengths of another. These advantages motivated this survey of the class of integrated models. The purpose of this literature survey therefore was to collect and to present information on integrated models. To carry out this task, several goals were identified. The first goal was to give an overview of what is reported on these models in general. The second one was to find and describe examples of such models. Other goals were to find out what kinds of models were used as component models, and to examine the linkage methodology. Solution methods and their convergence properties were also a subject of interest. The report has the following structure. In chapter 2, a 'conceptual framework' is given. In chapter 3 a number of integrated models is described. In a table, a complete overview is presented of all described models. Finally, in chapter 4, the report is summarized, and conclusions are drawn regarding the advantages and drawbacks of integrated models. 8 figs., 29 refs

The Virtual Brain: a simulator of primate brain network dynamics.

Science.gov (United States)

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.

The Virtual Brain: a simulator of primate brain network dynamics

Science.gov (United States)

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

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

NARCIS (Netherlands)

van Elk, Michiel; Aleman, Andre

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

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando

2017-01-01

aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel

Postnatal experiences influence how the brain integrates information from different senses

Directory of Open Access Journals (Sweden)

Barry E Stein

2009-09-01

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

Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease.

Science.gov (United States)

Jie, Biao; Liu, Mingxia; Shen, Dinggang

2018-07-01

Functional connectivity networks (FCNs) using resting-state functional magnetic resonance imaging (rs-fMRI) have been applied to the analysis and diagnosis of brain disease, such as Alzheimer's disease (AD) and its prodrome, i.e., mild cognitive impairment (MCI). Different from conventional studies focusing on static descriptions on functional connectivity (FC) between brain regions in rs-fMRI, recent studies have resorted to dynamic connectivity networks (DCNs) to characterize the dynamic changes of FC, since dynamic changes of FC may indicate changes in macroscopic neural activity patterns in cognitive and behavioral aspects. However, most of the existing studies only investigate the temporal properties of DCNs (e.g., temporal variability of FC between specific brain regions), ignoring the important spatial properties of the network (e.g., spatial variability of FC associated with a specific brain region). Also, emerging evidence on FCNs has suggested that, besides temporal variability, there is significant spatial variability of activity foci over time. Hence, integrating both temporal and spatial properties of DCNs can intuitively promote the performance of connectivity-network-based learning methods. In this paper, we first define a new measure to characterize the spatial variability of DCNs, and then propose a novel learning framework to integrate both temporal and spatial variabilities of DCNs for automatic brain disease diagnosis. Specifically, we first construct DCNs from the rs-fMRI time series at successive non-overlapping time windows. Then, we characterize the spatial variability of a specific brain region by computing the correlation of functional sequences (i.e., the changing profile of FC between a pair of brain regions within all time windows) associated with this region. Furthermore, we extract both temporal variabilities and spatial variabilities from DCNs as features, and integrate them for classification by using manifold regularized multi

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

Science.gov (United States)

Taruffi, Liila; Koelsch, Stefan

2017-07-01

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

The Virtual Brain: a simulator of primate brain network dynamics

Directory of Open Access Journals (Sweden)

Paula eSanz Leon

2013-06-01

Full Text Available We present TheVirtualBrain (TVB, a neuroinformatics platform for full brainnetwork simulations using biologically realistic connectivity. This simulationenvironment enables the model-based inference of neurophysiological mechanismsacross different brain scales that underlie the generation of macroscopicneuroimaging signals including functional MRI (fMRI, EEG and MEG. Researchersfrom different backgrounds can benefit from an integrative software platformincluding a supporting framework for data management (generation,organization, storage, integration and sharing and a simulation core writtenin Python. TVB allows the reproduction and evaluation of personalizedconfigurations of the brain by using individual subject data. Thispersonalization facilitates an exploration of the consequences of pathologicalchanges in the system, permitting to investigate potential ways to counteractsuch unfavorable processes. The architecture of TVB supports interaction withMATLAB packages, for example, the well known Brain Connectivity Toolbox. TVBcan be used in a client-server configuration, such that it can be remotelyaccessed through the Internet thanks to its web-basedHTML5, JS and WebGL graphical user interface. TVB is alsoaccessible as a standalone cross-platform Python library and application, andusers can interact with the scientific core through the scripting interfaceIDLE, enabling easy modeling, development and debugging of the scientifickernel. This second interface makes TVB extensible by combining it with otherlibraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to thedevelopment of TVB, the architecture and features of its major softwarecomponents as well as potential neuroscience applications.

Brain-inspired Stochastic Models and Implementations

KAUST Repository

Al-Shedivat, Maruan

2015-05-12

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

The integrate model of emotion, thinking and self regulation: an application to the "paradox of aging".

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Lirong Tan

2017-09-01

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

Predictive modeling of neuroanatomic structures for brain atrophy detection

Science.gov (United States)

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.

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan

2017-12-12

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

Fresh Frozen Plasma Modulates Brain Gene Expression in a Swine Model of Traumatic Brain Injury and Shock

DEFF Research Database (Denmark)

Sillesen, Martin; Bambakidis, Ted; Dekker, Simone E

2017-01-01

BACKGROUND: Resuscitation with fresh frozen plasma (FFP) decreases brain lesion size and swelling in a swine model of traumatic brain injury and hemorrhagic shock. We hypothesized that brain gene expression profiles after traumatic brain injury and hemorrhagic shock would be modulated by FFP resu...

Comparing Structural Brain Connectivity by the Infinite Relational Model

DEFF Research Database (Denmark)

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

2013-01-01

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

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

Science.gov (United States)

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

2014-01-01

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

Fuzzy object models for newborn brain MR image segmentation

Science.gov (United States)

Kobashi, Syoji; Udupa, Jayaram K.

2013-03-01

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

D-galactose-induced brain ageing model

DEFF Research Database (Denmark)

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

2017-01-01

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

Volatile anesthetics influence blood-brain barrier integrity by modulation of tight junction protein expression in traumatic brain injury.

Directory of Open Access Journals (Sweden)

Serge C Thal

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

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

Directory of Open Access Journals (Sweden)

Natalia Malinovskaya

2016-12-01

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

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

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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.

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.

Science.gov (United States)

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.

A neural model of decision making

OpenAIRE

Larsen, Torben

2008-01-01

Background: A descriptive neuroeconomic model is aimed for relativity of the concept of economic man to empirical science.Method: A 4-level client-server-integrator model integrating the brain models of McLean and Luria is the general framework for the model of empirical findings.Results: Decision making relies on integration across brain levels of emotional intelligence (LU) and logico-matematico intelligence (RIA), respectively. The integrated decision making formula approaching zero by bot...

Measuring brain atrophy with a generalized formulation of the boundary shift integral.

Science.gov (United States)

Prados, Ferran; Cardoso, Manuel Jorge; Leung, Kelvin K; Cash, David M; Modat, Marc; Fox, Nick C; Wheeler-Kingshott, Claudia A M; Ourselin, Sebastien

2015-01-01

Brain atrophy measured using structural magnetic resonance imaging (MRI) has been widely used as an imaging biomarker for disease diagnosis and tracking of pathologic progression in neurodegenerative diseases. In this work, we present a generalized and extended formulation of the boundary shift integral (gBSI) using probabilistic segmentations to estimate anatomic changes between 2 time points. This method adaptively estimates a non-binary exclusive OR region of interest from probabilistic brain segmentations of the baseline and repeat scans to better localize and capture the brain atrophy. We evaluate the proposed method by comparing the sample size requirements for a hypothetical clinical trial of Alzheimer's disease to that needed for the current implementation of BSI as well as a fuzzy implementation of BSI. The gBSI method results in a modest but reduced sample size, providing increased sensitivity to disease changes through the use of the probabilistic exclusive OR region. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2010-01-01

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

Development of a model for whole brain learning of physiology.

Science.gov (United States)

Eagleton, Saramarie; Muller, Anton

2011-12-01

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

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

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Nisha Puthiyedth

Full Text Available 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

Modeling the brain morphology distribution in the general aging population

Science.gov (United States)

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.

A Bayesian Model of Category-Specific Emotional Brain Responses

Science.gov (United States)

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

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

OpenAIRE

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

2016-01-01

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 br...

Lentivector Integration Sites in Ependymal Cells From a Model of Metachromatic Leukodystrophy: Non-B DNA as a New Factor Influencing Integration

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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

Science.gov (United States)

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

Diverse methods for integrable models

NARCIS (Netherlands)

Fehér, G.

2017-01-01

This thesis is centered around three topics, sharing integrability as a common theme. This thesis explores different methods in the field of integrable models. The first two chapters are about integrable lattice models in statistical physics. The last chapter describes an integrable quantum chain.

Resolving structural variability in network models and the brain.

Directory of Open Access Journals (Sweden)

Florian Klimm

2014-03-01

Full Text Available 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

Mathematical modelling of blood-brain barrier failure and edema

Science.gov (United States)

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.

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

Science.gov (United States)

van Elk, Michiel; Aleman, André

2017-02-01

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

Developing Integrated Care: Towards a development model for integrated care

NARCIS (Netherlands)

M.M.N. Minkman (Mirella)

2012-01-01

textabstractThe thesis adresses the phenomenon of integrated care. The implementation of integrated care for patients with a stroke or dementia is studied. Because a generic quality management model for integrated care is lacking, the study works towards building a development model for integrated

A model for integrating elementary neural functions into delayed-response behavior.

Directory of Open Access Journals (Sweden)

Thomas Gisiger

2006-04-01

Full Text Available 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.

A model for integrating elementary neural functions into delayed-response behavior.

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Isabelle GEORGE

2011-01-01

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

Monitoring Blood-Brain Barrier Integrity Following Amyloid-β Immunotherapy Using Gadolinium-Enhanced MRI in a PDAPP Mouse Model.

Science.gov (United States)

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.

Evaluation of cat brain infarction model using microPET

Energy Technology Data Exchange (ETDEWEB)

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

2004-07-01

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

Evaluation of cat brain infarction model using microPET

Energy Technology Data Exchange (ETDEWEB)

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

2004-12-01

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

Evaluation of cat brain infarction model using microPET

International Nuclear Information System (INIS)

Lee, J. J.; Lee, D. S.; Kim, J. H.; Hwang, D. W.; Jung, J. G.; Lee, M. C; Lim, S. M

2004-01-01

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

Evaluation of cat brain infarction model using microPET

International Nuclear Information System (INIS)

Lee, Jong Jin; Lee, Dong Soo; Kim, Yun Hui; Hwang, Do Won; Kim, Jin Su; Chung, June Key; Lee, Myung Chul; Lim, Sang Moo

2004-01-01

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

Normal Brain-Skull Development with Hybrid Deformable VR Models Simulation.

Science.gov (United States)

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.

Distributed organization of a brain microcircuit analysed by three-dimensional modeling: the olfactory bulb

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Michele eMigliore

2014-04-01

Full Text Available The functional consequences of the laminar organization observed in cortical systems cannot be easily studied using standard experimental techniques, abstract theoretical representations, or dimensionally reduced models built from scratch. To solve this problem we have developed a full implementation of an olfactory bulb microcircuit using realistic three-dimensional inputs, cell morphologies, and network connectivity. The results provide new insights into the relations between the functional properties of individual cells and the networks in which they are embedded. To our knowledge, this is the first model of the mitral-granule cell network to include a realistic representation of the experimentally-recorded complex spatial patterns elicited in the glomerular layer by natural odor stimulation. Although the olfactory bulb, due to its organization, has unique advantages with respect to other brain systems, the method is completely general, and can be integrated with more general approaches to other systems. The model makes experimentally testable predictions on distributed processing and on the differential backpropagation of somatic action potentials in each lateral dendrite following odor learning, providing a powerful three-dimensional framework for investigating the functions of brain microcircuits.

A family of hyperelastic models for human brain tissue

Science.gov (United States)

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

2017-09-01

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

Modeling the dynamics of human brain activity with recurrent neural networks

NARCIS (Netherlands)

Güçlü, U.; Gerven, M.A.J. van

2017-01-01

Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of stimuli to features (feature model) and a linear convolution

Community integration after severe traumatic brain injury in adults.

Science.gov (United States)

Truelle, Jean-Luc; Fayol, Patrick; Montreuil, Michèle; Chevignard, Mathilde

2010-12-01

Despite being the main cause of death and disability in young adults, traumatic brain injury (TBI) is a rather neglected epidemic. Community integration of persons with TBI was, until recently, insufficiently informed by clinical research. To bridge the gap between rehabilitation and community re-entry, the first task is to assess the person, using TBI-specific outcome measures. The second task is to provide re-entry programs, the effectiveness of which is assessed by those measures, using well designed studies. There are very few such studies. However, there are some effective comprehensive programs and others which are specifically targeted dealing mainly with return to work, behavior, and family issues. The complex psychological and environmental components of the disability require individualized and often long-term care. For persons with severe TBI trying to achieve the best possible community integration a new semiology is required, not just limited to medical care, but also involving social and psychological care that is tailored to the needs of each individual and family, living within his/her environment. Currently, only a minority benefit from well validated programs.

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

Science.gov (United States)

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

2013-03-01

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

Integration of fMRI, NIROT and ERP for studies of human brain function.

Science.gov (United States)

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.

I-123 iomazenil single photon emission computed tomography for detecting loss of neuronal integrity in patients with traumatic brain injury

OpenAIRE

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

2017-01-01

Background 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 whet...

Integration of Neuroimaging and Microarray Datasets  through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

Directory of Open Access Journals (Sweden)

Spiro P. Pantazatos

2009-06-01

Full Text Available 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.

An integrative model of auditory phantom perception: tinnitus as a unified percept of interacting separable subnetworks.

Science.gov (United States)

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

Novel brain arteriovenous malformation mouse models for type 1 hereditary hemorrhagic telangiectasia.

Directory of Open Access Journals (Sweden)

Eun-Jung Choi

Full Text Available Endoglin (ENG is a causative gene of type 1 hereditary hemorrhagic telangiectasia (HHT1. HHT1 patients have a higher prevalence of brain arteriovenous malformation (AVM than the general population and patients with other HHT subtypes. The pathogenesis of brain AVM in HHT1 patients is currently unknown and no specific medical therapy is available to treat patients. Proper animal models are crucial for identifying the underlying mechanisms for brain AVM development and for testing new therapies. However, creating HHT1 brain AVM models has been quite challenging because of difficulties related to deleting Eng-floxed sequence in Eng(2fl/2fl mice. To create an HHT1 brain AVM mouse model, we used several Cre transgenic mouse lines to delete Eng in different cell-types in Eng(2fl/2fl mice: R26CreER (all cell types after tamoxifen treatment, SM22α-Cre (smooth muscle and endothelial cell and LysM-Cre (lysozyme M-positive macrophage. An adeno-associated viral vector expressing vascular endothelial growth factor (AAV-VEGF was injected into the brain to induce focal angiogenesis. We found that SM22α-Cre-mediated Eng deletion in the embryo caused AVMs in the postnatal brain, spinal cord, and intestines. Induction of Eng deletion in adult mice using R26CreER plus local VEGF stimulation induced the brain AVM phenotype. In both models, Eng-null endothelial cells were detected in the brain AVM lesions, and formed mosaicism with wildtype endothelial cells. However, LysM-Cre-mediated Eng deletion in the embryo did not cause AVM in the postnatal brain even after VEGF stimulation. In this study, we report two novel HHT1 brain AVM models that mimic many phenotypes of human brain AVM and can thus be used for studying brain AVM pathogenesis and testing new therapies. Further, our data indicate that macrophage Eng deletion is insufficient and that endothelial Eng homozygous deletion is required for HHT1 brain AVM development.

Gpr124 is essential for blood-brain barrier integrity in central nervous system disease.

Science.gov (United States)

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.

A porcine model of haematogenous brain infectionwith staphylococcus aureus

DEFF Research Database (Denmark)

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

2012-01-01

A PORCINE MODEL OF HAEMATOGENOUS BRAIN INFECTION WITH STAPHYLOCOCCUS AUREUS Astrup Lærke1, Agerholm Jørgen1, Nielsen Ole1, Jensen Henrik1, Leifsson Páll1, Iburg Tine2. 1: Faculty of Health and Medical Sciences, University of Copenhagen, Denmark boye@life.ku.dk 2: National Veterinary Institute......, Uppsala, Sweden Introduction Staphylococcus aureus (S.aureus) is a common cause of sepsis and brain abscesses in man and a frequent cause of porcine pyaemia. Here we present a porcine model of haematogenous S. aureus-induced brain infection. Materials and Methods Four pigs had two intravenous catheters...... thromboemboli (two pigs). The venous catheter was used for blood sampling before, during and after inoculation. The pigs were euthanized either 24 or 48 hours after inoculation. The brains were collected and examined histologically. Results We describe unifocal suppurative encephalitis 48 hours after...

Development of three-dimensional brain arteriovenous malformation model for patient communication and young neurosurgeon education.

Science.gov (United States)

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.

Brain inspired high performance electronics on flexible silicon

KAUST Repository

Sevilla, Galo T.

2014-06-01

Brain\\'s stunning speed, energy efficiency and massive parallelism makes it the role model for upcoming high performance computation systems. Although human brain components are a million times slower than state of the art silicon industry components [1], they can perform 1016 operations per second while consuming less power than an electrical light bulb. In order to perform the same amount of computation with today\\'s most advanced computers, the output of an entire power station would be needed. In that sense, to obtain brain like computation, ultra-fast devices with ultra-low power consumption will have to be integrated in extremely reduced areas, achievable only if brain folded structure is mimicked. Therefore, to allow brain-inspired computation, flexible and transparent platform will be needed to achieve foldable structures and their integration on asymmetric surfaces. In this work, we show a new method to fabricate 3D and planar FET architectures in flexible and semitransparent silicon fabric without comprising performance and maintaining cost/yield advantage offered by silicon-based electronics.

Pathophysiological Responses in Rat and Mouse Models of Radiation-Induced Brain Injury.

Science.gov (United States)

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.

Science.gov (United States)

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.

Brain-mapping projects using the common marmoset.

Science.gov (United States)

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.

Qualitative Analysis of Integration Adapter Modeling

OpenAIRE

Ritter, Daniel; Holzleitner, Manuel

2015-01-01

Integration Adapters are a fundamental part of an integration system, since they provide (business) applications access to its messaging channel. However, their modeling and configuration remain under-represented. In previous work, the integration control and data flow syntax and semantics have been expressed in the Business Process Model and Notation (BPMN) as a semantic model for message-based integration, while adapter and the related quality of service modeling were left for further studi...

Multisensory integration and internal models for sensing gravity effects in primates.

Science.gov (United States)

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.

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

Science.gov (United States)

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

Dendrimer brain uptake and targeted therapy for brain injury in a large animal model of hypothermic circulatory arrest.

Science.gov (United States)

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.

Integrability of the Rabi Model

International Nuclear Information System (INIS)

Braak, D.

2011-01-01

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

A Dirichlet process mixture model for brain MRI tissue classification.

Science.gov (United States)

Ferreira da Silva, Adelino R

2007-04-01

Accurate classification of magnetic resonance images according to tissue type or region of interest has become a critical requirement in diagnosis, treatment planning, and cognitive neuroscience. Several authors have shown that finite mixture models give excellent results in the automated segmentation of MR images of the human normal brain. However, performance and robustness of finite mixture models deteriorate when the models have to deal with a variety of anatomical structures. In this paper, we propose a nonparametric Bayesian model for tissue classification of MR images of the brain. The model, known as Dirichlet process mixture model, uses Dirichlet process priors to overcome the limitations of current parametric finite mixture models. To validate the accuracy and robustness of our method we present the results of experiments carried out on simulated MR brain scans, as well as on real MR image data. The results are compared with similar results from other well-known MRI segmentation methods.

Integrative biological analysis for neuropsychopharmacology.

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Data-driven forward model inference for EEG brain imaging

DEFF Research Database (Denmark)

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

2016-01-01

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

Left Brain/Right Brain Learning for Adult Education.

Science.gov (United States)

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)

Disruption in the Blood-Brain Barrier: The Missing Link between Brain and Body Inflammation in Bipolar Disorder?

Directory of Open Access Journals (Sweden)

Jay P. Patel

2015-01-01

Full Text Available The blood-brain barrier (BBB regulates the transport of micro- and macromolecules between the peripheral blood and the central nervous system (CNS in order to maintain optimal levels of essential nutrients and neurotransmitters in the brain. In addition, the BBB plays a critical role protecting the CNS against neurotoxins. There has been growing evidence that BBB disruption is associated with brain inflammatory conditions such as Alzheimer’s disease and multiple sclerosis. Considering the increasing role of inflammation and oxidative stress in the pathophysiology of bipolar disorder (BD, here we propose a novel model wherein transient or persistent disruption of BBB integrity is associated with decreased CNS protection and increased permeability of proinflammatory (e.g., cytokines, reactive oxygen species substances from the peripheral blood into the brain. These events would trigger the activation of microglial cells and promote localized damage to oligodendrocytes and the myelin sheath, ultimately compromising myelination and the integrity of neural circuits. The potential implications for research in this area and directions for future studies are discussed.

Model sparsity and brain pattern interpretation of classification models in neuroimaging

DEFF Research Database (Denmark)

Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Churchill, Nathan W

2012-01-01

Interest is increasing in applying discriminative multivariate analysis techniques to the analysis of functional neuroimaging data. Model interpretation is of great importance in the neuroimaging context, and is conventionally based on a ‘brain map’ derived from the classification model. In this ...

Blood-brain barrier alterations provide evidence of subacute diaschisis in an ischemic stroke rat model.

Directory of Open Access Journals (Sweden)

Svitlana Garbuzova-Davis

Full Text Available 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.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.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.

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

Science.gov (United States)

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.

The influence of surrogate blood vessels on the impact response of a physical model of the brain.

Science.gov (United States)

Parnaik, Yednesh; Beillas, Philippe; Demetropoulos, Constantine K; Hardy, Warren N; Yang, King H; King, Albert I

2004-11-01

Cerebral blood vessels are an integral part of the brain and may play a role in the response of the brain to impact. The purpose of this study was to quantify the effects of surrogate vessels on the deformation patterns of a physical model of the brain under various impact conditions. Silicone gel and tubing were used as surrogates for brain tissue and blood vessels, respectively. Two aluminum cylinders representing a coronal section of the brain were constructed. One cylinder was filled with silicone gel only, and the other was filled with silicone gel and silicone tubing arranged in the radial direction in the peripheral region. An array of markers was embedded in the gel in both cylinders to facilitate strain calculation via high-speed video analysis. Both cylinders were simultaneously subjected to a combination of linear and angular acceleration using a two-segment pendulum. Marker motion was tracked, and maximum shear strain (MSS) and maximum principal strain (MPS) were calculated using markers clustered in groups of three. Four test series were conducted. Peak angular acceleration varied from 2,600 to 26,000 rad/s2, and peak angular speed varied from 17 to 29 rad/s. For a given impact condition, the test-to-test variation of these values was less than 5.5%. For all clusters, the peak MSS and peak MPS for both physical models were less than 26% and 32%, respectively. For 90% of the cluster locations, the absolute value of the difference in peak MSS and peak MPS between the physical models was 4% and 6%, respectively. In the physical model with tubing, strain tended to decrease in the periphery (near to the tubing), while it tended to increase toward the center (away from the tubing). Strain amplitudes were found to be sensitive to the peak angular speeds. In general, this study suggests that the vasculature could influence the deformation response of the brain.

Audio-Tactile Integration and the Influence of Musical Training

OpenAIRE

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 function...

Corticonic models of brain mechanisms underlying cognition and intelligence

Science.gov (United States)

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

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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.

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

Directory of Open Access Journals (Sweden)

Lian eDuan

2015-07-01

Full Text Available Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called Cluster Imaging of Multi-brain Networks (CIMBN. CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network’s properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology.

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

OpenAIRE

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 ri...

Hierarchical models in the brain.

Directory of Open Access Journals (Sweden)

Karl Friston

2008-11-01

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

Topological quantum theories and integrable models

International Nuclear Information System (INIS)

Keski-Vakkuri, E.; Niemi, A.J.; Semenoff, G.; Tirkkonen, O.

1991-01-01

The path-integral generalization of the Duistermaat-Heckman integration formula is investigated for integrable models. It is shown that for models with periodic classical trajectories the path integral reduces to a form similar to the finite-dimensional Duistermaat-Heckman integration formula. This provides a relation between exactness of the stationary-phase approximation and Morse theory. It is also argued that certain integrable models can be related to topological quantum theories. Finally, it is found that in general the stationary-phase approximation presumes that the initial and final configurations are in different polarizations. This is exemplified by the quantization of the SU(2) coadjoint orbit

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

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Murat Demirtaş

2017-01-01

Full Text Available 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.

Business and technology integrated model

OpenAIRE

Noce, Irapuan; Carvalho, João Álvaro

2011-01-01

There is a growing interest in business modeling and architecture in the areas of management and information systems. One of the issues in the area is the lack of integration between the modeling techniques that are employed to support business development and those used for technology modeling. This paper proposes a modeling approach that is capable of integrating the modeling of the business and of the technology. By depicting the business model, the organization structure and the technolog...

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

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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 biologically inspired neural model for visual and proprioceptive integration including sensory training.

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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

A perturbational approach for evaluating the brain's capacity for consciousness.

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Massimini, Marcello; Boly, Melanie; Casali, Adenauer; Rosanova, Mario; Tononi, Giulio

2009-01-01

How do we evaluate a brain's capacity to sustain conscious experience if the subject does not manifest purposeful behaviour and does not respond to questions and commands? What should we measure in this case? An emerging idea in theoretical neuroscience is that what really matters for consciousness in the brain is not activity levels, access to sensory inputs or neural synchronization per se, but rather the ability of different areas of the thalamocortical system to interact causally with each other to form an integrated whole. In particular, the information integration theory of consciousness (IITC) argues that consciousness is integrated information and that the brain should be able to generate consciousness to the extent that it has a large repertoire of available states (information), yet it cannot be decomposed into a collection of causally independent subsystems (integration). To evaluate the ability to integrate information among distributed cortical regions, it may not be sufficient to observe the brain in action. Instead, it is useful to employ a perturbational approach and examine to what extent different regions of the thalamocortical system can interact causally (integration) and produce specific responses (information). Thanks to a recently developed technique, transcranial magnetic stimulation and high-density electroencephalography (TMS/hd-EEG), one can record the immediate reaction of the entire thalamocortical system to controlled perturbations of different cortical areas. In this chapter, using sleep as a model of unconsciousness, we show that TMS/hd-EEG can detect clear-cut changes in the ability of the thalamocortical system to integrate information when the level of consciousness fluctuates across the sleep-wake cycle. Based on these results, we discuss the potential applications of this novel technique to evaluate objectively the brain's capacity for consciousness at the bedside of brain-injured patients.

Patients' experiences and care needs during the diagnostic phase of an Integrated Brain Cancer Pathway

DEFF Research Database (Denmark)

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

2018-01-01

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...... 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. DESIGN: A Case Study design was used to provide detailed information of the complex needs of patients being diagnosed with a malignant brain tumour. METHODS: Research interviews and direct participant observation of four patients...

Monitoring the injured brain: registered, patient specific atlas models to improve accuracy of recovered brain saturation values

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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.

TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

Energy Technology Data Exchange (ETDEWEB)

Preusser, T. [Fraunhofer MEVIS & Jacobs University (Germany)

2015-06-15

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

TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

International Nuclear Information System (INIS)

Preusser, T.

2015-01-01

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

Closed Loop Brain Model of Neocortical Information Based Exchange

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James eKozloski

2016-01-01

Full Text Available Here we describe an information based exchange' model of brain function that ascribes to neocortex, basal ganglia, and thalamus distinct network functions. The model allows us to analyze whole brain system set point measures, such as the rate and heterogeneity of transitions in striatum and neocortex, in the context of neuromodulation and other perturbations. Our closed-loop model is grounded in neuroanatomical observations, proposing a novel Grand Loop through neocortex, and invokes different forms of plasticity at specific tissue interfaces and their principle cell synapses to achieve these transitions. By implementing a system for maximum information based exchange of action potentials between modeled neocortical areas, we observe changes to these measures in simulation. We hypothesize that similar dynamic set points and modulations exist in the brain's resting state activity, and that different modifications to information based exchange may shift the risk profile of different component tissues, resulting in different neurodegenerative diseases. This model is targeted for further development using IBM's Neural Tissue Simulator, which allows scalable elaboration of networks, tissues, and their neural and synaptic components towards ever greater complexity and biological realism.

INTEGRATED CORPORATE STRATEGY MODEL

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CATALINA SORIANA SITNIKOV

2014-02-01

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

An improved in vitro blood-brain barrier model: rat brain endothelial cells co-cultured with astrocytes.

Science.gov (United States)

Abbott, N Joan; Dolman, Diana E M; Drndarski, Svetlana; Fredriksson, Sarah M

2012-01-01

In vitro blood-brain barrier (BBB) models using primary cultured brain endothelial cells are important for establishing cellular and molecular mechanisms of BBB function. Co-culturing with BBB-associated cells especially astrocytes to mimic more closely the in vivo condition leads to upregulation of the BBB phenotype in the brain endothelial cells. Rat brain endothelial cells (RBECs) are a valuable tool allowing ready comparison with in vivo studies in rodents; however, it has been difficult to obtain pure brain endothelial cells, and few models achieve a transendothelial electrical resistance (TEER, measure of tight junction efficacy) of >200 Ω cm(2), i.e. the models are still relatively leaky. Here, we describe methods for preparing high purity RBECs and neonatal rat astrocytes, and a co-culture method that generates a robust, stable BBB model that can achieve TEER >600 Ω cm(2). The method is based on >20 years experience with RBEC culture, together with recent improvements to kill contaminating cells and encourage BBB differentiation.Astrocytes are isolated by mechanical dissection and cell straining and are frozen for later co-culture. RBECs are isolated from 3-month-old rat cortices. The brains are cleaned of meninges and white matter and enzymatically and mechanically dissociated. Thereafter, the tissue homogenate is centrifuged in bovine serum albumin to separate vessel fragments from other cells that stick to the myelin plug. The vessel fragments undergo a second enzyme digestion to separate pericytes from vessels and break down vessels into shorter segments, after which a Percoll gradient is used to separate capillaries from venules, arterioles, and single cells. To kill remaining contaminating cells such as pericytes, the capillary fragments are plated in puromycin-containing medium and RBECs grown to 50-60% confluence. They are then passaged onto filters for co-culture with astrocytes grown in the bottom of the wells. The whole procedure takes ∼2

Fetal brain extracellular matrix boosts neuronal network formation in 3D bioengineered model of cortical brain tissue.

Science.gov (United States)

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.

Large Scale Computing for the Modelling of Whole Brain Connectivity

DEFF Research Database (Denmark)

Albers, Kristoffer Jon

organization of the brain in continuously increasing resolution. From these images, networks of structural and functional connectivity can be constructed. Bayesian stochastic block modelling provides a prominent data-driven approach for uncovering the latent organization, by clustering the networks into groups...... of neurons. Relying on Markov Chain Monte Carlo (MCMC) simulations as the workhorse in Bayesian inference however poses significant computational challenges, especially when modelling networks at the scale and complexity supported by high-resolution whole-brain MRI. In this thesis, we present how to overcome...... these computational limitations and apply Bayesian stochastic block models for un-supervised data-driven clustering of whole-brain connectivity in full image resolution. We implement high-performance software that allows us to efficiently apply stochastic blockmodelling with MCMC sampling on large complex networks...

The stress-vulnerability model how does stress impact on mental illness at the level of the brain and what are the consequences?

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

Xiaojin Li

2013-01-01

Full Text Available 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.

Separations and safeguards model integration.

Energy Technology Data Exchange (ETDEWEB)

Cipiti, Benjamin B.; Zinaman, Owen

2010-09-01

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

Combination radiotherapy in an orthotopic mouse brain tumor model.

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

Daniel J Kelley

2007-10-01

Full Text Available 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.

Development of a human head FE model for the impact analysis using VOXEL approach and simulation for the assessment on the focal brain injury

International Nuclear Information System (INIS)

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

2008-01-01

In this paper, a three-dimensional digital human-head model was developed and several dynamic analyses on the head trauma were conducted. This model was built up by the VOXEL approach using 433 slice CT images (512 x 512 pixels) and made of 1.22 million parallelepiped finite elements with 10 anatomical tissue properties such as scalp, cerebrospinal fluid (CSF), skull, brain, dura mater and so on. The numerical analyses were conducted using a finite element code the authors have developed. The main features of the code are it is based on the explicit time integration method and it uses the one point integration method to evaluate the equivalent nodal forces with the hourglass control proposed by Flanagan and Belythcko and it utilizes the parallel computation with the Massage Passing Interface (MPI). In order to verify the developed model, the head impact experiment for a cadaver by Nahum et al. was simulated. The calculated results showed good agreement with experimental ones. A front and rear impact analyses were also performed investigate the relation between the impact direction and the positions of the high measurement of pressure and stresses in brain. The obtained results represent that brain injury has a closer relation with the Mises equivalent stress rather than the pressure. At this time, the large deformation of a frontal cranial base was observed in both frontal and occipital impact analyses. We expect that it induces the brain injury in a frontal lobe regardless of the impact positions. (author)

Statistical models for brain signals with properties that evolve across trials

KAUST Repository

Ombao, Hernando

2017-12-07

Most neuroscience cognitive experiments involve repeated presentations of various stimuli across several minutes or a few hours. It has been observed that brain responses, even to the same stimulus, evolve over the course of the experiment. These changes in brain activation and connectivity are believed to be associated with learning and/or habituation. In this paper, we present two general approaches to modeling dynamic brain connectivity using electroencephalograms (EEGs) recorded across replicated trials in an experiment. The first approach is the Markovian regime-switching vector autoregressive model (MS-VAR) which treats EEGs as realizations of an underlying brain process that switches between different states both within a trial and across trials in the entire experiment. The second is the slowly evolutionary locally stationary process (SEv-LSP) which characterizes the observed EEGs as a mixture of oscillatory activities at various frequency bands. The SEv-LSP model captures the dynamic nature of the amplitudes of the band-oscillations and cross-correlations between them. The MS-VAR model is able to capture abrupt changes in the dynamics while the SEv-LSP directly gives interpretable results. Moreover, it is nonparametric and hence does not suffer from model misspecification. For both of these models, time-evolving connectivity metrics in the frequency domain are derived from the model parameters for both functional and effective connectivity. We illustrate these two models for estimating cross-trial connectivity in selective attention using EEG data from an oddball paradigm auditory experiment where the goal is to characterize the evolution of brain responses to target stimuli and to standard tones presented randomly throughout the entire experiment. The results suggest dynamic changes in connectivity patterns over trials with inter-subject variability.

Multisensory Integration and Internal Models for Sensing Gravity Effects in Primates

Directory of Open Access Journals (Sweden)

Francesco Lacquaniti

2014-01-01

Full Text Available 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.

Intervention and societal costs of residential community reintegration for patients with acquired brain injury: a cost-analysis of the Brain Integration Programme.

Science.gov (United States)

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 costs per patient were €48,449. After BIP these costs were €39,773; a significant reduction (p 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. :

CSF transthyretin neuroprotection in a mouse model of brain ischemia

DEFF Research Database (Denmark)

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

2010-01-01

Brain injury caused by ischemia is a major cause of human mortality and physical/cognitive disability worldwide. Experimentally, brain ischemia can be induced surgically by permanent middle cerebral artery occlusion. Using this model, we studied the influence of transthyretin in ischemic stroke. ...

Technical pitfalls in a porcine brain retraction model. The impact of brain spatula on the retracted brain tissue in a porcine model: a feasibility study and its technical pitfalls

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Thiex, R.; Hans, F.J.; Gilsbach, J.M. [Aachen University, Department of Neurosurgery, Aachen (Germany); Krings, T. [Aachen University, Department of Neuroradiology, Aachen (Germany); Sellhaus, B. [Aachen University, Department of Neuropathology, Aachen (Germany)

2005-10-01

We describe technical pitfalls of a porcine brain injury model for identifying primary and secondary pathological sequelae following brain retraction by brain spatula. In 16 anaesthetised male pigs, the right frontal brain was retracted in the interhemispheric fissure by a brain spatulum with varying pressures applied by the gravitational force of weights from 10 to 70 g for a duration of 30 min. The retracted brain tissue was monitored for changes in intracranial pressure and perfusion of the cortex using a Laser Doppler Perfusion Imager (MoorLDI). To evaluate the extent of oedema and cortical contusions, MRI was performed 30 min and 72 h after brain retraction. Following the MR scan, the retracted brain areas were histopathologically assessed using H and E and Fluoro-Jade B staining for neuronal damage. Sinus occlusion occurred in four animals, resulting in bilateral cortical contusions and extensive brain oedema. Retracting the brain with weights of 70 g (n=4) caused extensive oedema on FLAIR images that correlated clinically with a hemiparesis in three animals. Morphologically, an increased number of Fluoro-Jade B-positive neurons were found. A sequential decrease in weights prevented functional deficits in animals. A retraction pressure applied by 10-g weights (n=7) caused a mean rise in intracranial pressure to 4.0{+-}3.1 mm Hg, and a decrement in mean cortical perfusion from 740.8{+-}41.5 to 693.8{+-}72.4 PU/cm2, (P<0.24). A meticulous dissection of the interhemispheric fissure and a reduction of weights to 10 g were found to be mandatory to study the cortical impact caused by brain spatula reproducibly. (orig.)

Technical pitfalls in a porcine brain retraction model. The impact of brain spatula on the retracted brain tissue in a porcine model: a feasibility study and its technical pitfalls

International Nuclear Information System (INIS)

Thiex, R.; Hans, F.J.; Gilsbach, J.M.; Krings, T.; Sellhaus, B.

2005-01-01

We describe technical pitfalls of a porcine brain injury model for identifying primary and secondary pathological sequelae following brain retraction by brain spatula. In 16 anaesthetised male pigs, the right frontal brain was retracted in the interhemispheric fissure by a brain spatulum with varying pressures applied by the gravitational force of weights from 10 to 70 g for a duration of 30 min. The retracted brain tissue was monitored for changes in intracranial pressure and perfusion of the cortex using a Laser Doppler Perfusion Imager (MoorLDI). To evaluate the extent of oedema and cortical contusions, MRI was performed 30 min and 72 h after brain retraction. Following the MR scan, the retracted brain areas were histopathologically assessed using H and E and Fluoro-Jade B staining for neuronal damage. Sinus occlusion occurred in four animals, resulting in bilateral cortical contusions and extensive brain oedema. Retracting the brain with weights of 70 g (n=4) caused extensive oedema on FLAIR images that correlated clinically with a hemiparesis in three animals. Morphologically, an increased number of Fluoro-Jade B-positive neurons were found. A sequential decrease in weights prevented functional deficits in animals. A retraction pressure applied by 10-g weights (n=7) caused a mean rise in intracranial pressure to 4.0±3.1 mm Hg, and a decrement in mean cortical perfusion from 740.8±41.5 to 693.8±72.4 PU/cm2, (P<0.24). A meticulous dissection of the interhemispheric fissure and a reduction of weights to 10 g were found to be mandatory to study the cortical impact caused by brain spatula reproducibly. (orig.)

The role of right frontal brain regions in integration of spatial relation.

Science.gov (United States)

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.

Science.gov (United States)

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.

Modeling epileptic brain states using EEG spectral analysis and topographic mapping.

Science.gov (United States)

Direito, Bruno; Teixeira, César; Ribeiro, Bernardete; Castelo-Branco, Miguel; Sales, Francisco; Dourado, António

2012-09-30

Changes in the spatio-temporal behavior of the brain electrical activity are believed to be associated to epileptic brain states. We propose a novel methodology to identify the different states of the epileptic brain, based on the topographic mapping of the time varying relative power of delta, theta, alpha, beta and gamma frequency sub-bands, estimated from EEG. Using normalized-cuts segmentation algorithm, points of interest are identified in the topographic mappings and their trajectories over time are used for finding out relations with epileptogenic propagations in the brain. These trajectories are used to train a Hidden Markov Model (HMM), which models the different epileptic brain states and the transition among them. Applied to 10 patients suffering from focal seizures, with a total of 30 seizures over 497.3h of data, the methodology shows good results (an average point-by-point accuracy of 89.31%) for the identification of the four brain states--interictal, preictal, ictal and postictal. The results suggest that the spatio-temporal dynamics captured by the proposed methodology are related to the epileptic brain states and transitions involved in focal seizures. Copyright © 2012 Elsevier B.V. All rights reserved.

An integrated logistic formula for prediction of complications from radiosurgery

International Nuclear Information System (INIS)

Flickinger, J.C.

1989-01-01

An integrated logistic model for predicting the probability of complications when small volumes of tissue receive an inhomogeneous radiation dose is described. This model can be used with either an exponential or linear quadratic correction for dose per fraction and time. Both the exponential and linear quadratic versions of this integrated logistic formula provide reasonable estimates of the tolerance of brain to radiosurgical dose distributions where there are small volumes of brain receiving high radiation doses and larger volumes receiving lower doses. This makes it possible to predict the probability of complications from stereotactic radiosurgery, as well as combinations of fractionated large volume irradiation with a radiosurgical boost. Complication probabilities predicted for single fraction radiosurgery with the Leksell Gamma Unit using 4, 8, 14, and 18 mm diameter collimators as well as for whole brain irradiation combined with a radiosurgical boost are presented. The exponential and linear quadratic versions of the integrated logistic formula provide useful methods of calculating the probability of complications from radiosurgical treatment

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

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

2016-02-15

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

Fused cerebral organoids model interactions between brain regions.

Science.gov (United States)

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.

Early postnatal exposure to intermittent hypoxia in rodents is proinflammatory, impairs white matter integrity, and alters brain metabolism.

Science.gov (United States)

Darnall, Robert A; Chen, Xi; Nemani, Krishnamurthy V; Sirieix, Chrystelle M; Gimi, Barjor; Knoblach, Susan; McEntire, Betty L; Hunt, Carl E

2017-07-01

BackgroundPreterm infants are frequently exposed to intermittent hypoxia (IH) associated with apnea and periodic breathing that may result in inflammation and brain injury that later manifests as cognitive and executive function deficits. We used a rodent model to determine whether early postnatal exposure to IH would result in inflammation and brain injury.MethodsRat pups were exposed to IH from P2 to P12. Control animals were exposed to room air. Cytokines were analyzed in plasma and brain tissue at P13 and P18. At P20-P22, diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) were performed.ResultsPups exposed to IH had increased plasma Gro/CXCL1 and cerebellar IFN-γ and IL-1β at P13, and brainstem enolase at P18. DTI showed a decrease in FA and AD in the corpus callosum (CC) and cingulate gyrus, and an increase in RD in the CC. MRS revealed decreases in NAA/Cho, Cr, Tau/Cr, and Gly/Cr; increases in TCho and GPC in the brainstem; and decreases in NAA/Cho in the hippocampus.ConclusionsWe conclude that early postnatal exposure to IH, similar in magnitude to that experienced in human preterm infants, is associated with evidence for proinflammatory changes, decreases in white matter integrity, and metabolic changes consistent with hypoxia.

Modeling Structural Brain Connectivity

DEFF Research Database (Denmark)

Ambrosen, Karen Marie Sandø

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

Integrated Inflammatory Stress (ITIS) Model

DEFF Research Database (Denmark)

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

2017-01-01

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

Non-integrable quantum field theories as perturbations of certain integrable models

International Nuclear Information System (INIS)

Delfino, G.; Simonetti, P.

1996-03-01

We approach the study of non-integrable models of two-dimensional quantum field theory as perturbations of the integrable ones. By exploiting the knowledge of the exact S-matrix and Form Factors of the integrable field theories we obtain the first order corrections to the mass ratios, the vacuum energy density and the S-matrix of the non-integrable theories. As interesting applications of the formalism, we study the scaling region of the Ising model in an external magnetic field at T ∼ T c and the scaling region around the minimal model M 2 , τ . For these models, a remarkable agreement is observed between the theoretical predictions and the data extracted by a numerical diagonalization of their Hamiltonian. (author). 41 refs, 9 figs, 1 tab

A putative model of overeating and obesity based on brain-derived neurotrophic factor: direct and indirect effects.

Science.gov (United States)

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.

An architecture for integration of multidisciplinary models

DEFF Research Database (Denmark)

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

2014-01-01

Integrating multidisciplinary models requires linking models: that may operate at different temporal and spatial scales; developed using different methodologies, tools and techniques; different levels of complexity; calibrated for different ranges of inputs and outputs, etc. On the other hand......, Enterprise Application Integration, and Integration Design Patterns. We developed an architecture of a multidisciplinary model integration framework that brings these three aspects of integration together. Service-oriented-based platform independent architecture that enables to establish loosely coupled...

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

Science.gov (United States)

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

2017-03-01

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

Modelling glioblastoma tumour-host cell interactions using adult brain organotypic slice co-culture

Directory of Open Access Journals (Sweden)

Maria Angeles Marques-Torrejon

2018-02-01

Full Text Available Glioblastoma multiforme (GBM is an aggressive incurable brain cancer. The cells that fuel the growth of tumours resemble neural stem cells found in the developing and adult mammalian forebrain. These are referred to as glioma stem cells (GSCs. Similar to neural stem cells, GSCs exhibit a variety of phenotypic states: dormant, quiescent, proliferative and differentiating. How environmental cues within the brain influence these distinct states is not well understood. Laboratory models of GBM can be generated using either genetically engineered mouse models, or via intracranial transplantation of cultured tumour initiating cells (mouse or human. Unfortunately, these approaches are expensive, time-consuming, low-throughput and ill-suited for monitoring live cell behaviours. Here, we explored whole adult brain coronal organotypic slices as an alternative model. Mouse adult brain slices remain viable in a serum-free basal medium for several weeks. GSCs can be easily microinjected into specific anatomical sites ex vivo, and we demonstrate distinct responses of engrafted GSCs to diverse microenvironments in the brain tissue. Within the subependymal zone – one of the adult neural stem cell niches – injected tumour cells could effectively engraft and respond to endothelial niche signals. Tumour-transplanted slices were treated with the antimitotic drug temozolomide as proof of principle of the utility in modelling responses to existing treatments. Engraftment of mouse or human GSCs onto whole brain coronal organotypic brain slices therefore provides a simplified, yet flexible, experimental model. This will help to increase the precision and throughput of modelling GSC-host brain interactions and complements ongoing in vivo studies. This article has an associated First Person interview with the first author of the paper.

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

Science.gov (United States)

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.

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

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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

Data assimilation in integrated hydrological modelling

DEFF Research Database (Denmark)

Rasmussen, Jørn

Integrated hydrological models are useful tools for water resource management and research, and advances in computational power and the advent of new observation types has resulted in the models generally becoming more complex and distributed. However, the models are often characterized by a high...... degree of parameterization which results in significant model uncertainty which cannot be reduced much due to observations often being scarce and often taking the form of point measurements. Data assimilation shows great promise for use in integrated hydrological models , as it allows for observations...... to be efficiently combined with models to improve model predictions, reduce uncertainty and estimate model parameters. In this thesis, a framework for assimilating multiple observation types and updating multiple components and parameters of a catchment scale integrated hydrological model is developed and tested...

Statistical models for brain signals with properties that evolve across trials.

Science.gov (United States)

Ombao, Hernando; Fiecas, Mark; Ting, Chee-Ming; Low, Yin Fen

2017-12-07

Most neuroscience cognitive experiments involve repeated presentations of various stimuli across several minutes or a few hours. It has been observed that brain responses, even to the same stimulus, evolve over the course of the experiment. These changes in brain activation and connectivity are believed to be associated with learning and/or habituation. In this paper, we present two general approaches to modeling dynamic brain connectivity using electroencephalograms (EEGs) recorded across replicated trials in an experiment. The first approach is the Markovian regime-switching vector autoregressive model (MS-VAR) which treats EEGs as realizations of an underlying brain process that switches between different states both within a trial and across trials in the entire experiment. The second is the slowly evolutionary locally stationary process (SEv-LSP) which characterizes the observed EEGs as a mixture of oscillatory activities at various frequency bands. The SEv-LSP model captures the dynamic nature of the amplitudes of the band-oscillations and cross-correlations between them. The MS-VAR model is able to capture abrupt changes in the dynamics while the SEv-LSP directly gives interpretable results. Moreover, it is nonparametric and hence does not suffer from model misspecification. For both of these models, time-evolving connectivity metrics in the frequency domain are derived from the model parameters for both functional and effective connectivity. We illustrate these two models for estimating cross-trial connectivity in selective attention using EEG data from an oddball paradigm auditory experiment where the goal is to characterize the evolution of brain responses to target stimuli and to standard tones presented randomly throughout the entire experiment. The results suggest dynamic changes in connectivity patterns over trials with inter-subject variability. Copyright © 2017. Published by Elsevier Inc.

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain.

Directory of Open Access Journals (Sweden)

Lev E Givon

Full Text Available 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.

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

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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.

Dosha brain-types: A neural model of individual differences

Directory of Open Access Journals (Sweden)

Frederick T Travis

2015-01-01

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

Transcranial magnetic stimulation of mouse brain using high-resolution anatomical models

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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.

Permeability of PEGylated immunoarsonoliposomes through in vitro blood brain barrier-medulloblastoma co-culture models for brain tumor therapy.

Science.gov (United States)

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.

Enabling model customization and integration

Science.gov (United States)

Park, Minho; Fishwick, Paul A.

2003-09-01

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

Integrated modelling in materials and process technology

DEFF Research Database (Denmark)

Hattel, Jesper Henri

2008-01-01

Integrated modelling of entire process sequences and the subsequent in-service conditions, and multiphysics modelling of the single process steps are areas that increasingly support optimisation of manufactured parts. In the present paper, three different examples of modelling manufacturing...... processes from the viewpoint of combined materials and process modelling are presented: solidification of thin walled ductile cast iron, integrated modelling of spray forming and multiphysics modelling of friction stir welding. The fourth example describes integrated modelling applied to a failure analysis...

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

Science.gov (United States)

Inocian, Reynaldo B.

2015-01-01

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

A model based system for the interpretation of MR human brain scans

International Nuclear Information System (INIS)

Kapouleas, I.; Kulikowski, C.A.

1988-01-01

This paper describes a prototype system for identifying and characterizing Multiple Scleroris (MS) lesions in the brain from magnetic resonance (MR) images. The system is designed to obtain an initial segmentation of each cross-sectional image with low level vision methods, and then derive successive refinements of image subregions through a model-driven approach that correlates relevant information from T1 and T2 images and 3-D information from complementary cross-sections when necessary. The system uses a b-spline surface model of the brain that matches the characteristics of the individual's brain. The normal internal structures of the brain are then scaled proportionately before carrying out the successive refinement operations for the detection of the MS lesions. The low level vision and the solid modeling components of the system have been successfully tested on several hundred images from a number of MR patient studies. The first steps of model fitting have been implemented and show promising results

Proscription supports robust perceptual integration by suppression in human visual cortex.

Science.gov (United States)

Rideaux, Reuben; Welchman, Andrew E

2018-04-17

Perception relies on integrating information within and between the senses, but how does the brain decide which pieces of information should be integrated and which kept separate? Here we demonstrate how proscription can be used to solve this problem: certain neurons respond best to unrealistic combinations of features to provide 'what not' information that drives suppression of unlikely perceptual interpretations. First, we present a model that captures both improved perception when signals are consistent (and thus should be integrated) and robust estimation when signals are conflicting. Second, we test for signatures of proscription in the human brain. We show that concentrations of inhibitory neurotransmitter GABA in a brain region intricately involved in integrating cues (V3B/KO) correlate with robust integration. Finally, we show that perturbing excitation/inhibition impairs integration. These results highlight the role of proscription in robust perception and demonstrate the functional purpose of 'what not' sensors in supporting sensory estimation.

Exposure to traffic-generated air pollutants mediates alterations in brain microvascular integrity in wildtype mice on a high-fat diet.

Science.gov (United States)

Suwannasual, Usa; Lucero, JoAnn; McDonald, Jacob D; Lund, Amie K

2018-01-01

Air pollution-exposure is associated with detrimental outcomes in the central nervous system (CNS) such as cerebrovascular disorders, including stroke, and neurodegenerative diseases. While the mechanisms of these CNS-related outcomes involved have not been fully elucidated, exposure to traffic-generated air pollutants has been associated with altered blood brain barrier (BBB) integrity and permeability. The current study investigated whether inhalation exposure to mixed vehicle emissions (MVE) alters cerebral microvascular integrity in healthy 3 mo old C57BL/6 mice, as well as whether exposure-mediated effects were exacerbated by a high-fat (HF) vs. low-fat (LF) diet. Mice on each diet were randomly assigned to be exposed to either filtered air (FA) or MVE [100PM/m 3 vehicle emissions mixture: 30µg PM/m 3 gasoline engine + 70µg PM/m 3 diesel engine emissions; median size ~ 60nm; particle mass size distribution median of ~ 1µm (range: diet, results in altered BBB integrity and increased ox-LDL signaling in the cerebral vasculature in a wildtype animal model. Copyright © 2017 Elsevier Inc. All rights reserved.

An integrated development environment for PMESII model authoring, integration, validation, and debugging

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Pioch, Nicholas J.; Lofdahl, Corey; Sao Pedro, Michael; Krikeles, Basil; Morley, Liam

2007-04-01

To foster shared battlespace awareness in Air Operations Centers supporting the Joint Forces Commander and Joint Force Air Component Commander, BAE Systems is developing a Commander's Model Integration and Simulation Toolkit (CMIST), an Integrated Development Environment (IDE) for model authoring, integration, validation, and debugging. CMIST is built on the versatile Eclipse framework, a widely used open development platform comprised of extensible frameworks that enable development of tools for building, deploying, and managing software. CMIST provides two distinct layers: 1) a Commander's IDE for supporting staff to author models spanning the Political, Military, Economic, Social, Infrastructure, Information (PMESII) taxonomy; integrate multiple native (third-party) models; validate model interfaces and outputs; and debug the integrated models via intuitive controls and time series visualization, and 2) a PMESII IDE for modeling and simulation developers to rapidly incorporate new native simulation tools and models to make them available for use in the Commander's IDE. The PMESII IDE provides shared ontologies and repositories for world state, modeling concepts, and native tool characterization. CMIST includes extensible libraries for 1) reusable data transforms for semantic alignment of native data with the shared ontology, and 2) interaction patterns to synchronize multiple native simulations with disparate modeling paradigms, such as continuous-time system dynamics, agent-based discrete event simulation, and aggregate solution methods such as Monte Carlo sampling over dynamic Bayesian networks. This paper describes the CMIST system architecture, our technical approach to addressing these semantic alignment and synchronization problems, and initial results from integrating Political-Military-Economic models of post-war Iraq spanning multiple modeling paradigms.

Open source integrated modeling environment Delta Shell

Science.gov (United States)

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

2012-04-01

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

HMGB1 a-Box Reverses Brain Edema and Deterioration of Neurological Function in a Traumatic Brain Injury Mouse Model

Directory of Open Access Journals (Sweden)

Lijun Yang

2018-05-01

Full Text Available Background/Aims: 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. Methods: 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. Results: 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. Conclusion: 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.

HMGB1 a-Box Reverses Brain Edema and Deterioration of Neurological Function in a Traumatic Brain Injury Mouse Model.

Science.gov (United States)

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.

I-123 iomazenil single photon emission computed tomography for detecting loss of neuronal integrity in patients with traumatic brain injury.

Science.gov (United States)

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.

Computational brain models: Advances from system biology and future challenges

Directory of Open Access Journals (Sweden)

George E. Barreto

2015-02-01

Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

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

2017-07-01

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

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

Science.gov (United States)

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 functional BOLD perturbation modelling for forward fMRI and inverse mapping.

Science.gov (United States)

Chen, Zikuan; Robinson, Jennifer; Calhoun, Vince

2018-01-01

To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. 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. 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. 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.

Impairment of brain endothelial glucose transporter by methamphetamine causes blood-brain barrier dysfunction

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Murrin L Charles

2011-03-01

Full Text Available Abstract Background Methamphetamine (METH, an addictive psycho-stimulant drug with euphoric effect is known to cause neurotoxicity due to oxidative stress, dopamine accumulation and glial cell activation. Here we hypothesized that METH-induced interference of glucose uptake and transport at the endothelium can disrupt the energy requirement of the blood-brain barrier (BBB function and integrity. We undertake this study because there is no report of METH effects on glucose uptake and transport across the blood-brain barrier (BBB to date. Results In this study, we demonstrate that METH-induced disruption of glucose uptake by endothelium lead to BBB dysfunction. Our data indicate that a low concentration of METH (20 μM increased the expression of glucose transporter protein-1 (GLUT1 in primary human brain endothelial cell (hBEC, main component of BBB without affecting the glucose uptake. A high concentration of 200 μM of METH decreased both the glucose uptake and GLUT1 protein levels in hBEC culture. Transcription process appeared to regulate the changes in METH-induced GLUT1 expression. METH-induced decrease in GLUT1 protein level was associated with reduction in BBB tight junction protein occludin and zonula occludens-1. Functional assessment of the trans-endothelial electrical resistance of the cell monolayers and permeability of dye tracers in animal model validated the pharmacokinetics and molecular findings that inhibition of glucose uptake by GLUT1 inhibitor cytochalasin B (CB aggravated the METH-induced disruption of the BBB integrity. Application of acetyl-L-carnitine suppressed the effects of METH on glucose uptake and BBB function. Conclusion Our findings suggest that impairment of GLUT1 at the brain endothelium by METH may contribute to energy-associated disruption of tight junction assembly and loss of BBB integrity.

A porcine astrocyte/endothelial cell co-culture model of the blood-brain barrier.

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Jeliazkova-Mecheva, Valentina V; Bobilya, Dennis J

2003-10-01

A method for the isolation of porcine atrocytes as a simple extension of a previously described procedure for isolation of brain capillary endothelial cells from adolescent pigs [Methods Cell Sci. 17 (1995) 2] is described. The obtained astroglial culture purified through two passages and by the method of the selective detachment was validated by a phase contrast microscopy and through an immunofluorescent assay for the glial fibrillary acidic protein (GFAP). Porcine astrocytes were co-cultivated with porcine brain capillary endothelial cells (PBCEC) for the development of an in vitro blood-brain barrier (BBB) model. The model was visualized by an electron microscopy and showed elevated transendothellial electrical resistance and reduced inulin permeability. To our knowledge, this is the first report for the establishment of a porcine astrocyte/endothelial cell co-culture BBB model, which avoids interspecies and age differences between the two cell types, usually encountered in the other reported co-culture BBB models. Considering the availability of the porcine brain tissue and the close physiological and anatomical relation between the human and pig brain, the porcine astrocyte/endothelial cell co-culture system can serve as a reliable and easily reproducible model for different in vitro BBB studies.

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

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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.

Integrated Debugging of Modelica Models

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Adrian Pop

2014-04-01

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

Neural precursor cells in the ischemic brain - integration, cellular crosstalk and consequences for stroke recovery

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Dirk M. Hermann

2014-09-01

Full Text Available After an ischemic stroke, neural precursor cells (NPCs proliferate within major germinal niches of the brain. Endogenous NPCs subsequently migrate towards the ischemic lesion where they promote tissue remodelling and neural repair. Unfortunately, this restorative process is generally insufficient and thus unable to support a full recovery of lost neurological functions. Supported by solid experimental and preclinical data, the transplantation of exogenous NPCs has emerged as a potential tool for stroke treatment. Transplanted NPCs are thought to act mainly via trophic and immune modulatory effects, thereby complementing the restorative responses initially executed by the endogenous NPC population. Recent studies have attempted to elucidate how the therapeutic properties of transplanted NPCs vary depending on the route of transplantation. Systemic NPC delivery leads to potent immune modulatory actions, which prevent secondary neuronal degeneration, reduces glial scar formation, diminishes oxidative stress and stabilizes blood-brain barrier integrity. On the contrary, local stem cell delivery, allows for the accumulation of large numbers of transplanted NPCs in the brain, thus achieving high levels of locally available tissue trophic factors, which may better induce a strong endogenous NPC proliferative response.Herein we describe the diverse capabilities of exogenous (systemically vs locally transplanted NPCs in enhancing the endogenous neurogenic response after stroke, and how the route of transplantation may affect migration, survival, bystander effects and integration of the cellular graft. It is the authors’ claim that understanding these aspects will be of pivotal importance in discerning how transplanted NPCs exert their therapeutic effects in stroke.

Audio-tactile integration and the influence of musical training.

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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.

Audio-tactile integration and the influence of musical training.

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Anja Kuchenbuch

Full Text Available 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.

Amphiphilic HPMA-LMA copolymers increase the transport of Rhodamine 123 across a BBB model without harming its barrier integrity.

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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.

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

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

2016-11-03

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

A simulation model for analysing brain structure deformations

Energy Technology Data Exchange (ETDEWEB)

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

2003-12-21

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

Sigmund Freud-early network theories of the brain.

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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.

Contextualizing aquired brain damage

DEFF Research Database (Denmark)

Nielsen, Charlotte Marie Bisgaard

2014-01-01

Contextualizing aquired brain damage Traditional approaches study ’communicational problems’ often in a discourse of disabledness or deficitness. With an ontology of communcation as something unique and a presupposed uniqueness of each one of us, how could an integrational approach (Integrational...... for people with aquired brain injuries will be presented and comparatively discussed in a traditional versus an integrational perspective. Preliminary results and considerations on ”methods” and ”participation” from this study will be presented along with an overview of the project's empirical data....

A new model for diffuse brain injury by rotational acceleration: I model, gross appearance, and astrocytosis.

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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.

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

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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.

N-Terminal pro-Brain Natriuretic Peptide and Associations With Brain Magnetic Resonance Imaging (MRI Features in Middle Age: The CARDIA Brain MRI Study

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Ian T. Ferguson

2018-05-01

Full Text Available ObjectiveAs part of research on the heart–brain axis, we investigated the association of N-terminal pro-brain natriuretic peptide (NT-proBNP with brain structure and function in a community-based cohort of middle-aged adults from the Brain Magnetic Resonance Imaging sub-study of the Coronary Artery Risk Development in Young Adults (CARDIA Study.Approach and resultsIn a cohort of 634 community-dwelling adults with a mean (range age of 50.4 (46–52 years, we examined the cross-sectional association of NT-proBNP to total, gray (GM and white matter (WM volumes, abnormal WM load and WM integrity, and to cognitive function tests [the Digit Symbol Substitution Test (DSST, the Stroop test, and the Rey Auditory–Verbal Learning Test]. These associations were examined using linear regression models adjusted for demographic and cardiovascular risk factors and cardiac output. Higher NT-proBNP concentration was significantly associated with smaller GM volume (β = −3.44; 95% CI = −5.32, −0.53; p = 0.003, even after additionally adjusting for cardiac output (β = −2.93; 95% CI = −5.32, −0.53; p = 0.017. Higher NT-proBNP levels were also associated with lower DSST scores. NT-proBNP was not related to WM volume, WM integrity, or abnormal WM load.ConclusionIn this middle-aged cohort, subclinical levels of NT-proBNP were related to brain function and specifically to GM and not WM measures, extending similar findings in older cohorts. Further research is warranted into biomarkers of cardiac dysfunction as a target for early markers of a brain at risk.

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

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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.

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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.

The Simulation and Correction to the Brain Deformation Based on the Linear Elastic Model in IGS

Institute of Scientific and Technical Information of China (English)

MU Xiao-lan; SONG Zhi-jian

2004-01-01

@@ The brain deformation is a vital factor affecting the precision of the IGS and it becomes a hotspot to simulate and correct the brain deformation recently.The research organizations, which firstly resolved the brain deformation with the physical models, have the Image Processing and Analysis department of Yale University, Biomedical Modeling Lab of Vanderbilt University and so on. The former uses the linear elastic model; the latter uses the consolidation model.The linear elastic model only needs to drive the model using the surface displacement of exposed brain cortex,which is more convenient to be measured in the clinic.

Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

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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.

Characterization of a novel brain barrier ex vivo insect-based P-glycoprotein screening model

DEFF Research Database (Denmark)

Andersson, O.; Badisco, L.; Hansen, A. H.

2014-01-01

In earlier studies insects were proposed as suitable models for vertebrate blood–brain barrier (BBB) permeability prediction and useful in early drug discovery. Here we provide transcriptome and functional data demonstrating the presence of a P-glycoprotein (Pgp) efflux transporter in the brain b...... has the potential to act as a robust and convenient model for assessing BBB permeability in early drug discovery.......In earlier studies insects were proposed as suitable models for vertebrate blood–brain barrier (BBB) permeability prediction and useful in early drug discovery. Here we provide transcriptome and functional data demonstrating the presence of a P-glycoprotein (Pgp) efflux transporter in the brain...

Atomistic modeling of the structural components of the blood-brain barrier

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Glukhova, O. E.; Grishina, O. A.; Slepchenkov, M. M.

2015-03-01

Blood-brain barrier, which is a barrage system between the brain and blood vessels, plays a key role in the "isolation" of the brain of unnecessary information, and reduce the "noise" in the interneuron communication. It is known that the barrier function of the BBB strictly depends on the initial state of the organism and changes significantly with age and, especially in developing the "vascular accidents". Disclosure mechanisms of regulation of the barrier function will develop new ways to deliver neurotrophic drugs to the brain in the newborn. The aim of this work is the construction of atomistic models of structural components of the blood-brain barrier to reveal the mechanisms of regulation of the barrier function.

Cerebral volumes, neuronal integrity and brain inflammation measured by MRI in patients receiving PI monotherapy or triple therapy.

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Valero, Ignacio Pérez; Baeza, Alicia Gonzalez; Hernandez-Tamames, Juan Antonio; Monge, Susana; Arnalich, Francisco; Arribas, Jose Ramon

2014-01-01

Penetration of protease inhibitors (PI) in the central nervous system (CNS) is limited. Therefore, there are concerns about the capacity of PI monotherapy (MT) to control HIV in CNS and preserve brain integrity. Exploratory case-control study designed to compare neuronal integrity and brain inflammation in HIV-suppressed patients (>2 years) with and without neurocognitive impairment (NI), treated with MT or triple therapy (TT), 3-Tesla cerebral magnetic resonance image (MRI) and spectroscopy (MRS) were used to evaluate neuronal integrity (volume of cerebral structures and MRS levels of N-acetyl-aspartate (NAA)) and brain inflammation (MRS levels of myo-inositol (MI) and choline (CHO)). MRS biomarkers were measured in 4 voxels located in basal ganglia, frontal (2) and parietal lobes. A comprehensive battery of tests (14 tests - 7 domains) was used to diagnose neurocognitive impairment (1). We included 18 neurocognitively impaired patients (MT: 10, TT: 8) and 21 without NI (MT: 9; TT: 12, Table 1). Subset of patients with NI: cerebral volumes and MRS biomarkers were mostly similar between MT and TT with exception of the right cingulate nucleolus volume (MT: 8854±1851 vs TT: 10482±1107 mm(3); p<0.04), CHO levels in basal ganglia (MT: 0.44±0.05 vs TT: 0.37±0.03 MMOL/L; p<0.01) and the NAA levels in parietal lobe (MT: 1.49±0.12 vs 1.70±0.13 MMOL/L; p<0.01). Subset of patients without NI: cerebral volumes and MRS biomarkers were mostly similar between MT and TT with exception of MI levels in frontal lobe (MT: 1.20±0.36 vs 0.81±0.25 MMOL/L; p=0.01). We did not find significant differences in cerebral volumes or MRS biomarkers in most areas of the brain. However, we found higher levels of inflammation and neuronal damage in some brain areas of patients who received MT. This observation has to be taken into caution while we could not adjust our results by potential confounders. Further investigation is needed to confirm these preliminary results.

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

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Maria del C. Valdés Hernández

2017-07-01

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

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

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Rui F Oliveira

2014-07-01

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

Non-human Primate Models for Brain Disorders - Towards Genetic Manipulations via Innovative Technology.

Science.gov (United States)

Qiu, Zilong; Li, Xiao

2017-04-01

Modeling brain disorders has always been one of the key tasks in neurobiological studies. A wide range of organisms including worms, fruit flies, zebrafish, and rodents have been used for modeling brain disorders. However, whether complicated neurological and psychiatric symptoms can be faithfully mimicked in animals is still debatable. In this review, we discuss key findings using non-human primates to address the neural mechanisms underlying stress and anxiety behaviors, as well as technical advances for establishing genetically-engineered non-human primate models of autism spectrum disorders and other disorders. Considering the close evolutionary connections and similarity of brain structures between non-human primates and humans, together with the rapid progress in genome-editing technology, non-human primates will be indispensable for pathophysiological studies and exploring potential therapeutic methods for treating brain disorders.

Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

Science.gov (United States)

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.

A model to predict progression in brain-injured patients.

Science.gov (United States)

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.

TVB-EduPack - An interactive learning and scripting platform for The Virtual Brain

Directory of Open Access Journals (Sweden)

Henrik eMatzke

2015-11-01

Full Text Available The Virtual Brain (TVB; www.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 modelling 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 modelling; (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 modelling 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.

Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

Science.gov (United States)

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.

Measurement of human blood brain barrier integrity using 11C-inulin and positron emission tomography

International Nuclear Information System (INIS)

Hara, Toshihiko; Iio, Masaaki; Tsukiyama, Takashi

1988-01-01

Positron emission tomography (PET) using 11 C-inulin was demonstrated to be applicable to the clinical measurement of blood brain barrier permeability and cerebral interstitial fluid volume. Kinetic data were analyzed by application of a two compartment model, in which blood plasma and interstitial fluid spaces constitute the compartments. The blood activity contribution was subtracted from the PET count with the aid of the 11 CO inhalation technique. The values we estimated in a human brain were in agreement with the reported values obtained for animal brains by the use of 14 C-inulin. (orig.)

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

Science.gov (United States)

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

Modeling localized delivery of Doxorubicin to the brain following focused ultrasound enhanced blood-brain barrier permeability

International Nuclear Information System (INIS)

Nhan, Tam; Burgess, Alison; Hynynen, Kullervo; Lilge, Lothar

2014-01-01

Doxorubicin (Dox) is a well-established chemotherapeutic agent, however it has limited efficacy in treating brain malignancies due to the presence of the blood-brain barrier (BBB). Recent preclinical studies have demonstrated that focused ultrasound induced BBB disruption (BBBD) enables efficient delivery of Dox to the brain. For future treatment planning of BBBD-based drug delivery, it is crucial to establish a mathematical framework to predict the effect of transient BBB permeability enhancement on the spatiotemporal distribution of Dox at the targeted area. The constructed model considers Dox concentrations within three compartments (plasma, extracellular, intracellular) that are governed by various transport processes (e.g. diffusion in interstitial space, exchange across vessel wall, clearance by cerebral spinal fluid, uptake by brain cells). By examining several clinical treatment aspects (e.g. sonication scheme, permeability enhancement, injection mode), our simulation results support the experimental findings of optimal interval delay between two consecutive sonications and therapeutically-sufficient intracellular concentration with respect to transfer constant K trans range of 0.01–0.03 min −1 . Finally, the model suggests that infusion over a short duration (20–60 min) should be employed along with single-sonication or multiple-sonication at 10 min interval to ensure maximum delivery to the intracellular compartment while attaining minimal cardiotoxicity via suppressing peak plasma concentration. (paper)

A physical multifield model predicts the development of volume and structure in the human brain

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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.

Brain anatomical networks in early human brain development.

Science.gov (United States)

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.

Toward an Integrative Model of Global Business Strategy

DEFF Research Database (Denmark)

Li, Xin

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

The algorithmic level is the bridge between computation and brain.

Science.gov (United States)

Love, Bradley C

2015-04-01

Every scientist chooses a preferred level of analysis and this choice shapes the research program, even determining what counts as evidence. This contribution revisits Marr's (1982) three levels of analysis (implementation, algorithmic, and computational) and evaluates the prospect of making progress at each individual level. After reviewing limitations of theorizing within a level, two strategies for integration across levels are considered. One is top-down in that it attempts to build a bridge from the computational to algorithmic level. Limitations of this approach include insufficient theoretical constraint at the computation level to provide a foundation for integration, and that people are suboptimal for reasons other than capacity limitations. Instead, an inside-out approach is forwarded in which all three levels of analysis are integrated via the algorithmic level. This approach maximally leverages mutual data constraints at all levels. For example, algorithmic models can be used to interpret brain imaging data, and brain imaging data can be used to select among competing models. Examples of this approach to integration are provided. This merging of levels raises questions about the relevance of Marr's tripartite view. Copyright © 2015 Cognitive Science Society, Inc.

Model integration and the economics of nuclear power

International Nuclear Information System (INIS)

Lundgren, S.

1985-01-01

The author proposes and applies a specific approach to model integration, i.e. the merger of two or several independently developed models. The approach is intended for integrations of activity analysis sector models and applied general equilibrium models. Model integration makes it possible to extend the range of applicability of applied general equilibrium models by exploiting the information contained in sector models. It also makes it possible to evaluate the validity of the partial equilibrium analyses in which sector models often are employed. The proposed approach is used to integrate a sector model of electricity and heat production with a general equilibrium model of the Swedish economy. Both models have been constructed within the research programme. The author uses the integrated model to look at two issues concerning the role of nuclear power on the Swedish electricity market: What are the likely consequences of a nuclear power discontinuation and how does the nuclear power investment programme of the 1970's and the early 1980's compare with a socially efficient one. (Author)

Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons.

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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.

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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.

Science.gov (United States)

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.

The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

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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.

Modern model of integrated corporate communication

Directory of Open Access Journals (Sweden)

Milica Slijepčević

2018-03-01

Full Text Available The main purpose of this paper is to present the modern model of integrated corporate communication. Beside this, the authors will describe the changes occurring in the corporate environment and importance of changing the model of corporate communication. This paper also discusses the importance of implementation of the suggested model, the use of new media and effects of these changes on corporations. The approach used in this paper is the literature review. The authors explore the importance of implementation of the suggested model and the new media in corporate communication, both internal and external, addressing all the stakeholders and communication contents. The paper recommends implementation of a modern model of integrated corporate communication as a response to constant development of the new media and generation changes taking place. Practical implications: the modern model of integrated corporate communication can be used as an upgrade of the conventional communication models. This modern model empowers companies to sustain and build up the existing relationships with stakeholders, and to find out and create new relationships with stakeholders who were previously inaccessible and invisible.

Integration of design applications with building models

DEFF Research Database (Denmark)

Eastman, C. M.; Jeng, T. S.; Chowdbury, R.

1997-01-01

This paper reviews various issues in the integration of applications with a building model... (Truncated.)......This paper reviews various issues in the integration of applications with a building model... (Truncated.)...

Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders.

Science.gov (United States)

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.

Early post-natal exposure to intermittent hypoxia in rodents is pro-inflammatory, impairs white matter integrity and alters brain metabolism

Science.gov (United States)

Darnall, Robert A.; Chen, Xi; Nemani, Krishnamurthy V.; Sirieix, Chrystelle M.; Gimi, Barjor; Knoblach, Susan; McEntire, Betty L.; Hunt, Carl E.

2017-01-01

Background Preterm infants are frequently exposed to intermittent hypoxia (IH) associated with apnea and periodic breathing that may result in inflammation and brain injury that later manifests as cognitive and executive function deficits. We used a rodent model to determine whether early postnatal exposure to IH would result in inflammation and brain injury. Methods Rat pups were exposed to IH from P2–P12. Control animals were exposed to room air. Cytokines were analyzed in plasma and brain tissue at P13 and P18. At P20–P22, diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) were performed. Results Pups exposed to IH had increased plasma Gro/CXCL1 and cerebellar IFN-γ and IL-1β at P13, and brainstem enolase at P18. DTI showed a decrease in FA and AD in the corpus callosum (CC) and cingulate gyrus and an increase in RD in the CC. MRS revealed decreases in NAA/Cho, Cr, Tau/Cr and Gly/Cr and increases in TCho and GPC in the brainstem and decreases in NAA/Cho in the hippocampus. Conclusions We conclude that early postnatal exposure to IH, similar in magnitude experienced in human preterm infants, is associated with evidence for pro-inflammatory changes, decreases in white matter integrity, and metabolic changes consistent with hypoxia. PMID:28388601

Magnetic resonance spectroscopy of traumatic brain in SD rats model

International Nuclear Information System (INIS)

Li Ke; Li Yangbin; Li Zhiming; Huang Yong; Li Bin; Lu Guangming

2009-01-01

Objective: To assess the value and prospect of magnetic resonance spectroscopy (MRS) in early diagnosis of traumatic brain with traumatic brain model in SD rats. Methods: Traumatic brain modal was established in 40 male SD rats utilizing a weigh-drop device, and MRS was performed before trauma and 4,8,24 and 48 hours after trauma. The ratio of N-acetylaspartate/creatine (NAA/Ct) and choline/creatine (Cho/Cr) were calculated and compared with pathological findings respectively. Results: Axonal changes were confirmed in microscopic study 4 hours after injury. The ratio of NAA/Ct decreased distinctly at 4 hours after trauma, followed by a steadily recover at 8 hours, and no significant change from 24h to 48h. There was no significant change in the ratio of Cho/Cr before and after trauma. Conclusion: MRS can be used to monitor the metabolic changes of brain non-invasively. MRS could play a positive role in early diagnosis, prognosis and follow-up of traumatic brain. (authors)

In vitro blood-brain barrier models: current and perspective technologies.

Science.gov (United States)

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.

Model-integrating software components engineering flexible software systems

CERN Document Server

Derakhshanmanesh, Mahdi

2015-01-01

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

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

Science.gov (United States)

Bilkei-Gorzo, Andras

2014-05-01

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

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

Science.gov (United States)

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

2015-02-01

White matter hyperintensities (WMH) of presumed vascular origin are a common finding in brain magnetic resonance imaging of older individuals and contribute to cognitive and functional decline. It is unknown how WMH form, although white matter degeneration is characterized pathologically by demyelination, axonal loss, and rarefaction, often attributed to ischemia. Changes within normal-appearing white matter (NAWM) in subjects with WMH have also been reported but have not yet been fully characterized. Here, we describe the in vivo imaging signatures of both NAWM and WMH in a large group of community-dwelling older people of similar age using biomarkers derived from magnetic resonance imaging that collectively reflect white matter integrity, myelination, and brain water content. Fractional anisotropy (FA) and magnetization transfer ratio (MTR) were significantly lower, whereas mean diffusivity (MD) and longitudinal relaxation time (T1) were significantly higher, in WMH than NAWM (p curve, 0.982; 95% CI, 0.975-0.989). Furthermore, the level of deterioration of NAWM was strongly associated with the severity of WMH, with MD and T1 increasing and FA and MTR decreasing in NAWM with increasing WMH score, a relationship that was sustained regardless of distance from the WMH. These multimodal imaging data indicate that WMH have reduced structural integrity compared with surrounding NAWM, and MD provides the best discriminator between the 2 tissue classes even within the mild range of WMH severity, whereas FA, MTR, and T1 only start reflecting significant changes in tissue microstructure as WMH become more severe. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

BrainK for Structural Image Processing: Creating Electrical Models of the Human Head

Directory of Open Access Journals (Sweden)

Kai Li

2016-01-01

Full Text Available BrainK is a set of automated procedures for characterizing the tissues of the human head from MRI, CT, and photogrammetry images. The tissue segmentation and cortical surface extraction support the primary goal of modeling the propagation of electrical currents through head tissues with a finite difference model (FDM or finite element model (FEM created from the BrainK geometries. The electrical head model is necessary for accurate source localization of dense array electroencephalographic (dEEG measures from head surface electrodes. It is also necessary for accurate targeting of cerebral structures with transcranial current injection from those surface electrodes. BrainK must achieve five major tasks: image segmentation, registration of the MRI, CT, and sensor photogrammetry images, cortical surface reconstruction, dipole tessellation of the cortical surface, and Talairach transformation. We describe the approach to each task, and we compare the accuracies for the key tasks of tissue segmentation and cortical surface extraction in relation to existing research tools (FreeSurfer, FSL, SPM, and BrainVisa. BrainK achieves good accuracy with minimal or no user intervention, it deals well with poor quality MR images and tissue abnormalities, and it provides improved computational efficiency over existing research packages.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

Science.gov (United States)

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.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

Directory of Open Access Journals (Sweden)

Kabilar Gunalan

Full Text Available 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.

Early treatment with lyophilized plasma protects the brain in a large animal model of combined traumatic brain injury and hemorrhagic shock

DEFF Research Database (Denmark)

Imam, Ayesha M; Jin, Guang; Sillesen, Martin

2013-01-01

Combination of traumatic brain injury (TBI) and hemorrhagic shock (HS) can result in significant morbidity and mortality. We have previously shown that early administration of fresh frozen plasma (FFP) in a large animal model of TBI and HS reduces the size of the brain lesion as well as the assoc...... as the associated edema. However, FFP is a perishable product that is not well suited for use in the austere prehospital settings. In this study, we tested whether a shelf-stable, low-volume, lyophilized plasma (LSP) product was as effective as FFP.......Combination of traumatic brain injury (TBI) and hemorrhagic shock (HS) can result in significant morbidity and mortality. We have previously shown that early administration of fresh frozen plasma (FFP) in a large animal model of TBI and HS reduces the size of the brain lesion as well...

Endothelium-targeted overexpression of heat shock protein 27 ameliorates blood–brain barrier disruption after ischemic brain injury

Science.gov (United States)

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

SU-E-T-549: Modeling Relative Biological Effectiveness of Protons for Radiation Induced Brain Necrosis

International Nuclear Information System (INIS)

Mirkovic, D; Peeler, C; Grosshans, D; Titt, U; Taleei, R; Mohan, R

2015-01-01

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 to 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

Comparison of the dynamic behaviour of brain tissue and two model materials

NARCIS (Netherlands)

Brands, D.W.A.; Bovendeerd, P.H.M.; Peters, G.W.M.; Wismans, J.S.H.M.; Paas, M.H.J.W.; Bree, van J.L.M.J.; Brands, D.W.A.

1999-01-01

Linear viscoelastic material parameters of porcine brain tissue and two brain substitute/ materials for use in mechanical head models (edible bone gelatin and dielectric silicone gel) were determined in small deformation, oscillatory shear experiments. Frequencies to 1000 Hertz could be obtained

A mathematical model of endovascular heat transfer for human brain cooling

Science.gov (United States)

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.

Integrable models in classical and quantum mechanics

International Nuclear Information System (INIS)

Jurco, B.

1991-01-01

Integrable systems are investigated, especially the rational and trigonometric Gaudin models. The Gaudin models are diagonalized for the case of classical Lie algebras. Their relation to the other integrable models and to the quantum inverse scattering method is investigated. Applications in quantum optics and plasma physics are discussed. (author). 94 refs

Sensitivity analysis of brain morphometry based on MRI-derived surface models

Science.gov (United States)

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

MEASURING INFORMATION INTEGR-ATION MODEL FOR CAD/CMM

Institute of Scientific and Technical Information of China (English)

无

2003-01-01

A CAD/CMM workpiece modeling system based on IGES file is proposed. The modeling system is implemented by using a new method for labelling the tolerance items of 3D workpiece. The concept-"feature face" is used in the method. First the CAD data of workpiece are extracted and recognized automatically. Then a workpiece model is generated, which is the integration of pure 3D geometry form with its corresponding inspection items. The principle of workpiece modeling is also presented. At last, the experiment results are shown and correctness of the model is certified.

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

Science.gov (United States)

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

Science.gov (United States)

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

Integrated Site Model Process Model Report

International Nuclear Information System (INIS)

Booth, T.

2000-01-01

The Integrated Site Model (ISM) provides a framework for discussing the geologic features and properties of Yucca Mountain, which is being evaluated as a potential site for a geologic repository for the disposal of nuclear waste. The ISM is important to the evaluation of the site because it provides 3-D portrayals of site geologic, rock property, and mineralogic characteristics and their spatial variabilities. The ISM is not a single discrete model; rather, it is a set of static representations that provide three-dimensional (3-D), computer representations of site geology, selected hydrologic and rock properties, and mineralogic-characteristics data. These representations are manifested in three separate model components of the ISM: the Geologic Framework Model (GFM), the Rock Properties Model (RPM), and the Mineralogic Model (MM). The GFM provides a representation of the 3-D stratigraphy and geologic structure. Based on the framework provided by the GFM, the RPM and MM provide spatial simulations of the rock and hydrologic properties, and mineralogy, respectively. Functional summaries of the component models and their respective output are provided in Section 1.4. Each of the component models of the ISM considers different specific aspects of the site geologic setting. Each model was developed using unique methodologies and inputs, and the determination of the modeled units for each of the components is dependent on the requirements of that component. Therefore, while the ISM represents the integration of the rock properties and mineralogy into a geologic framework, the discussion of ISM construction and results is most appropriately presented in terms of the three separate components. This Process Model Report (PMR) summarizes the individual component models of the ISM (the GFM, RPM, and MM) and describes how the three components are constructed and combined to form the ISM

An automatic rat brain extraction method based on a deformable surface model.

Science.gov (United States)

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.

Development of a generalized integral jet model

DEFF Research Database (Denmark)

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

2017-01-01

Integral type models to describe stationary plumes and jets in cross-flows (wind) have been developed since about 1970. These models are widely used for risk analysis, to describe the consequences of many different scenarios. Alternatively, CFD codes are being applied, but computational requireme......Integral type models to describe stationary plumes and jets in cross-flows (wind) have been developed since about 1970. These models are widely used for risk analysis, to describe the consequences of many different scenarios. Alternatively, CFD codes are being applied, but computational...... requirements still limit the number of scenarios that can be dealt with using CFD only. The integral models, however, are not suited to handle transient releases, such as releases from pressurized equipment, where the initially high release rate decreases rapidly with time. Further, on gas ignition, a second...... model is needed to describe the rapid combustion of the flammable part of the plume (flash fire) and a third model has to be applied for the remaining jet fire. The objective of this paper is to describe the first steps of the development of an integral-type model describing the transient development...

Global Integration of the Hot-State Brain Network of Appetite Predicts Short Term Weight Loss in Older Adult

Directory of Open Access Journals (Sweden)

Brielle M Paolini

2015-05-01

Full Text Available 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, amygdala and the parahippocampal gyrus were highly integrated as evidenced by the results of a principal component analysis. 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

Model-Based Integration and Interpretation of Data

DEFF Research Database (Denmark)

Petersen, Johannes

2004-01-01

Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...

Modular Architecture for Integrated Model-Based Decision Support.

Science.gov (United States)

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.

Electric field calculations in brain stimulation based on finite elements

DEFF Research Database (Denmark)

Windhoff, Mirko; Opitz, Alexander; Thielscher, Axel

2013-01-01

The need for realistic electric field calculations in human noninvasive brain stimulation is undisputed to more accurately determine the affected brain areas. However, using numerical techniques such as the finite element method (FEM) is methodologically complex, starting with the creation...... of accurate head models to the integration of the models in the numerical calculations. These problems substantially limit a more widespread application of numerical methods in brain stimulation up to now. We introduce an optimized processing pipeline allowing for the automatic generation of individualized...... the successful usage of the pipeline in six subjects, including field calculations for transcranial magnetic stimulation and transcranial direct current stimulation. The quality of the head volume meshes is validated both in terms of capturing the underlying anatomy and of the well-shapedness of the mesh...

Modeling integrated biomass gasification business concepts

Science.gov (United States)

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

2011-01-01

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

Large Scale Functional Brain Networks Underlying Temporal Integration of Audio-Visual Speech Perception: An EEG Study.

Science.gov (United States)

Kumar, G Vinodh; Halder, Tamesh; Jaiswal, Amit K; Mukherjee, Abhishek; Roy, Dipanjan; Banerjee, Arpan

2016-01-01

Observable lip movements of the speaker influence perception of auditory speech. A classical example of this influence is reported by listeners who perceive an illusory (cross-modal) speech sound (McGurk-effect) when presented with incongruent audio-visual (AV) speech stimuli. Recent neuroimaging studies of AV speech perception accentuate the role of frontal, parietal, and the integrative brain sites in the vicinity of the superior temporal sulcus (STS) for multisensory speech perception. However, if and how does the network across the whole brain participates during multisensory perception processing remains an open question. We posit that a large-scale functional connectivity among the neural population situated in distributed brain sites may provide valuable insights involved in processing and fusing of AV speech. Varying the psychophysical parameters in tandem with electroencephalogram (EEG) recordings, we exploited the trial-by-trial perceptual variability of incongruent audio-visual (AV) speech stimuli to identify the characteristics of the large-scale cortical network that facilitates multisensory perception during synchronous and asynchronous AV speech. We evaluated the spectral landscape of EEG signals during multisensory speech perception at varying AV lags. Functional connectivity dynamics for all sensor pairs was computed using the time-frequency global coherence, the vector sum of pairwise coherence changes over time. During synchronous AV speech, we observed enhanced global gamma-band coherence and decreased alpha and beta-band coherence underlying cross-modal (illusory) perception compared to unisensory perception around a temporal window of 300-600 ms following onset of stimuli. During asynchronous speech stimuli, a global broadband coherence was observed during cross-modal perception at earlier times along with pre-stimulus decreases of lower frequency power, e.g., alpha rhythms for positive AV lags and theta rhythms for negative AV lags. Thus, our

BRAIN initiative: fast and parallel solver for real-time monitoring of the eddy current in the brain for TMS applications.

Science.gov (United States)

Sabouni, Abas; Pouliot, Philippe; Shmuel, Amir; Lesage, Frederic

2014-01-01

This paper introduce a fast and efficient solver for simulating the induced (eddy) current distribution in the brain during transcranial magnetic stimulation procedure. This solver has been integrated with MRI and neuronavigation software to accurately model the electromagnetic field and show eddy current in the head almost in real-time. To examine the performance of the proposed technique, we used a 3D anatomically accurate MRI model of the 25 year old female subject.

FIIND: Ferret Interactive Integrated Neurodevelopment Atlas

Directory of Open Access Journals (Sweden)

Roberto Toro

2018-03-01

Full Text Available The first days after birth in ferrets provide a privileged view of the development of a complex mammalian brain. Unlike mice, ferrets develop a rich pattern of deep neocortical folds and cortico- cortical connections. Unlike humans and other primates, whose brains are well differentiated and folded at birth, ferrets are born with a very immature and completely smooth neocortex: folds, neocortical regionalisation and cortico-cortical connectivity develop in ferrets during the first postnatal days. After a period of fast neocortical expansion, during which brain volume increases by up to a factor of 4 in 2 weeks, the ferret brain reaches its adult volume at about 6 weeks of age. Ferrets could thus become a major animal model to investigate the neurobiological correlates of the phenomena observed in human neuroimaging. Many of these phenomena, such as the relationship between brain folding, cortico-cortical connectivity and neocortical regionalisation cannot be investigated in mice, but could be investigated in ferrets. Our aim is to provide the research community with a detailed description of the development of a complex brain, necessary to better understand the nature of human neuroimaging data, create models of brain development, or analyse the relationship between multiple spatial scales. We have already started a project to constitute an open, collaborative atlas of ferret brain development, integrating multi-modal and multi-scale data. We have acquired data for 28 ferrets (4 animals per time point from P0 to adults, using high-resolution MRI and diffusion tensor imaging (DTI. We have developed an open-source pipeline to segment and produce – online – 3D reconstructions of brain MRI data. We propose to process the brains of 16 of our specimens (from P0 to P16 using high-throughput 3D histology, staining for cytoarchitectonic landmarks, neuronal progenitors and neurogenesis. This would allow us to relate the MRI data that we have already

Development of a Model for Whole Brain Learning of Physiology

Science.gov (United States)

Eagleton, Saramarie; Muller, Anton

2011-01-01

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

Integrated Medical Model – Chest Injury Model

Data.gov (United States)

National Aeronautics and Space Administration — The Exploration Medical Capability (ExMC) Element of NASA's Human Research Program (HRP) developed the Integrated Medical Model (IMM) to forecast the resources...

Probing the brain with molecular fMRI.

Science.gov (United States)

Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan

2018-04-09

One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.

Frequency dependence of complex moduli of brain tissue using a fractional Zener model

International Nuclear Information System (INIS)

Kohandel, M; Sivaloganathan, S; Tenti, G; Darvish, K

2005-01-01

Brain tissue exhibits viscoelastic behaviour. If loading times are substantially short, static tests are not sufficient to determine the complete viscoelastic behaviour of the material, and dynamic test methods are more appropriate. The concept of complex modulus of elasticity is a powerful tool for characterizing the frequency domain behaviour of viscoelastic materials. On the other hand, it is well known that classical viscoelastic models can be generalized by means of fractional calculus to describe more complex viscoelastic behaviour of materials. In this paper, the fractional Zener model is investigated in order to describe the dynamic behaviour of brain tissue. The model is fitted to experimental data of oscillatory shear tests of bovine brain tissue to verify its behaviour and to obtain the material parameters

Challenges in horizontal model integration.

Science.gov (United States)

Kolczyk, Katrin; Conradi, Carsten

2016-03-11

Systems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control. To answer important biomedical questions, however, one has to go beyond the study of isolated pathways towards the joint study of interacting signaling pathways or the joint study of signal transduction and cell cycle control. Thereby the reuse of established models is preferable, as it will generally reduce the modeling effort and increase the acceptance of the combined model in the field. Obtaining a combined model can be challenging, especially if the submodels are large and/or come from different working groups (as is generally the case, when models stored in established repositories are used). To support this task, we describe a semi-automatic workflow based on established software tools. In particular, two frequent challenges are described: identification of the overlap and subsequent (re)parameterization of the integrated model. The reparameterization step is crucial, if the goal is to obtain a model that can reproduce the data explained by the individual models. For demonstration purposes we apply our workflow to integrate two signaling pathways (EGF and NGF) from the BioModels Database.

Explaining brain size variation: from social to cultural brain.

Science.gov (United States)

van Schaik, Carel P; Isler, Karin; Burkart, Judith M

2012-05-01

Although the social brain hypothesis has found near-universal acceptance as the best explanation for the evolution of extensive variation in brain size among mammals, it faces two problems. First, it cannot account for grade shifts, where species or complete lineages have a very different brain size than expected based on their social organization. Second, it cannot account for the observation that species with high socio-cognitive abilities also excel in general cognition. These problems may be related. For birds and mammals, we propose to integrate the social brain hypothesis into a broader framework we call cultural intelligence, which stresses the importance of the high costs of brain tissue, general behavioral flexibility and the role of social learning in acquiring cognitive skills. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

2014-12-01

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

Comparison of a Rat Primary Cell-Based Blood-Brain Barrier Model With Epithelial and Brain Endothelial Cell Lines: Gene Expression and Drug Transport

Directory of Open Access Journals (Sweden)

Szilvia Veszelka

2018-05-01

Full Text Available Cell culture-based blood-brain barrier (BBB models are useful tools for screening of CNS drug candidates. Cell sources for BBB models include primary brain endothelial cells or immortalized brain endothelial cell lines. Despite their well-known differences, epithelial cell lines are also used as surrogate models for testing neuropharmaceuticals. The aim of the present study was to compare the expression of selected BBB related genes including tight junction proteins, solute carriers (SLC, ABC transporters, metabolic enzymes and to describe the paracellular properties of nine different culture models. To establish a primary BBB model rat brain capillary endothelial cells were co-cultured with rat pericytes and astrocytes (EPA. As other BBB and surrogate models four brain endothelial cells lines, rat GP8 and RBE4 cells, and human hCMEC/D3 cells with or without lithium treatment (D3 and D3L, and four epithelial cell lines, native human intestinal Caco-2 and high P-glycoprotein expressing vinblastine-selected VB-Caco-2 cells, native MDCK and MDR1 transfected MDCK canine kidney cells were used. To test transporter functionality, the permeability of 12 molecules, glucopyranose, valproate, baclofen, gabapentin, probenecid, salicylate, rosuvastatin, pravastatin, atorvastatin, tacrine, donepezil, was also measured in the EPA and epithelial models. Among the junctional protein genes, the expression level of occludin was high in all models except the GP8 and RBE4 cells, and each model expressed a unique claudin pattern. Major BBB efflux (P-glycoprotein or ABCB1 and influx transporters (GLUT-1, LAT-1 were present in all models at mRNA levels. The transcript of BCRP (ABCG2 was not expressed in MDCK, GP8 and RBE4 cells. The absence of gene expression of important BBB efflux and influx transporters BCRP, MRP6, -9, MCT6, -8, PHT2, OATPs in one or both types of epithelial models suggests that Caco-2 or MDCK models are not suitable to test drug candidates which

Differential Effects of High-Protein Diets Derived from Soy and Casein on Blood–Brain Barrier Integrity in Wild-type Mice

OpenAIRE

Matthew Snelson; Matthew Snelson; John C. L. Mamo; John C. L. Mamo; Virginie Lam; Virginie Lam; Corey Giles; Corey Giles; Ryusuke Takechi; Ryusuke Takechi

2017-01-01

A number of studies report that a diet high in protein influences cognitive performance, but the results are inconsistent. Studies demonstrated that protein from different food sources has differential effects on cognition. It is increasingly recognized that the integrity of cerebrovascular blood–brain barrier (BBB) is pivotal for central nervous system function. However, to date, no studies have reported the effects of high-protein diets on BBB integrity. Therefore, in this study, the effect...

Gravitational interactions of integrable models

International Nuclear Information System (INIS)

Abdalla, E.; Abdalla, M.C.B.

1995-10-01

We couple non-linear σ-models to Liouville gravity, showing that integrability properties of symmetric space models still hold for the matter sector. Using similar arguments for the fermionic counterpart, namely Gross-Neveu-type models, we verify that such conclusions must also hold for them, as recently suggested. (author). 18 refs

Human brain as the model of a new computer system. II

Energy Technology Data Exchange (ETDEWEB)

Holtz, K; Langheld, E

1981-12-09

For Pt. I see IBID., Vol. 29, No. 22, P. 13 (1981). The authors describe the self-generating system of connections of a self-teaching no-program associative computer. The self-generating systems of connections are regarded as simulation models of the human brain and compared with the brain structure. The system hardware comprises microprocessor, PROM, memory, VDU, keyboard unit.

Neurocomputational models of brain disorders

NARCIS (Netherlands)

Cutsuridis, Vassilis; Heida, Tjitske; Duch, Wlodek; Doya, Kenji

2011-01-01

Recent decades have witnessed dramatic accumulation of knowledge about the genetic, molecular, pharmacological, neurophysiological, anatomical, imaging and psychological characteristics of brain disorders. Despite these advances, however, experimental brain science has offered very little insight

Opioid Abuse after Traumatic Brain Injury: Evaluation Using Rodent Models

Science.gov (United States)

2015-09-01

craniotomy was cut with a trephine by hand over the right motor cortex . An injury cannula was fashioned from the hub of a female leur-lock 20g needle...ABSTRACT This project evaluated the effect of a moderate-level brain injury on risk for opioid abuse using preclinical models in rats . We assessed the...effect of brain injury on the rewarding effects of oxycodone in three rat self-administration procedures and found significant differences in the

Implantation of glioblastoma spheroids into organotypic brain slice cultures as a model for investigating effects of irradiation

DEFF Research Database (Denmark)

Petterson, Stine Asferg; Jakobsen, Ida Pind; Jensen, Stine Skov

2016-01-01

, models for studying the effects of radiotherapy in combination with novel strategies are lacking but important since radiotherapy is the most successful non-surgical treatment of brain tumors. The aim of this study was to establish a glioblastoma spheroid-organotypic rat brain slice culture model...... comprising both tumors, tumor-brain interface and brain tissue to provide a proof of concept that this model is useful for studying effects of radiotherapy. Organotypic brain slice cultures cultured for 1-2 days or 11-16 days corresponding to immature brain and mature brain respectively were irradiated...... with doses between 10 and 50 Gy. There was a high uptake of the cell death marker propidium iodide in the immature cultures. In addition, MAP2 expression decreased whereas GFAP expression increased in these cultures suggesting neuronal death and astrogliosis. We therefore proceeded with the mature cultures...

Cyclosporin safety in a simplified rat brain tumor implantation model

Directory of Open Access Journals (Sweden)

Francisco H. C. Felix

2012-01-01

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

Renewed mer model of integral management

Directory of Open Access Journals (Sweden)

Janko Belak

2015-12-01

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