Exploring the brain on multiple scales with correlative two-photon and light sheet microscopy

NASA Astrophysics Data System (ADS)

Silvestri, Ludovico; Allegra Mascaro, Anna Letizia; Costantini, Irene; Sacconi, Leonardo; Pavone, Francesco S.

2014-02-01

One of the unique features of the brain is that its activity cannot be framed in a single spatio-temporal scale, but rather spans many orders of magnitude both in space and time. A single imaging technique can reveal only a small part of this complex machinery. To obtain a more comprehensive view of brain functionality, complementary approaches should be combined into a correlative framework. Here, we describe a method to integrate data from in vivo two-photon fluorescence imaging and ex vivo light sheet microscopy, taking advantage of blood vessels as reference chart. We show how the apical dendritic arbor of a single cortical pyramidal neuron imaged in living thy1-GFP-M mice can be found in the large-scale brain reconstruction obtained with light sheet microscopy. Starting from the apical portion, the whole pyramidal neuron can then be segmented. The correlative approach presented here allows contextualizing within a three-dimensional anatomic framework the neurons whose dynamics have been observed with high detail in vivo.

Phenotypic integration of neurocranium and brain.

PubMed

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

2006-07-15

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

The impact of unilateral brain damage on anticipatory grip force scaling when lifting everyday objects.

PubMed

Eidenmüller, S; Randerath, J; Goldenberg, G; Li, Y; Hermsdörfer, J

2014-08-01

The scaling of our finger forces according to the properties of manipulated objects is an elementary prerequisite of skilled motor behavior. Lesions of the motor-dominant left brain may impair several aspects of motor planning. For example, limb-apraxia, a tool-use disorder after left brain damage is thought to be caused by deficient recall or integration of tool-use knowledge into an action plan. The aim of the present study was to investigate whether left brain damage affects anticipatory force scaling when lifting everyday objects. We examined 26 stroke patients with unilateral brain damage (16 with left brain damage, ten with right brain damage) and 21 healthy control subjects. Limb apraxia was assessed by testing pantomime of familiar tool-use and imitation of meaningless hand postures. Participants grasped and lifted twelve randomly presented everyday objects. Grip force was measured with help of sensors fixed on thumb, index and middle-finger. The maximum rate of grip force was determined to quantify the precision of anticipation of object properties. Regression analysis yielded clear deficits of anticipation in the group of patients with left brain damage, while the comparison of patient with right brain damage with their respective control group did not reveal comparable deficits. Lesion-analyses indicate that brain structures typically associated with a tool-use network in the left hemisphere play an essential role for anticipatory grip force scaling, especially the left inferior frontal gyrus (IFG) and the premotor cortex (PMC). Furthermore, significant correlations of impaired anticipation with limb apraxia scores suggest shared representations. However, the presence of dissociations, implicates also independent processes. Overall, our findings suggest that the left hemisphere is engaged in anticipatory grip force scaling for lifting everyday objects. The underlying neural substrate is not restricted to a single region or stream; instead it may rely on

Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues.

PubMed

Farisco, Michele; Kotaleski, Jeanette H; Evers, Kathinka

2018-01-01

Modeling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate the plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness (DOCs), e.g., Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State. Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs.

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

PubMed

Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

2016-01-01

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities. © 2015 Wiley Periodicals, Inc.

Foundational perspectives on causality in large-scale brain networks

NASA Astrophysics Data System (ADS)

Mannino, Michael; Bressler, Steven L.

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

Utility of the Croatian translation of the community integration questionnaire-revised in a sample of adults with moderate to severe traumatic brain injury.

PubMed

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

2018-02-23

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

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

PubMed

Morimoto, Jun; Kawato, Mitsuo

2015-03-06

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

The temporal structures and functional significance of scale-free brain activity

PubMed Central

He, Biyu J.; Zempel, John M.; Snyder, Abraham Z.; Raichle, Marcus E.

2010-01-01

SUMMARY Scale-free dynamics, with a power spectrum following P ∝ f-β, are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with β being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications. PMID:20471349

Foundational perspectives on causality in large-scale brain networks.

PubMed

Mannino, Michael; Bressler, Steven L

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

Functional atlas of the awake rat brain: A neuroimaging study of rat brain specialization and integration.

PubMed

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

2018-04-15

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

Multi-sensory integration in a small brain

NASA Astrophysics Data System (ADS)

Gepner, Ruben; Wolk, Jason; Gershow, Marc

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Cellular scaling rules for the brain of afrotherians

PubMed Central

Neves, Kleber; Ferreira, Fernanda M.; Tovar-Moll, Fernanda; Gravett, Nadine; Bennett, Nigel C.; Kaswera, Consolate; Gilissen, Emmanuel; Manger, Paul R.; Herculano-Houzel, Suzana

2014-01-01

Quantitative analysis of the cellular composition of rodent, primate and eulipotyphlan brains has shown that non-neuronal scaling rules are similar across these mammalian orders that diverged about 95 million years ago, and therefore appear to be conserved in evolution, while neuronal scaling rules appear to be free to vary in evolution in a clade-specific manner. Here we analyze the cellular scaling rules that apply to the brain of afrotherians, believed to be the first clade to radiate from the common eutherian ancestor. We find that afrotherians share non-neuronal scaling rules with rodents, primates and eulipotyphlans, as well as the coordinated scaling of numbers of neurons in the cerebral cortex and cerebellum. Afrotherians share with rodents and eulipotyphlans, but not with primates, the scaling of number of neurons in the cortex and in the cerebellum as a function of the number of neurons in the rest of the brain. Afrotheria also share with rodents and eulipotyphlans the neuronal scaling rules that apply to the cerebral cortex. Afrotherians share with rodents, but not with eulipotyphlans nor primates, the neuronal scaling rules that apply to the cerebellum. Importantly, the scaling of the folding index of the cerebral cortex with the number of neurons in the cerebral cortex is not shared by either afrotherians, rodents, or primates. The sharing of some neuronal scaling rules between afrotherians and rodents, and of some additional features with eulipotyphlans and primates, raise the interesting possibility that these shared characteristics applied to the common eutherian ancestor. In turn, the clade-specific characteristics that relate to the distribution of neurons along the surface of the cerebral cortex and to its degree of gyrification suggest that these characteristics compose an evolutionarily plastic suite of features that may have defined and distinguished mammalian groups in evolution. PMID:24596544

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

PubMed Central

Morimoto, Jun; Kawato, Mitsuo

2015-01-01

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

Updated Neuronal Scaling Rules for the Brains of Glires (Rodents/Lagomorphs)

PubMed Central

Herculano-Houzel, Suzana; Ribeiro, Pedro; Campos, Leandro; Valotta da Silva, Alexandre; Torres, Laila B.; Catania, Kenneth C.; Kaas, Jon H.

2011-01-01

Brain size scales as different functions of its number of neurons across mammalian orders such as rodents, primates, and insectivores. In rodents, we have previously shown that, across a sample of 6 species, from mouse to capybara, the cerebral cortex, cerebellum and the remaining brain structures increase in size faster than they gain neurons, with an accompanying decrease in neuronal density in these structures [Herculano-Houzel et al.: Proc Natl Acad Sci USA 2006;103:12138–12143]. Important remaining questions are whether such neuronal scaling rules within an order apply equally to all pertaining species, and whether they extend to closely related taxa. Here, we examine whether 4 other species of Rodentia, as well as the closely related rabbit (Lagomorpha), conform to the scaling rules identified previously for rodents. We report the updated neuronal scaling rules obtained for the average values of each species in a way that is directly comparable to the scaling rules that apply to primates [Gabi et al.: Brain Behav Evol 2010;76:32–44], and examine whether the scaling relationships are affected when phylogenetic relatedness in the dataset is accounted for. We have found that the brains of the spiny rat, squirrel, prairie dog and rabbit conform to the neuronal scaling rules that apply to the previous sample of rodents. The conformity to the previous rules of the new set of species, which includes the rabbit, suggests that the cellular scaling rules we have identified apply to rodents in general, and probably to Glires as a whole (rodents/lagomorphs), with one notable exception: the naked mole-rat brain is apparently an outlier, with only about half of the neurons expected from its brain size in its cerebral cortex and cerebellum. PMID:21985803

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

PubMed

Maex, Reinoud; Gutkin, Boris

2017-07-01

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

An allometric scaling relationship in the brain of preterm infants

PubMed Central

Paul, Rachel A; Smyser, Christopher D; Rogers, Cynthia E; English, Ian; Wallendorf, Michael; Alexopoulos, Dimitrios; Meyer, Erin J; Van Essen, David C; Neil, Jeffrey J; Inder, Terrie E

2014-01-01

Allometry has been used to demonstrate a power–law scaling relationship in the brain of premature born infants. Forty-nine preterm infants underwent neonatal MRI scans and neurodevelopmental testing at age 2. Measures of cortical surface area and total cerebral volume demonstrated a power–law scaling relationship (α = 1.27). No associations were identified between these measures and investigated clinical variables. Term equivalent cortical surface area and total cerebral volume measures and scaling exponents were not related to outcome. These findings confirm a previously reported allometric scaling relationship in the preterm brain, and suggest that scaling is not a sensitive indicator of aberrant cortical maturation. PMID:25540808

Salience network integrity predicts default mode network function after traumatic brain injury

PubMed Central

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

2012-01-01

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

Development of large-scale functional brain networks in children.

PubMed

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Development of Large-Scale Functional Brain Networks in Children

PubMed Central

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-01-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7–9 y) and 22 young-adults (ages 19–22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar “small-world” organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066

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

PubMed

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

2018-06-11

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

Meeting the memory challenges of brain-scale network simulation.

PubMed

Kunkel, Susanne; Potjans, Tobias C; Eppler, Jochen M; Plesser, Hans Ekkehard; Morrison, Abigail; Diesmann, Markus

2011-01-01

The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity, and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10(5) neurons with up to 10(9) synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been investigated in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Blue Gene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of neuronal simulators as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place. As a consequence, development cycles can be shorter and

An animal-to-human scaling law for blast-induced traumatic brain injury risk assessment.

PubMed

Jean, Aurélie; Nyein, Michelle K; Zheng, James Q; Moore, David F; Joannopoulos, John D; Radovitzky, Raúl

2014-10-28

Despite recent efforts to understand blast effects on the human brain, there are still no widely accepted injury criteria for humans. Recent animal studies have resulted in important advances in the understanding of brain injury due to intense dynamic loads. However, the applicability of animal brain injury results to humans remains uncertain. Here, we use advanced computational models to derive a scaling law relating blast wave intensity to the mechanical response of brain tissue across species. Detailed simulations of blast effects on the brain are conducted for different mammals using image-based biofidelic models. The intensity of the stress waves computed for different external blast conditions is compared across species. It is found that mass scaling, which successfully estimates blast tolerance of the thorax, fails to capture the brain mechanical response to blast across mammals. Instead, we show that an appropriate scaling variable must account for the mass of protective tissues relative to the brain, as well as their acoustic impedance. Peak stresses transmitted to the brain tissue by the blast are then shown to be a power function of the scaling parameter for a range of blast conditions relevant to TBI. In particular, it is found that human brain vulnerability to blast is higher than for any other mammalian species, which is in distinct contrast to previously proposed scaling laws based on body or brain mass. An application of the scaling law to recent experiments on rabbits furnishes the first physics-based injury estimate for blast-induced TBI in humans.

Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues

PubMed Central

Farisco, Michele; Kotaleski, Jeanette H.; Evers, Kathinka

2018-01-01

Modeling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain’s operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate the plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness (DOCs), e.g., Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State. Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs. PMID:29740372

C5a alters blood-brain barrier integrity in experimental lupus

PubMed Central

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

2010-01-01

The blood-brain barrier (BBB) is a crucial anatomic location in the brain. Its dysfunction complicates many neurodegenerative diseases, from acute conditions, such as sepsis, to chronic diseases, such as systemic lupus erythematosus (SLE). Several studies suggest an altered BBB in lupus, but the underlying mechanism remains unknown. In the current study, we observed a definite loss of BBB integrity in MRL/MpJ-Tnfrsf6lpr (MRL/lpr) lupus mice by IgG infiltration into brain parenchyma. In line with this result, we examined the role of complement activation, a key event in this setting, in maintenance of BBB integrity. Complement activation generates C5a, a molecule with multiple functions. Because the expression of the C5a receptor (C5aR) is significantly increased in brain endothelial cells treated with lupus serum, the study focused on the role of C5a signaling through its G-protein-coupled receptor C5aR in brain endothelial cells, in a lupus setting. Reactive oxygen species production increased significantly in endothelial cells, in both primary cells and the bEnd3 cell line treated with lupus serum from MRL/lpr mice, compared with those treated with control serum from MRL+/+ mice. In addition, increased permeability monitored by changes in transendothelial electrical resistance, cytoskeletal remodeling caused by actin fiber rearrangement, and increased iNOS mRNA expression were observed in bEnd3 cells. These disruptive effects were alleviated by pretreating cells with a C5a receptor antagonist (C5aRant) or a C5a antibody. Furthermore, the structural integrity of the vasculature in MRL/lpr brain was maintained by C5aR inhibition. These results demonstrate the regulation of BBB integrity by the complement system in a neuroinflammatory setting. For the first time, a novel role of C5a in the maintenance of BBB integrity is identified and the potential of C5a/C5aR blockade highlighted as a promising therapeutic strategy in SLE and other neurodegenerative diseases

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

PubMed

Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh

2018-06-25

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Spatiotemporal dynamics of large-scale brain activity

NASA Astrophysics Data System (ADS)

Neuman, Jeremy

Understanding the dynamics of large-scale brain activity is a tough challenge. One reason for this is the presence of an incredible amount of complexity arising from having roughly 100 billion neurons connected via 100 trillion synapses. Because of the extremely high number of degrees of freedom in the nervous system, the question of how the brain manages to properly function and remain stable, yet also be adaptable, must be posed. Neuroscientists have identified many ways the nervous system makes this possible, of which synaptic plasticity is possibly the most notable one. On the other hand, it is vital to understand how the nervous system also loses stability, resulting in neuropathological diseases such as epilepsy, a disease which affects 1% of the population. In the following work, we seek to answer some of these questions from two different perspectives. The first uses mean-field theory applied to neuronal populations, where the variables of interest are the percentages of active excitatory and inhibitory neurons in a network, to consider how the nervous system responds to external stimuli, self-organizes and generates epileptiform activity. The second method uses statistical field theory, in the framework of single neurons on a lattice, to study the concept of criticality, an idea borrowed from physics which posits that in some regime the brain operates in a collectively stable or marginally stable manner. This will be examined in two different neuronal networks with self-organized criticality serving as the overarching theme for the union of both perspectives. One of the biggest problems in neuroscience is the question of to what extent certain details are significant to the functioning of the brain. These details give rise to various spatiotemporal properties that at the smallest of scales explain the interaction of single neurons and synapses and at the largest of scales describe, for example, behaviors and sensations. In what follows, we will shed some

What Brain Sciences Reveal about Integrating Theory and Practice

ERIC Educational Resources Information Center

Patton, Michael Quinn

2014-01-01

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

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

DTIC Science & Technology

2015-12-22

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

Generate the scale-free brain music from BOLD signals

PubMed Central

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Abstract Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen–Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon–Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. PMID:29480872

Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

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

Gorilla and Orangutan Brains Conform to the Primate Cellular Scaling Rules: Implications for Human Evolution

PubMed Central

Herculano-Houzel, Suzana; Kaas, Jon H.

2011-01-01

Gorillas and orangutans are primates at least as large as humans, but their brains amount to about one third of the size of the human brain. This discrepancy has been used as evidence that the human brain is about 3 times larger than it should be for a primate species of its body size. In contrast to the view that the human brain is special in its size, we have suggested that it is the great apes that might have evolved bodies that are unusually large, on the basis of our recent finding that the cellular composition of the human brain matches that expected for a primate brain of its size, making the human brain a linearly scaled-up primate brain in its number of cells. To investigate whether the brain of great apes also conforms to the primate cellular scaling rules identified previously, we determine the numbers of neuronal and other cells that compose the orangutan and gorilla cerebella, use these numbers to calculate the size of the brain and of the cerebral cortex expected for these species, and show that these match the sizes described in the literature. Our results suggest that the brains of great apes also scale linearly in their numbers of neurons like other primate brains, including humans. The conformity of great apes and humans to the linear cellular scaling rules that apply to other primates that diverged earlier in primate evolution indicates that prehistoric Homo species as well as other hominins must have had brains that conformed to the same scaling rules, irrespective of their body size. We then used those scaling rules and published estimated brain volumes for various hominin species to predict the numbers of neurons that composed their brains. We predict that Homo heidelbergensis and Homo neanderthalensis had brains with approximately 80 billion neurons, within the range of variation found in modern Homo sapiens. We propose that while the cellular scaling rules that apply to the primate brain have remained stable in hominin evolution (since they

Gorilla and orangutan brains conform to the primate cellular scaling rules: implications for human evolution.

PubMed

Herculano-Houzel, Suzana; Kaas, Jon H

2011-01-01

Gorillas and orangutans are primates at least as large as humans, but their brains amount to about one third of the size of the human brain. This discrepancy has been used as evidence that the human brain is about 3 times larger than it should be for a primate species of its body size. In contrast to the view that the human brain is special in its size, we have suggested that it is the great apes that might have evolved bodies that are unusually large, on the basis of our recent finding that the cellular composition of the human brain matches that expected for a primate brain of its size, making the human brain a linearly scaled-up primate brain in its number of cells. To investigate whether the brain of great apes also conforms to the primate cellular scaling rules identified previously, we determine the numbers of neuronal and other cells that compose the orangutan and gorilla cerebella, use these numbers to calculate the size of the brain and of the cerebral cortex expected for these species, and show that these match the sizes described in the literature. Our results suggest that the brains of great apes also scale linearly in their numbers of neurons like other primate brains, including humans. The conformity of great apes and humans to the linear cellular scaling rules that apply to other primates that diverged earlier in primate evolution indicates that prehistoric Homo species as well as other hominins must have had brains that conformed to the same scaling rules, irrespective of their body size. We then used those scaling rules and published estimated brain volumes for various hominin species to predict the numbers of neurons that composed their brains. We predict that Homo heidelbergensis and Homo neanderthalensis had brains with approximately 80 billion neurons, within the range of variation found in modern Homo sapiens. We propose that while the cellular scaling rules that apply to the primate brain have remained stable in hominin evolution (since they

Amplitude-integrated EEG in newborns with critical congenital heart disease predicts preoperative brain magnetic resonance imaging findings.

PubMed

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

2015-06-01

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

Consciousness, information integration, and the brain.

PubMed

Tononi, Giulio

2005-01-01

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

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

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

2018-01-01

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

Generate the scale-free brain music from BOLD signals.

PubMed

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon-Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

C5a alters blood-brain barrier integrity in experimental lupus.

PubMed

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

2010-06-01

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

Very Large Scale Integration (VLSI).

ERIC Educational Resources Information Center

Yeaman, Andrew R. J.

Very Large Scale Integration (VLSI), the state-of-the-art production techniques for computer chips, promises such powerful, inexpensive computing that, in the future, people will be able to communicate with computer devices in natural language or even speech. However, before full-scale VLSI implementation can occur, certain salient factors must be…

Integrating Traumatic Brain Injury Model Systems Data into the Federal Interagency Traumatic Brain Injury Research Informatics Systems

DTIC Science & Technology

2016-10-01

Traumatic Brain Injury Research Informatics Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-14-1-0564 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...AWARD NUMBER: W81XWH-14-1-0564 TITLE: Integrating Traumatic Brain Injury Model Systems Data into the Federal Interagency Traumatic Brain Injury...Research Informatics Systems PRINCIPAL INVESTIGATOR: Cynthia Harrison-Felix, PhD CONTRACTING ORGANIZATION: Craig Hospital Englewood, CO 80113

Fifth dimension of life and the 4/5 allometric scaling law for human brain.

PubMed

He, Ji-Huan; Zhang, Juan

2004-01-01

Brain cells are not spherical. The basal metabolic rate (B) of a spherical cell scales as B approximately r2, where r is the radius of the cell; that of a brain cell scales as B approximately r(d), where r is the characteristic radius of the cell and d is the fractal dimensionality of its contour. The fractal geometry of the cell leads to a 4/5 allometric scaling law for human brain, uniquely endowing humans with a 5th dimension and successfully explains why the scaling exponent varies during rest and exercise. A striking analogy between Kleiber's 3/4 law and Newton's second law is heuristically illustrated. A physical explanation is given for the 4th dimension of life for three-dimensional organisms and the 5th dimension for human brain.

Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales

PubMed Central

Hogstrom, L. J.; Guo, S. M.; Murugadoss, K.; Bathe, M.

2016-01-01

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure. PMID:26855758

Integrating Retinoic Acid Signaling with Brain Function

ERIC Educational Resources Information Center

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

2009-01-01

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

Scale-Free Music of the Brain

PubMed Central

Wu, Dan; Li, Chao-Yi; Yao, De-Zhong

2009-01-01

Background There is growing interest in the relation between the brain and music. The appealing similarity between brainwaves and the rhythms of music has motivated many scientists to seek a connection between them. A variety of transferring rules has been utilized to convert the brainwaves into music; and most of them are mainly based on spectra feature of EEG. Methodology/Principal Findings In this study, audibly recognizable scale-free music was deduced from individual Electroencephalogram (EEG) waveforms. The translation rules include the direct mapping from the period of an EEG waveform to the duration of a note, the logarithmic mapping of the change of average power of EEG to music intensity according to the Fechner's law, and a scale-free based mapping from the amplitude of EEG to music pitch according to the power law. To show the actual effect, we applied the deduced sonification rules to EEG segments recorded during rapid-eye movement sleep (REM) and slow-wave sleep (SWS). The resulting music is vivid and different between the two mental states; the melody during REM sleep sounds fast and lively, whereas that in SWS sleep is slow and tranquil. 60 volunteers evaluated 25 music pieces, 10 from REM, 10 from SWS and 5 from white noise (WN), 74.3% experienced a happy emotion from REM and felt boring and drowsy when listening to SWS, and the average accuracy for all the music pieces identification is 86.8%(κ = 0.800, P<0.001). We also applied the method to the EEG data from eyes closed, eyes open and epileptic EEG, and the results showed these mental states can be identified by listeners. Conclusions/Significance The sonification rules may identify the mental states of the brain, which provide a real-time strategy for monitoring brain activities and are potentially useful to neurofeedback therapy. PMID:19526057

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

PubMed

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

2015-03-01

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2006-02-01

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

Genomic integrity and the ageing brain.

PubMed

Chow, Hei-man; Herrup, Karl

2015-11-01

DNA damage is correlated with and may drive the ageing process. Neurons in the brain are postmitotic and are excluded from many forms of DNA repair; therefore, neurons are vulnerable to various neurodegenerative diseases. The challenges facing the field are to understand how and when neuronal DNA damage accumulates, how this loss of genomic integrity might serve as a 'time keeper' of nerve cell ageing and why this process manifests itself as different diseases in different individuals.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

1998-01-01

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

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

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

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

2009-09-01

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

Weighted and directed interactions in evolving large-scale epileptic brain networks

NASA Astrophysics Data System (ADS)

Dickten, Henning; Porz, Stephan; Elger, Christian E.; Lehnertz, Klaus

2016-10-01

Epilepsy can be regarded as a network phenomenon with functionally and/or structurally aberrant connections in the brain. Over the past years, concepts and methods from network theory substantially contributed to improve the characterization of structure and function of these epileptic networks and thus to advance understanding of the dynamical disease epilepsy. We extend this promising line of research and assess—with high spatial and temporal resolution and using complementary analysis approaches that capture different characteristics of the complex dynamics—both strength and direction of interactions in evolving large-scale epileptic brain networks of 35 patients that suffered from drug-resistant focal seizures with different anatomical onset locations. Despite this heterogeneity, we find that even during the seizure-free interval the seizure onset zone is a brain region that, when averaged over time, exerts strongest directed influences over other brain regions being part of a large-scale network. This crucial role, however, manifested by averaging on the population-sample level only - in more than one third of patients, strongest directed interactions can be observed between brain regions far off the seizure onset zone. This may guide new developments for individualized diagnosis, treatment and control.

Integration of miRNA and Protein Profiling Reveals Coordinated Neuroadaptations in the Alcohol-Dependent Mouse Brain

PubMed Central

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

2013-01-01

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

Integrated Genomic and Epigenomic Analysis of Breast Cancer Brain Metastasis

PubMed Central

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

2014-01-01

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

An Integrated Scale for Measuring an Organizational Learning System

ERIC Educational Resources Information Center

Jyothibabu, C.; Farooq, Ayesha; Pradhan, Bibhuti Bhusan

2010-01-01

Purpose: The purpose of this paper is to develop an integrated measurement scale for an organizational learning system by capturing the learning enablers, learning results and performance outcome in an organization. Design/methodology/approach: A new measurement scale was developed by integrating and modifying two existing scales, identified…

Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders

PubMed Central

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

2017-01-01

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

3-D in vivo brain tumor geometry study by scaling analysis

NASA Astrophysics Data System (ADS)

Torres Hoyos, F.; Martín-Landrove, M.

2012-02-01

A new method, based on scaling analysis, is used to calculate fractal dimension and local roughness exponents to characterize in vivo 3-D tumor growth in the brain. Image acquisition was made according to the standard protocol used for brain radiotherapy and radiosurgery, i.e., axial, coronal and sagittal magnetic resonance T1-weighted images, and comprising the brain volume for image registration. Image segmentation was performed by the application of the k-means procedure upon contrasted images. We analyzed glioblastomas, astrocytomas, metastases and benign brain tumors. The results show significant variations of the parameters depending on the tumor stage and histological origin.

Social factors predictive of social integration for adults with brain injury.

PubMed

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

2018-08-01

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

Chip-scale sensor system integration for portable health monitoring.

PubMed

Jokerst, Nan M; Brooke, Martin A; Cho, Sang-Yeon; Shang, Allan B

2007-12-01

The revolution in integrated circuits over the past 50 yr has produced inexpensive computing and communications systems that are powerful and portable. The technologies for these integrated chip-scale sensing systems, which will be miniature, lightweight, and portable, are emerging with the integration of sensors with electronics, optical systems, micromachines, microfluidics, and the integration of chemical and biological materials (soft/wet material integration with traditional dry/hard semiconductor materials). Hence, we stand at a threshold for health monitoring technology that promises to provide wearable biochemical sensing systems that are comfortable, inauspicious, wireless, and battery-operated, yet that continuously monitor health status, and can transmit compressed data signals at regular intervals, or alarm conditions immediately. In this paper, we explore recent results in chip-scale sensor integration technology for health monitoring. The development of inexpensive chip-scale biochemical optical sensors, such as microresonators, that are customizable for high sensitivity coupled with rapid prototyping will be discussed. Ground-breaking work in the integration of chip-scale optical systems to support these optical sensors will be highlighted, and the development of inexpensive Si complementary metal-oxide semiconductor circuitry (which makes up the vast majority of computational systems today) for signal processing and wireless communication with local receivers that lie directly on the chip-scale sensor head itself will be examined.

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

PubMed Central

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

2015-01-01

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

Integrated simulation of continuous-scale and discrete-scale radiative transfer in metal foams

NASA Astrophysics Data System (ADS)

Xia, Xin-Lin; Li, Yang; Sun, Chuang; Ai, Qing; Tan, He-Ping

2018-06-01

A novel integrated simulation of radiative transfer in metal foams is presented. It integrates the continuous-scale simulation with the direct discrete-scale simulation in a single computational domain. It relies on the coupling of the real discrete-scale foam geometry with the equivalent continuous-scale medium through a specially defined scale-coupled zone. This zone holds continuous but nonhomogeneous volumetric radiative properties. The scale-coupled approach is compared to the traditional continuous-scale approach using volumetric radiative properties in the equivalent participating medium and to the direct discrete-scale approach employing the real 3D foam geometry obtained by computed tomography. All the analyses are based on geometrical optics. The Monte Carlo ray-tracing procedure is used for computations of the absorbed radiative fluxes and the apparent radiative behaviors of metal foams. The results obtained by the three approaches are in tenable agreement. The scale-coupled approach is fully validated in calculating the apparent radiative behaviors of metal foams composed of very absorbing to very reflective struts and that composed of very rough to very smooth struts. This new approach leads to a reduction in computational time by approximately one order of magnitude compared to the direct discrete-scale approach. Meanwhile, it can offer information on the local geometry-dependent feature and at the same time the equivalent feature in an integrated simulation. This new approach is promising to combine the advantages of the continuous-scale approach (rapid calculations) and direct discrete-scale approach (accurate prediction of local radiative quantities).

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

PubMed Central

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

2014-01-01

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

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

PubMed

Stockton, David B; Santamaria, Fidel

2017-10-01

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

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

PubMed

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

2018-01-01

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

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

PubMed

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

2017-01-01

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

The Metastable Brain

PubMed Central

Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

Neural ensembles oscillate across a broad range of frequencies and are transiently coupled or “bound” together when people attend to a stimulus, perceive, think and act. This is a dynamic, self-assembling process, with parts of the brain engaging and disengaging in time. But how is it done? The theory of Coordination Dynamics proposes a mechanism called metastability, a subtle blend of integration and segregation. Tendencies for brain regions to express their individual autonomy and specialized functions (segregation, modularity) coexist with tendencies to couple and coordinate globally for multiple functions (integration). Although metastability has garnered increasing attention, it has yet to be demonstrated and treated within a fully spatiotemporal perspective. Here, we illustrate metastability in continuous neural and behavioral recordings, and we discuss theory and experiments at multiple scales suggesting that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic cognitive, behavioral and social functions. PMID:24411730

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

PubMed

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

2018-04-01

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

Normative brain size variation and brain shape diversity in humans.

PubMed

Reardon, P K; Seidlitz, Jakob; Vandekar, Simon; Liu, Siyuan; Patel, Raihaan; Park, Min Tae M; Alexander-Bloch, Aaron; Clasen, Liv S; Blumenthal, Jonathan D; Lalonde, Francois M; Giedd, Jay N; Gur, Ruben C; Gur, Raquel E; Lerch, Jason P; Chakravarty, M Mallar; Satterthwaite, Theodore D; Shinohara, Russell T; Raznahan, Armin

2018-06-15

Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Seizure Control and Memory Impairment Are Related to Disrupted Brain Functional Integration in Temporal Lobe Epilepsy.

PubMed

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

2017-01-01

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

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

PubMed Central

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

2013-01-01

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

Functional integrity in children with anoxic brain injury from drowning.

PubMed

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

2017-10-01

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

Scaling of graphene integrated circuits.

PubMed

Bianchi, Massimiliano; Guerriero, Erica; Fiocco, Marco; Alberti, Ruggero; Polloni, Laura; Behnam, Ashkan; Carrion, Enrique A; Pop, Eric; Sordan, Roman

2015-05-07

The influence of transistor size reduction (scaling) on the speed of realistic multi-stage integrated circuits (ICs) represents the main performance metric of a given transistor technology. Despite extensive interest in graphene electronics, scaling efforts have so far focused on individual transistors rather than multi-stage ICs. Here we study the scaling of graphene ICs based on transistors from 3.3 to 0.5 μm gate lengths and with different channel widths, access lengths, and lead thicknesses. The shortest gate delay of 31 ps per stage was obtained in sub-micron graphene ROs oscillating at 4.3 GHz, which is the highest oscillation frequency obtained in any strictly low-dimensional material to date. We also derived the fundamental Johnson limit, showing that scaled graphene ICs could be used at high frequencies in applications with small voltage swing.

Power law scaling in synchronization of brain signals depends on cognitive load.

PubMed

Tinker, Jesse; Velazquez, Jose Luis Perez

2014-01-01

As it has several features that optimize information processing, it has been proposed that criticality governs the dynamics of nervous system activity. Indications of such dynamics have been reported for a variety of in vitro and in vivo recordings, ranging from in vitro slice electrophysiology to human functional magnetic resonance imaging. However, there still remains considerable debate as to whether the brain actually operates close to criticality or in another governing state such as stochastic or oscillatory dynamics. A tool used to investigate the criticality of nervous system data is the inspection of power-law distributions. Although the findings are controversial, such power-law scaling has been found in different types of recordings. Here, we studied whether there is a power law scaling in the distribution of the phase synchronization derived from magnetoencephalographic recordings during executive function tasks performed by children with and without autism. Characterizing the brain dynamics that is different between autistic and non-autistic individuals is important in order to find differences that could either aid diagnosis or provide insights as to possible therapeutic interventions in autism. We report in this study that power law scaling in the distributions of a phase synchrony index is not very common and its frequency of occurrence is similar in the control and the autism group. In addition, power law scaling tends to diminish with increased cognitive load (difficulty or engagement in the task). There were indications of changes in the probability distribution functions for the phase synchrony that were associated with a transition from power law scaling to lack of power law (or vice versa), which suggests the presence of phenomenological bifurcations in brain dynamics associated with cognitive load. Hence, brain dynamics may fluctuate between criticality and other regimes depending upon context and behaviors.

Topological Properties of Some Integrated Circuits for Very Large Scale Integration Chip Designs

NASA Astrophysics Data System (ADS)

Swanson, S.; Lanzerotti, M.; Vernizzi, G.; Kujawski, J.; Weatherwax, A.

2015-03-01

This talk presents topological properties of integrated circuits for Very Large Scale Integration chip designs. These circuits can be implemented in very large scale integrated circuits, such as those in high performance microprocessors. Prior work considered basic combinational logic functions and produced a mathematical framework based on algebraic topology for integrated circuits composed of logic gates. Prior work also produced an historically-equivalent interpretation of Mr. E. F. Rent's work for today's complex circuitry in modern high performance microprocessors, where a heuristic linear relationship was observed between the number of connections and number of logic gates. This talk will examine topological properties and connectivity of more complex functionally-equivalent integrated circuits. The views expressed in this article are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense or the U.S. Government.

Miniaturized integration of a fluorescence microscope

PubMed Central

Ghosh, Kunal K.; Burns, Laurie D.; Cocker, Eric D.; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J.

2013-01-01

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals towards relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including semiconductor light source and sensor. This device enables high-speed cellular-level imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens. PMID:21909102

Miniaturized integration of a fluorescence microscope.

PubMed

Ghosh, Kunal K; Burns, Laurie D; Cocker, Eric D; Nimmerjahn, Axel; Ziv, Yaniv; Gamal, Abbas El; Schnitzer, Mark J

2011-09-11

The light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals for relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including a semiconductor light source and sensor. This device enables high-speed cellular imaging across ∼0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to many animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens.

Return to productive activity after traumatic brain injury: relationship with measures of disability, handicap, and community integration.

PubMed

Wagner, Amy K; Hammond, Flora M; Sasser, Howell C; Wiercisiewski, David

2002-01-01

To identify which factors are associated with successful return to productive activity (RTPA) 1 year after hospitalization with traumatic brain injury (TBI) and to examine the relations between successful RTPA and other measures of impairment, disability, handicap, and integration into the community. Prospective study with 1-year follow-up. Level I trauma center. One hundred five respondents from a cohort of 378 adults hospitalized with TBI admitted between September 1997 and May 1998. Not applicable. Return to productive work 1 year after injury; Disability Rating Scale (DRS); and Community Integration Scale (CIQ). Of the 105 participants, 72% achieved RTPA. Logistic regression showed an association between RPTA and the following factors: premorbid educational level, premorbid psychiatric history, violent mechanism of injury, discharge status after acute hospitalization, prior alcohol and drug use, and injury severity. Handicap and community integration at 1-year postinjury, as measured by subscales of the DRS and the CIQ, were also associated with RTPA. Premorbid and injury-related variables and measures of handicap and community integration were associated with RTPA at 1 year. To understand and effectively support vocational pursuits in the TBI population, future studies are needed to define further causality and origin of these relationships. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

Participation in a social and recreational day programme increases community integration and reduces family burden of persons with acquired brain injury.

PubMed

Gerber, Gary J; Gargaro, Judith

2015-01-01

To describe and evaluate a new day programme for persons living with an acquired brain injury (ABI), including persons exhibiting challenging behaviours. Activities were designed to reduce participants' social isolation, increase participation in community activities and increase social and leisure skills. It was expected that community integration would increase and challenging behaviours and family burden would decrease for day programme participants. Pre-post convenience sample design. Sixty-one participants and family members completed questionnaires before starting the day programme and after 6-month participation. Community Integration Questionnaire, Overt Behaviour Scale, Burden Assessment Scale, Goal Attainment Scaling. Participants had increased community integration (p = 0.000) and decreased family burden (p = 0.006). There was a trend to decreased severity of challenging behaviour. Participants and family members were very satisfied. Results suggest that the programme was effective in reducing participants' social isolation and increasing appropriate interpersonal behaviours. Participation increased community integration and reduced burden on family caregivers. ABI day programmes help fill the void left after other rehabilitation services end and provide survivors with opportunities to engage in a variety of activities. Persons living with ABI have need for ongoing social, recreational and life skill coaching services after formal rehabilitation has been completed.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Large-Scale Brain Systems in ADHD: Beyond the Prefrontal-Striatal Model

PubMed Central

Castellanos, F. Xavier; Proal, Erika

2012-01-01

Attention-deficit/hyperactivity disorder (ADHD) has long been thought to reflect dysfunction of prefrontal-striatal circuitry, with involvement of other circuits largely ignored. Recent advances in systems neuroscience-based approaches to brain dysfunction enable the development of models of ADHD pathophysiology that encompass a number of different large-scale “resting state” networks. Here we review progress in delineating large-scale neural systems and illustrate their relevance to ADHD. We relate frontoparietal, dorsal attentional, motor, visual, and default networks to the ADHD functional and structural literature. Insights emerging from mapping intrinsic brain connectivity networks provide a potentially mechanistic framework for understanding aspects of ADHD, such as neuropsychological and behavioral inconsistency, and the possible role of primary visual cortex in attentional dysfunction in the disorder. PMID:22169776

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

PubMed Central

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

2011-01-01

A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i) differences in weighted costs and (ii) differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration. PMID:21829437

Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.

Probing the brain with molecular fMRI.

PubMed

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

2018-06-01

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.

Integrated Photonic Neural Probes for Patterned Brain Stimulation

DTIC Science & Technology

2017-08-14

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

Integrative Understanding of Emergent Brain Properties, Quantum Brain Hypotheses, and Connectome Alterations in Dementia are Key Challenges to Conquer Alzheimer's Disease.

PubMed

Kuljiš, Rodrigo O

2010-01-01

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

Large-Scale Functional Brain Network Reorganization During Taoist Meditation.

PubMed

Jao, Tun; Li, Chia-Wei; Vértes, Petra E; Wu, Changwei Wesley; Achard, Sophie; Hsieh, Chao-Hsien; Liou, Chien-Hui; Chen, Jyh-Horng; Bullmore, Edward T

2016-02-01

Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network, mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally, whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.

Intraoperative virtual brain counseling

NASA Astrophysics Data System (ADS)

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

1997-06-01

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

Impact of Blood-Brain Barrier Integrity on Tumor Growth and Therapy Response in Brain Metastases.

PubMed

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

2016-12-15

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

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

PubMed Central

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

2015-01-01

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

Angiotensin receptors and β-catenin regulate brain endothelial integrity in malaria

PubMed Central

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

2016-01-01

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

Segregated Systems of Human Brain Networks.

PubMed

Wig, Gagan S

2017-12-01

The organization of the brain network enables its function. Evaluation of this organization has revealed that large-scale brain networks consist of multiple segregated subnetworks of interacting brain areas. Descriptions of resting-state network architecture have provided clues for understanding the functional significance of these segregated subnetworks, many of which correspond to distinct brain systems. The present report synthesizes accumulating evidence to reveal how maintaining segregated brain systems renders the human brain network functionally specialized, adaptable to task demands, and largely resilient following focal brain damage. The organizational properties that support system segregation are harmonious with the properties that promote integration across the network, but confer unique and important features to the brain network that are central to its function and behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantifying white matter structural integrity with high-definition fiber tracking in traumatic brain injury.

PubMed

Presson, Nora; Krishnaswamy, Deepa; Wagener, Lauren; Bird, William; Jarbo, Kevin; Pathak, Sudhir; Puccio, Ava M; Borasso, Allison; Benso, Steven; Okonkwo, David O; Schneider, Walter

2015-03-01

There is an urgent, unmet demand for definitive biological diagnosis of traumatic brain injury (TBI) to pinpoint the location and extent of damage. We have developed High-Definition Fiber Tracking, a 3 T magnetic resonance imaging-based diffusion spectrum imaging and tractography analysis protocol, to quantify axonal injury in military and civilian TBI patients. A novel analytical methodology quantified white matter integrity in patients with TBI and healthy controls. Forty-one subjects (23 TBI, 18 controls) were scanned with the High-Definition Fiber Tracking diffusion spectrum imaging protocol. After reconstruction, segmentation was used to isolate bilateral hemisphere homologues of eight major tracts. Integrity of segmented tracts was estimated by calculating homologue correlation and tract coverage. Both groups showed high correlations for all tracts. TBI patients showed reduced homologue correlation and tract spread and increased outlier count (correlations>2.32 SD below control mean). On average, 6.5% of tracts in the TBI group were outliers with substantial variability among patients. Number and summed deviation of outlying tracts correlated with initial Glasgow Coma Scale score and 6-month Glasgow Outcome Scale-Extended score. The correlation metric used here can detect heterogeneous damage affecting a low proportion of tracts, presenting a potential mechanism for advancing TBI diagnosis. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Wafer integrated micro-scale concentrating photovoltaics

NASA Astrophysics Data System (ADS)

Gu, Tian; Li, Duanhui; Li, Lan; Jared, Bradley; Keeler, Gordon; Miller, Bill; Sweatt, William; Paap, Scott; Saavedra, Michael; Das, Ujjwal; Hegedus, Steve; Tauke-Pedretti, Anna; Hu, Juejun

2017-09-01

Recent development of a novel micro-scale PV/CPV technology is presented. The Wafer Integrated Micro-scale PV approach (WPV) seamlessly integrates multijunction micro-cells with a multi-functional silicon platform that provides optical micro-concentration, hybrid photovoltaic, and mechanical micro-assembly. The wafer-embedded micro-concentrating elements is shown to considerably improve the concentration-acceptance-angle product, potentially leading to dramatically reduced module materials and fabrication costs, sufficient angular tolerance for low-cost trackers, and an ultra-compact optical architecture, which makes the WPV module compatible with commercial flat panel infrastructures. The PV/CPV hybrid architecture further allows the collection of both direct and diffuse sunlight, thus extending the geographic and market domains for cost-effective PV system deployment. The WPV approach can potentially benefits from both the high performance of multijunction cells and the low cost of flat plate Si PV systems.

Scale-free brain quartet: artistic filtering of multi-channel brainwave music.

PubMed

Wu, Dan; Li, Chaoyi; Yao, Dezhong

2013-01-01

To listen to the brain activities as a piece of music, we proposed the scale-free brainwave music (SFBM) technology, which translated scalp EEGs into music notes according to the power law of both EEG and music. In the present study, the methodology was extended for deriving a quartet from multi-channel EEGs with artistic beat and tonality filtering. EEG data from multiple electrodes were first translated into MIDI sequences by SFBM, respectively. Then, these sequences were processed by a beat filter which adjusted the duration of notes in terms of the characteristic frequency. And the sequences were further filtered from atonal to tonal according to a key defined by the analysis of the original music pieces. Resting EEGs with eyes closed and open of 40 subjects were utilized for music generation. The results revealed that the scale-free exponents of the music before and after filtering were different: the filtered music showed larger variety between the eyes-closed (EC) and eyes-open (EO) conditions, and the pitch scale exponents of the filtered music were closer to 1 and thus it was more approximate to the classical music. Furthermore, the tempo of the filtered music with eyes closed was significantly slower than that with eyes open. With the original materials obtained from multi-channel EEGs, and a little creative filtering following the composition process of a potential artist, the resulted brainwave quartet opened a new window to look into the brain in an audible musical way. In fact, as the artistic beat and tonal filters were derived from the brainwaves, the filtered music maintained the essential properties of the brain activities in a more musical style. It might harmonically distinguish the different states of the brain activities, and therefore it provided a method to analyze EEGs from a relaxed audio perspective.

Scale-Free Brain Quartet: Artistic Filtering of Multi-Channel Brainwave Music

PubMed Central

Wu, Dan; Li, Chaoyi; Yao, Dezhong

2013-01-01

To listen to the brain activities as a piece of music, we proposed the scale-free brainwave music (SFBM) technology, which translated scalp EEGs into music notes according to the power law of both EEG and music. In the present study, the methodology was extended for deriving a quartet from multi-channel EEGs with artistic beat and tonality filtering. EEG data from multiple electrodes were first translated into MIDI sequences by SFBM, respectively. Then, these sequences were processed by a beat filter which adjusted the duration of notes in terms of the characteristic frequency. And the sequences were further filtered from atonal to tonal according to a key defined by the analysis of the original music pieces. Resting EEGs with eyes closed and open of 40 subjects were utilized for music generation. The results revealed that the scale-free exponents of the music before and after filtering were different: the filtered music showed larger variety between the eyes-closed (EC) and eyes-open (EO) conditions, and the pitch scale exponents of the filtered music were closer to 1 and thus it was more approximate to the classical music. Furthermore, the tempo of the filtered music with eyes closed was significantly slower than that with eyes open. With the original materials obtained from multi-channel EEGs, and a little creative filtering following the composition process of a potential artist, the resulted brainwave quartet opened a new window to look into the brain in an audible musical way. In fact, as the artistic beat and tonal filters were derived from the brainwaves, the filtered music maintained the essential properties of the brain activities in a more musical style. It might harmonically distinguish the different states of the brain activities, and therefore it provided a method to analyze EEGs from a relaxed audio perspective. PMID:23717527

Gait and Glasgow Coma Scale scores can predict functional recovery in patients with traumatic brain injury☆

PubMed Central

Bilgin, Sevil; Guclu-Gunduz, Arzu; Oruckaptan, Hakan; Kose, Nezire; Celik, Bülent

2012-01-01

Fifty-one patients with mild (n = 14), moderate (n = 10) and severe traumatic brain injury (n = 27) received early rehabilitation. Level of consciousness was evaluated using the Glasgow Coma Score. Functional level was determined using the Glasgow Outcome Score, whilst mobility was evaluated using the Mobility Scale for Acute Stroke. Activities of daily living were assessed using the Barthel Index. Following Bobath neurodevelopmental therapy, the level of consciousness was significantly improved in patients with moderate and severe traumatic brain injury, but was not greatly influenced in patients with mild traumatic brain injury. Mobility and functional level were significantly improved in patients with mild, moderate and severe traumatic brain injury. Gait recovery was more obvious in patients with mild traumatic brain injury than in patients with moderate and severe traumatic brain injury. Activities of daily living showed an improvement but this was insignificant except for patients with severe traumatic brain injury. Nevertheless, complete recovery was not acquired at discharge. Multiple regression analysis showed that gait and Glasgow Coma Scale scores can be considered predictors of functional outcomes following traumatic brain injury. PMID:25624828

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

PubMed

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Scale relativity theory and integrative systems biology: 1. Founding principles and scale laws.

PubMed

Auffray, Charles; Nottale, Laurent

2008-05-01

In these two companion papers, we provide an overview and a brief history of the multiple roots, current developments and recent advances of integrative systems biology and identify multiscale integration as its grand challenge. Then we introduce the fundamental principles and the successive steps that have been followed in the construction of the scale relativity theory, and discuss how scale laws of increasing complexity can be used to model and understand the behaviour of complex biological systems. In scale relativity theory, the geometry of space is considered to be continuous but non-differentiable, therefore fractal (i.e., explicitly scale-dependent). One writes the equations of motion in such a space as geodesics equations, under the constraint of the principle of relativity of all scales in nature. To this purpose, covariant derivatives are constructed that implement the various effects of the non-differentiable and fractal geometry. In this first review paper, the scale laws that describe the new dependence on resolutions of physical quantities are obtained as solutions of differential equations acting in the scale space. This leads to several possible levels of description for these laws, from the simplest scale invariant laws to generalized laws with variable fractal dimensions. Initial applications of these laws to the study of species evolution, embryogenesis and cell confinement are discussed.

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Mems: Platform for Large-Scale Integrated Vacuum Electronic Circuits

DTIC Science & Technology

2017-03-20

SECURITY CLASSIFICATION OF: The objective of the LIVEC advanced study project was to develop a platform for large-scale integrated vacuum electronic ...Distribution Unlimited UU UU UU UU 20-03-2017 1-Jul-2014 30-Jun-2015 Final Report: MEMS Platform for Large-Scale Integrated Vacuum Electronic ... Electronic Circuits (LIVEC) Contract No: W911NF-14-C-0093 COR Dr. James Harvey U.S. ARO RTP, NC 27709-2211 Phone: 702-696-2533 e-mail

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

PubMed Central

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

2015-01-01

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

Integrative Review: Post-Craniotomy Pain in the Brain Tumor Patient

PubMed Central

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

2015-01-01

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

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept.

PubMed

Franke, Barbara; Stein, Jason L; Ripke, Stephan; Anttila, Verneri; Hibar, Derrek P; van Hulzen, Kimm J E; Arias-Vasquez, Alejandro; Smoller, Jordan W; Nichols, Thomas E; Neale, Michael C; McIntosh, Andrew M; Lee, Phil; McMahon, Francis J; Meyer-Lindenberg, Andreas; Mattheisen, Manuel; Andreassen, Ole A; Gruber, Oliver; Sachdev, Perminder S; Roiz-Santiañez, Roberto; Saykin, Andrew J; Ehrlich, Stefan; Mather, Karen A; Turner, Jessica A; Schwarz, Emanuel; Thalamuthu, Anbupalam; Shugart, Yin Yao; Ho, Yvonne Yw; Martin, Nicholas G; Wright, Margaret J; O'Donovan, Michael C; Thompson, Paul M; Neale, Benjamin M; Medland, Sarah E; Sullivan, Patrick F

2016-03-01

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

Assessing emotional status following acquired brain injury: the clinical potential of the depression, anxiety and stress scales.

PubMed

Ownsworth, Tamara; Little, Trudi; Turner, Ben; Hawkes, Anna; Shum, David

2008-10-01

To investigate the clinical potential of the Depression, Anxiety and Stress Scales (DASS 42) and its shorter version (DASS 21) for assessing emotional status following acquired brain injury. Participants included 23 individuals with traumatic brain injury (TBI), 25 individuals with brain tumour and 29 non-clinical controls. Investigations of internal consistency, test-re-test reliability, theory-consistent differences, sensitivity to change and concurrent validity were conducted. Internal consistency of the DASS was generally acceptable (r > 0.70), with the exception of the anxiety scale for the TBI sample. Test-re-test reliability (1-3 weeks) was sound for the depression scale (r > 0.75) and significant but comparatively lower for other scales (r = 0.60-0.73, p < 0.01). Theory-consistent differences were only evident between the brain tumour sample and non-clinical control sample on the anxiety scale (p < 0.01). Sensitivity to change of the DASS in the context of hospital discharge was demonstrated for depression and stress (p < 0.01), but not for anxiety (p > 0.05). Concurrent validity with the Hospital Anxiety and Depression Scale was significant for all scales of the DASS (p < 0.05). While the results generally support the clinical application of the DASS following ABI, further research examining the factor structure of existing and modified versions of the DASS is recommended.

The Human Thalamus Is an Integrative Hub for Functional Brain Networks

PubMed Central

Bertolero, Maxwell A.

2017-01-01

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

PPAR-gamma agonist pioglitazone modifies craving intensity and brain white matter integrity in patients with primary cocaine use disorder: a double-blind randomized controlled pilot trial.

PubMed

Schmitz, Joy M; Green, Charles E; Hasan, Khader M; Vincent, Jessica; Suchting, Robert; Weaver, Michael F; Moeller, F Gerard; Narayana, Ponnada A; Cunningham, Kathryn A; Dineley, Kelly T; Lane, Scott D

2017-10-01

Pioglitazone (PIO), a potent agonist of PPAR-gamma, is a promising candidate treatment for cocaine use disorder (CUD). We tested the effects of PIO on targeted mechanisms relevant to CUD: cocaine craving and brain white matter (WM) integrity. Feasibility, medication compliance and tolerability were evaluated. Two-arm double-blind randomized controlled proof-of-concept pilot trial of PIO or placebo (PLC). Single-site out-patient treatment research clinic in Houston, TX, USA. Thirty treatment-seeking adults, 18 to 60 years old, with CUD. Eighteen participants (8 = PIO; 10 = PLC) completed diffusion tensor imaging (DTI) of WM integrity at pre-/post-treatment. Study medication was dispensed at thrice weekly visits along with once-weekly cognitive behavioral therapy for 12 weeks. Measures of target engagement mechanisms of interest included cocaine craving assessed by the Brief Substance Craving Scale (BSCS), the Obsessive Compulsive Drug Use Scale (OCDUS), a visual analog scale (VAS) and change in WM integrity. Feasibility measures included number completing treatment, medication compliance (riboflavin detection) and tolerability (side effects, serious adverse events). Target engagement change in mechanisms of interest, defined as a ≥ 0.75 Bayesian posterior probability of an interaction existing favoring PIO over PLC, was demonstrated on measures of craving (BSCS, VAS) and WM integrity indexed by fractional anisotropy (FA) values. Outcomes indicated greater decrease in craving and greater increase in FA values in the PIO group. Feasibility was demonstrated by high completion rates among those starting treatment (21/26 = 80%) and medication compliance (≥ 80%). There were no reported serious adverse events for PIO. Compared with placebo, patients receiving pioglitazone show a higher likelihood of reduced cocaine craving and improved brain white matter integrity as a function of time in treatment. Pioglitazone shows good feasibility as a treatment for cocaine

Validation of the Early Functional Abilities scale: An assessment of four dimensions in early recovery after traumatic brain injury.

PubMed

Poulsen, Ingrid; Kreiner, Svend; Engberg, Aase W

2018-02-13

The Early Functional Abilities scale assesses the restoration of brain function after brain injury, based on 4 dimensions. The primary objective of this study was to evaluate the validity, objectivity, reliability and measurement precision of the Early Functional Abilities scale by Rasch model item analysis. A secondary objective was to examine the relationship between the Early Functional Abilities scale and the Functional Independence Measurement™, in order to establish the criterion validity of the Early Functional Abilities scale and to compare the sensitivity of measurements using the 2 instruments. The Rasch analysis was based on the assessment of 408 adult patients at admission to sub-acute rehabilitation in Copenhagen, Denmark after traumatic brain injury. The Early Functional Abilities scale provides valid and objective measurement of vegetative (autonomic), facio-oral, sensorimotor and communicative/cognitive functions. Removal of one item from the sensorimotor scale confirmed unidimensionality for each of the 4 subscales, but not for the entire scale. The Early Functional Abilities subscales are sensitive to differences between patients in ranges in which the Functional Independence Measurement™ has a floor effect. The Early Functional Abilities scale assesses the early recovery of important aspects of brain function after traumatic brain injury, but is not unidimensional. We recommend removal of the "standing" item and calculation of summary subscales for the separate dimensions.

Size-weight illusion and anticipatory grip force scaling following unilateral cortical brain lesion.

PubMed

Li, Yong; Randerath, Jennifer; Goldenberg, Georg; Hermsdörfer, Joachim

2011-04-01

The prediction of object weight from its size is an important prerequisite of skillful object manipulation. Grip and load forces anticipate object size during early phases of lifting an object. A mismatch between predicted and actual weight when two different sized objects have the same weight results in the size-weight illusion (SWI), the small object feeling heavier. This study explores whether lateralized brain lesions in patients with or without apraxia alter the size-weight illusion and impair anticipatory finger force scaling. Twenty patients with left brain damage (LBD, 10 with apraxia, 10 without apraxia), ten patients with right brain damage (RBD), and matched control subjects lifted two different-sized boxes in alternation. All subjects experienced a similar size-weight illusion. The anticipatory force scaling of all groups was in correspondence with the size cue: higher forces and force rates were applied to the big box and lower forces and force rates to the small box during the first lifts. Within few lifts, forces were scaled to actual object weight. Despite the lack of significant differences at group level, 5 out of 20 LBD patients showed abnormal predictive scaling of grip forces. They differed from the LBD patients with normal predictive scaling by a greater incidence of posterior occipito-parietal lesions but not by a greater incidence of apraxia. The findings do not support a more general role for the motor-dominant left hemisphere, or an influence of apraxia per se, in the scaling of finger force according to object properties. However, damage in the vicinity of the parietal-occipital junction may be critical for deriving predictions of weight from size. Copyright © 2011 Elsevier Ltd. All rights reserved.

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

PubMed

Merolla, Paul A; Arthur, John V; Alvarez-Icaza, Rodrigo; Cassidy, Andrew S; Sawada, Jun; Akopyan, Filipp; Jackson, Bryan L; Imam, Nabil; Guo, Chen; Nakamura, Yutaka; Brezzo, Bernard; Vo, Ivan; Esser, Steven K; Appuswamy, Rathinakumar; Taba, Brian; Amir, Arnon; Flickner, Myron D; Risk, William P; Manohar, Rajit; Modha, Dharmendra S

2014-08-08

Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses. Chips can be tiled in two dimensions via an interchip communication interface, seamlessly scaling the architecture to a cortexlike sheet of arbitrary size. The architecture is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification. With 400-pixel-by-240-pixel video input at 30 frames per second, the chip consumes 63 milliwatts. Copyright © 2014, American Association for the Advancement of Science.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

PubMed

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

2015-01-01

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

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

PubMed

Kivunja, Stephen; River, Jo; Gullick, Janice

2018-04-01

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

Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

Min, Eunjung; Kandel, Mikhail E.; Ko, Chemyong J.; Popescu, Gabriel; Jung, Woonggyu; Best-Popescu, Catherine

2016-12-01

Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy.

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation

PubMed Central

Griffis, Joseph C.; Elkhetali, Abdurahman S.; Burge, Wesley K.; Chen, Richard H.; Bowman, Anthony D.; Szaflarski, Jerzy P.; Visscher, Kristina M.

2016-01-01

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation. Importantly, our analyses reveal that eccentricity sectors in V1 have different functional connectivity with non-visual areas associated with large-scale brain networks. Regions associated with the fronto-parietal control network are most strongly connected with central sectors of V1, regions associated with the cingulo-opercular control network are most strongly connected with near-peripheral sectors of V1, and regions associated with the default mode and auditory networks are most strongly connected with far-peripheral sectors of V1. Additional analyses suggest that similar patterns are present during eyes-closed rest. These results suggest that different types of visual information may be prioritized by large-scale brain networks with distinct functional profiles, and provide insights into how the small-scale functional specialization within early visual regions such as V1 relates to the large-scale organization of functionally distinct whole-brain networks. PMID:27554527

Inter-subject FDG PET Brain Networks Exhibit Multi-scale Community Structure with Different Normalization Techniques.

PubMed

Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A

2018-07-01

Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p < 0.00001); however, community structure is similar at network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-04-01

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

The Organic Brain Syndrome (OBS) scale: a systematic review.

PubMed

Björkelund, Karin Björkman; Larsson, Sylvia; Gustafson, Lars; Andersson, Edith

2006-03-01

The Organic Brain Syndrome (OBS) Scale was developed to determine elderly patients' disturbances of awareness and orientation as to time, place and own identity, and assessment of various emotional and behavioural symptoms appearing in delirium, dementia and other organic mental diseases. The aim of the study was to examine the OBS Scale, using the eight criteria and guidelines formulated by the Scientific Advisory Committee of the Medical Outcomes Trust (SAC), and to investigate its relevance and suitability for use in various clinical settings. Systematic search and analysis of papers (30) on the OBS Scale were carried out using the criteria suggested by the SAC. The OBS Scale in many aspects satisfies the requirements suggested by the SAC: conceptual and measurement model, reliability, validity, responsiveness, interpretability, respondent and administrative burden, alternative forms of administration, and cultural and language adaptations, but there is a need for additional evaluation, especially with regard to different forms of reliability, and the translation and adaptation to other languages. The OBS Scale is a sensitive scale which is clinically useful for the description and long-term follow-up of patients showing symptoms of acute confusional state and dementia. Although the OBS Scale has been used in several clinical studies there is need for further evaluation.

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities

PubMed Central

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities.

PubMed

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks

Higher levels of trait emotional awareness are associated with more efficient global information integration throughout the brain: A graph-theoretic analysis of resting state functional connectivity.

PubMed

Smith, Ryan; Sanova, Anna; Alkozei, Anna; Lane, Richard D; Killgore, William D S

2018-06-21

Previous studies have suggested that trait differences in emotional awareness (tEA) are clinically relevant, and associated with differences in neural structure/function. While multiple leading theories suggest that conscious awareness requires widespread information integration across the brain, no study has yet tested the hypothesis that higher tEA corresponds to more efficient brain-wide information exchange. Twenty-six healthy volunteers (13 female) underwent a resting state functional magnetic resonance imaging scan, and completed the Levels of Emotional Awareness Scale (LEAS; a measure of tEA) and the Wechsler Abbreviated Scale of Intelligence (WASI-II; a measure of general intelligence [IQ]). Using a whole-brain (functionally defined) region-of-interest (ROI) atlas, we computed several graph theory metrics to assess the efficiency of brain-wide information exchange. After statistically controlling for differences in age, gender, and IQ, we first observed a significant relationship between higher LEAS scores and greater average degree (i.e., overall whole-brain network density). When controlling for average degree, we found that higher LEAS scores were also associated with shorter average path lengths across the collective network of all included ROIs. These results jointly suggest that individuals with higher tEA display more efficient global information exchange throughout the brain. This is consistent with the idea that conscious awareness requires global accessibility of represented information.

A Network Model of the Emotional Brain.

PubMed

Pessoa, Luiz

2017-05-01

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

Endothelial β-Catenin Signaling Is Required for Maintaining Adult Blood-Brain Barrier Integrity and CNS Homeostasis

PubMed Central

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

2015-01-01

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

Genetically increased cell-intrinsic excitability enhances neuronal integration into adult brain circuits

PubMed Central

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

2009-01-01

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

Large-Scale Brain Network Coupling Predicts Total Sleep Deprivation Effects on Cognitive Capacity

PubMed Central

Wang, Lubin; Zhai, Tianye; Zou, Feng; Ye, Enmao; Jin, Xiao; Li, Wuju; Qi, Jianlin; Yang, Zheng

2015-01-01

Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI). Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM) task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN) and default mode network (DMN). Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation. PMID:26218521

An Animal-to-Human Scaling Law for Blast-Induced Traumatic Brain Injury Risk Assessment

DTIC Science & Technology

2014-10-28

TERMS b. ABSTRACT 2. REPORT TYPE 17. LIMITATION OF ABSTRACT 15. NUMBER OF PAGES 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 5c...brain, as well as their acoustic impedance. Peak stresses transmitted to the brain tissue by the blast are then shown to be a power function of the...be a power function of the scaling parameter for a range of blast conditions relevant to TBI. In particu- lar, it is found that human brain

[Development of a scale to measure Korean ego-integrity in older adults].

PubMed

Chang, Sung Ok; Kong, Eun Sook; Kim, Kwuy Bun; Kim, Nam Cho; Kim, Ju Hee; Kim, Chun Gill; Kim, Hee Kyung; Song, Mi Soon; Ahn, Soo Yeon; Lee, Kyung Ja; Lee, Young Whee; Chon, Si Ja; Cho, Nam Ok; Cho, Myung Ok; Choi, Kyung Sook

2007-04-01

Ego-integrity in older adults is the central concept related to quality of life in later life. Therefore, for effective interventions to enhance the quality of later life, a scale to measure ego-integrity in older adults is necessary. This study was carried out to develop a scale to measure ego-integrity in older adults. This study utilized cronbach's alpha in analyzing the reliability of the collected data and expert group, and factor analysis and item analysis to analyze validity. Seventeen items were selected from a total of 21 items. Cronbach's alpha coefficient for internal consistency was .88 for the 17 items of ego-integrity in the older adults scale. Three factors evolved by factor analysis, which explained 50.71% of the total variance. The scale for measuring ego-integrity in Korean older adults in this study was evaluated as a tool with a high degree of reliability and validity.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

Tracking the development of brain connectivity in adolescence through a fast Bayesian integrative method

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Boltzmann brains and the scale-factor cutoff measure of the multiverse

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

De Simone, Andrea; Guth, Alan H.; Linde, Andrei

2010-09-15

To make predictions for an eternally inflating 'multiverse', one must adopt a procedure for regulating its divergent spacetime volume. Recently, a new test of such spacetime measures has emerged: normal observers - who evolve in pocket universes cooling from hot big bang conditions - must not be vastly outnumbered by 'Boltzmann brains' - freak observers that pop in and out of existence as a result of rare quantum fluctuations. If the Boltzmann brains prevail, then a randomly chosen observer would be overwhelmingly likely to be surrounded by an empty world, where all but vacuum energy has redshifted away, rather thanmore » the rich structure that we observe. Using the scale-factor cutoff measure, we calculate the ratio of Boltzmann brains to normal observers. We find the ratio to be finite, and give an expression for it in terms of Boltzmann brain nucleation rates and vacuum decay rates. We discuss the conditions that these rates must obey for the ratio to be acceptable, and we discuss estimates of the rates under a variety of assumptions.« less

Episodic memory in aspects of large-scale brain networks

PubMed Central

Jeong, Woorim; Chung, Chun Kee; Kim, June Sic

2015-01-01

Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL) structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network (DMN). Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network (RSN). Altered patterns of functional connectivity (FC) among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment. PMID:26321939

Chronic, Wireless Recordings of Large Scale Brain Activity in Freely Moving Rhesus Monkeys

PubMed Central

Schwarz, David A.; Lebedev, Mikhail A.; Hanson, Timothy L.; Dimitrov, Dragan F.; Lehew, Gary; Meloy, Jim; Rajangam, Sankaranarayani; Subramanian, Vivek; Ifft, Peter J.; Li, Zheng; Ramakrishnan, Arjun; Tate, Andrew; Zhuang, Katie; Nicolelis, Miguel A.L.

2014-01-01

Advances in techniques for recording large-scale brain activity contribute to both the elucidation of neurophysiological principles and the development of brain-machine interfaces (BMIs). Here we describe a neurophysiological paradigm for performing tethered and wireless large-scale recordings based on movable volumetric three-dimensional (3D) multielectrode implants. This approach allowed us to isolate up to 1,800 units per animal and simultaneously record the extracellular activity of close to 500 cortical neurons, distributed across multiple cortical areas, in freely behaving rhesus monkeys. The method is expandable, in principle, to thousands of simultaneously recorded channels. It also allows increased recording longevity (5 consecutive years), and recording of a broad range of behaviors, e.g. social interactions, and BMI paradigms in freely moving primates. We propose that wireless large-scale recordings could have a profound impact on basic primate neurophysiology research, while providing a framework for the development and testing of clinically relevant neuroprostheses. PMID:24776634

Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain.

PubMed

Kuipers, Jeroen; Kalicharan, Ruby D; Wolters, Anouk H G; van Ham, Tjakko J; Giepmans, Ben N G

2016-05-25

Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae(1-7). Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically ~ 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture(1-5). Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)(8) on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner.

Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain

PubMed Central

Kuipers, Jeroen; Kalicharan, Ruby D.; Wolters, Anouk H. G.

2016-01-01

Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae1-7. Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically ~ 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture1-5. Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)8 on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner. PMID:27285162

Realistic modeling of neurons and networks: towards brain simulation.

PubMed

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

2013-01-01

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

Realistic modeling of neurons and networks: towards brain simulation

PubMed Central

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

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

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Resource integration and shared outcomes at the watershed scale

Treesearch

Eleanor S. Towns

2000-01-01

Shared resources are universal resources that are vital for sustaining communities, enhancing our quality of life and preserving ecosystem health. We have a shared responsibility to conserve shared resources and preserve their integrity for future generations. Resource integration is accomplished through ecosystem management, often at a watershed scale. The shared...

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

PubMed

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

2013-01-01

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

The Virtual Brain: a simulator of primate brain network dynamics

PubMed Central

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

2013-01-01

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

Dependence of normal brain integral dose and normal tissue complication probability on the prescription isodose values for γ-knife radiosurgery

NASA Astrophysics Data System (ADS)

Ma, Lijun

2001-11-01

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

Heterogeneous integration of adult-generated granule cells into the epileptic brain

PubMed Central

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

2011-01-01

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

Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

PubMed Central

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

2013-01-01

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

Brain/MINDS: brain-mapping project in Japan

PubMed Central

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-01-01

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

Meditation is associated with increased brain network integration.

PubMed

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

2017-09-01

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

Pain assessment scales in newborns: integrative review

PubMed Central

de Melo, Gleicia Martins; Lélis, Ana Luíza Paula de Aguiar; de Moura, Alline Falconieri; Cardoso, Maria Vera Lúcia Moreira Leitão; da Silva, Viviane Martins

2014-01-01

OBJECTIVE: To analyze studies on methods used to assess pain in newborns. DATA SOURCES: Integrative review study of articles published from 2001 to 2012, carried out in the following databases: Scopus, PubMed, CINAHL, LILACS and Cochrane. The sample consisted of 13 articles with level of evidence 5. DATA SYNTHESIS: 29 pain assessment scales in newborns, including 13 one-dimensional and 16 multidimensional, that assess acute and prolonged pain in preterm and full-term infants were available in scientific publications. CONCLUSION: Based on the characteristics of scales, one cannot choose a single one as the most appropriate scale, as this choice will depend on gestational age, type of painful stimulus and the environment in which the infant is inserted. It is suggested the use of multidimensional or one-dimensional scales; however, they must be reliable and validated. PMID:25511005

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

PubMed

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

2018-06-01

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

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

PubMed

Schaefer, Jennifer E

2016-01-01

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

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

PubMed

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

2018-04-01

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

Stepwise Connectivity of the Modal Cortex Reveals the Multimodal Organization of the Human Brain

PubMed Central

Sepulcre, Jorge; Sabuncu, Mert R.; Yeo, Thomas B.; Liu, Hesheng; Johnson, Keith A.

2012-01-01

How human beings integrate information from external sources and internal cognition to produce a coherent experience is still not well understood. During the past decades, anatomical, neurophysiological and neuroimaging research in multimodal integration have stood out in the effort to understand the perceptual binding properties of the brain. Areas in the human lateral occipito-temporal, prefrontal and posterior parietal cortices have been associated with sensory multimodal processing. Even though this, rather patchy, organization of brain regions gives us a glimpse of the perceptual convergence, the articulation of the flow of information from modality-related to the more parallel cognitive processing systems remains elusive. Using a method called Stepwise Functional Connectivity analysis, the present study analyzes the functional connectome and transitions from primary sensory cortices to higher-order brain systems. We identify the large-scale multimodal integration network and essential connectivity axes for perceptual integration in the human brain. PMID:22855814

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

PubMed

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

2018-05-22

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

Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis.

PubMed

Frasch, Martin G; Lobmaier, Silvia M; Stampalija, Tamara; Desplats, Paula; Pallarés, María Eugenia; Pastor, Verónica; Brocco, Marcela A; Wu, Hau-Tieng; Schulkin, Jay; Herry, Christophe L; Seely, Andrew J E; Metz, Gerlinde A S; Louzoun, Yoram; Antonelli, Marta C

2018-05-30

Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of PS. The multiple scales include brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS as well as follow-up indicators of success of therapeutic interventions to correct such altered neurodevelopmental trajectories. PS studies must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive detection and follow-up biomarkers, a prerequisite for designing effective therapeutic interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings

PubMed Central

Lu, Jing; Wu, Dan; Yang, Hua; Luo, Cheng; Li, Chaoyi; Yao, Dezhong

2012-01-01

In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain. PMID:23166768

Differences between brain mass and body weight scaling to height: potential mechanism of reduced mass-specific resting energy expenditure of taller adults.

PubMed

Heymsfield, Steven B; Chirachariyavej, Thamrong; Rhyu, Im Joo; Roongpisuthipong, Chulaporn; Heo, Moonseong; Pietrobelli, Angelo

2009-01-01

Adult resting energy expenditure (REE) scales as height( approximately 1.5), whereas body weight (BW) scales as height( approximately 2). Mass-specific REE (i.e., REE/BW) is thus lower in tall subjects compared with their shorter counterparts, the mechanism of which is unknown. We evaluated the hypothesis that high-metabolic-rate brain mass scales to height with a power significantly less than that of BW, a theory that if valid would provide a potential mechanism for height-related REE effects. The hypothesis was tested by measuring brain mass on a large (n = 372) postmortem sample of Thai men. Since brain mass-body size relations may be influenced by age, the hypothesis was secondarily explored in Thai men age < or =45 yr (n = 299) and with brain magnetic resonance imaging (MRI) studies in Korean men (n = 30) age > or =20<30 yr. The scaling of large body compartments was examined in a third group of Asian men living in New York (NY, n = 28) with MRI and dual-energy X-ray absorptiometry. Brain mass scaled to height with a power (mean +/- SEE; 0.46 +/- 0.13) significantly smaller (P < 0.001) than that of BW scaled to height (2.36 +/- 0.19) in the whole group of Thai men; brain mass/BW scaled negatively to height (-1.94 +/- 0.20, P < 0.001). Similar results were observed in younger Thai men, and results for brain mass/BW vs. height were directionally the same (P = 0.09) in Korean men. Skeletal muscle and bone scaled to height with powers similar to that of BW (i.e., approximately 2-3) in the NY Asian men. Models developed using REE estimates in Thai men suggest that brain accounts for most of the REE/BW height dependency. Tall and short men thus differ in relative brain mass, but the proportions of BW as large compartments appear independent of height, observations that provide a potential mechanistic basis for related differences in REE and that have implications for the study of adult energy requirements.

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

PubMed

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

2015-01-15

Peripheral circulating cytokines are involved in immune to brain communication and systemic inflammation is considered a risk factor for flaring up the symptoms in most neurodegenerative diseases. We induced both central inflammatory demyelinating lesion, and systemic inflammation with an interleukin-1β expressing adenovector. The peripheral pro-inflammatory stimulus aggravated the ongoing central lesion independently of the blood-brain barrier (BBB) integrity. This model allows studying the role of specific molecules and cells (neutrophils) from the innate immune system, in the relationship between central and peripheral communication, and on relapsing episodes of demyelinating lesions, along with the role of BBB integrity. Copyright © 2014 Elsevier B.V. All rights reserved.

Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

NASA Astrophysics Data System (ADS)

Stoop, Ralph; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi

2013-03-01

We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic—intercolumnar—scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.

Modeling brain circuitry over a wide range of scales.

PubMed

Fua, Pascal; Knott, Graham W

2015-01-01

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

Modeling brain circuitry over a wide range of scales

PubMed Central

Fua, Pascal; Knott, Graham W.

2015-01-01

If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM) can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes (LM) see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the topology and the connection strength are integral parts of the brain's wiring diagram, being able to combine these two modalities is critically important. In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. In this paper, we briefly review the Computer Vision techniques we have developed at EPFL to address this need. They include delineating dendritic arbors from LM imagery, segmenting organelles from EM, and combining the two into a consistent representation. PMID:25904852

What is community integration anyway?: defining meaning following traumatic brain injury.

PubMed

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

2010-01-01

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

Refining a measure of brain injury sequelae to predict postacute rehabilitation outcome: rating scale analysis of the Mayo-Portland Adaptability Inventory.

PubMed

Malec, J F; Moessner, A M; Kragness, M; Lezak, M D

2000-02-01

Evaluate the psychometric properties of the Mayo-Portland Adaptability Inventory (MPAI). Rating scale (Rasch) analysis of MPAI and principal component analysis of residuals; the predictive validity of the MPAI measures and raw scores was assessed in a sample from a day rehabilitation program. Outpatient brain injury rehabilitation. 305 persons with brain injury. A 22-item scale reflecting severity of sequelae of brain injury that contained a mix of indicators of impairment, activity, and participation was identified. Scores and measures for MPAI scales were strongly correlated and their predictive validities were comparable. Impairment, activity, and participation define a single dimension of brain injury sequelae. The MPAI shows promise as a measure of this construct.

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

DTIC Science & Technology

2005-02-01

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

Reliability of the Client-Centeredness of Goal Setting (C-COGS) Scale in Acquired Brain Injury Rehabilitation.

PubMed

Doig, Emmah; Prescott, Sarah; Fleming, Jennifer; Cornwell, Petrea; Kuipers, Pim

2016-01-01

To examine the internal reliability and test-retest reliability of the Client-Centeredness of Goal Setting (C-COGS) scale. The C-COGS scale was administered to 42 participants with acquired brain injury after completion of multidisciplinary goal planning. Internal reliability of scale items was examined using item-partial total correlations and Cronbach's α coefficient. The scale was readministered within a 1-mo period to a subsample of 12 participants to examine test-retest reliability by calculating exact and close percentage agreement for each item. After examination of item-partial total correlations, test items were revised. The revised items demonstrated stronger internal consistency than the original items. Preliminary evaluation of test-retest reliability was fair, with an average exact percent agreement across all test items of 67%. Findings support the preliminary reliability of the C-COGS scale as a tool to evaluate and promote client-centered goal planning in brain injury rehabilitation. Copyright © 2016 by the American Occupational Therapy Association, Inc.

Silicon Hybrid Wafer Scale Integration Interconnect Evaluation

DTIC Science & Technology

1989-12-01

perform Wafer Scale Integration on a routine basis is being vigorously pursued by a number of interests in military, academic , and commercial sectors...A iliciosi rip1 St -110 illic. (;11ptai / W. -a ;,tcd Ihat Ilesc hybhrid futl liods separiltely soI lie llixiiiul’upw~v~ ielts andl ~il (otii’ie thli

Multiscale modeling and simulation of brain blood flow

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

PubMed

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

2017-04-01

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

Cellular scaling rules for the brain of Artiodactyla include a highly folded cortex with few neurons

PubMed Central

Kazu, Rodrigo S.; Maldonado, José; Mota, Bruno; Manger, Paul R.; Herculano-Houzel, Suzana

2014-01-01

Quantitative analysis of the cellular composition of rodent, primate, insectivore, and afrotherian brains has shown that non-neuronal scaling rules are similar across these mammalian orders that diverged about 95 million years ago, and therefore appear to be conserved in evolution, while neuronal scaling rules appear to be free to vary in a clade-specific manner. Here we analyze the cellular scaling rules that apply to the brain of artiodactyls, a group within the order Cetartiodactyla, believed to be a relatively recent radiation from the common Eutherian ancestor. We find that artiodactyls share non-neuronal scaling rules with all groups analyzed previously. Artiodactyls share with afrotherians and rodents, but not with primates, the neuronal scaling rules that apply to the cerebral cortex and cerebellum. The neuronal scaling rules that apply to the remaining brain areas are, however, distinct in artiodactyls. Importantly, we show that the folding index of the cerebral cortex scales with the number of neurons in the cerebral cortex in distinct fashions across artiodactyls, afrotherians, rodents, and primates, such that the artiodactyl cerebral cortex is more convoluted than primate cortices of similar numbers of neurons. Our findings suggest that the scaling rules found to be shared across modern afrotherians, glires, and artiodactyls applied to the common Eutherian ancestor, such as the relationship between the mass of the cerebral cortex as a whole and its number of neurons. In turn, the distribution of neurons along the surface of the cerebral cortex, which is related to its degree of gyrification, appears to be a clade-specific characteristic. If the neuronal scaling rules for artiodactyls extend to all cetartiodactyls, we predict that the large cerebral cortex of cetaceans will still have fewer neurons than the human cerebral cortex. PMID:25429261

Integrated But Not Whole? Applying an Ontological Account of Human Organismal Unity to the Brain Death Debate.

PubMed

Moschella, Melissa

2016-10-01

As is clear in the 2008 report of the President's Council on Bioethics, the brain death debate is plagued by ambiguity in the use of such key terms as 'integration' and 'wholeness'. Addressing this problem, I offer a plausible ontological account of organismal unity drawing on the work of Hoffman and Rosenkrantz, and then apply that account to the case of brain death, concluding that a brain dead body lacks the unity proper to a human organism, and has therefore undergone a substantial change. I also show how my view can explain hard cases better than one in which biological integration (as understood by Alan Shewmon and the President's Council) is taken to imply ontological wholeness or unity. © 2016 John Wiley & Sons Ltd.

Cerebral energy metabolism and the brain's functional network architecture: an integrative review.

PubMed

Lord, Louis-David; Expert, Paul; Huckins, Jeremy F; Turkheimer, Federico E

2013-09-01

Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.

Scale invariant rearrangement of resting state networks in the human brain under sustained stimulation.

PubMed

Tommasin, Silvia; Mascali, Daniele; Moraschi, Marta; Gili, Tommaso; Assan, Ibrahim Eid; Fratini, Michela; DiNuzzo, Mauro; Wise, Richard G; Mangia, Silvia; Macaluso, Emiliano; Giove, Federico

2018-06-14

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may be not the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation. Copyright © 2018. Published by Elsevier Inc.

Controllability of structural brain networks

NASA Astrophysics Data System (ADS)

Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K.; Yu, Alfred B.; Kahn, Ari E.; Medaglia, John D.; Vettel, Jean M.; Miller, Michael B.; Grafton, Scott T.; Bassett, Danielle S.

2015-10-01

Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.

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

ERIC Educational Resources Information Center

Palasigue, Jesame Torres

2009-01-01

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

Fractionaly Integrated Flux model and Scaling Laws in Weather and Climate

NASA Astrophysics Data System (ADS)

Schertzer, Daniel; Lovejoy, Shaun

2013-04-01

The Fractionaly Integrated Flux model (FIF) has been extensively used to model intermittent observables, like the velocity field, by defining them with the help of a fractional integration of a conservative (i.e. strictly scale invariant) flux, such as the turbulent energy flux. It indeed corresponds to a well-defined modelling that yields the observed scaling laws. Generalised Scale Invariance (GSI) enables FIF to deal with anisotropic fractional integrations and has been rather successful to define and model a unique regime of scaling anisotropic turbulence up to planetary scales. This turbulence has an effective dimension of 23/9=2.55... instead of the classical hypothesised 2D and 3D turbulent regimes, respectively for large and small spatial scales. It therefore theoretically eliminates a non plausible "dimension transition" between these two regimes and the resulting requirement of a turbulent energy "mesoscale gap", whose empirical evidence has been brought more and more into question. More recently, GSI-FIF was used to analyse climate, therefore at much larger time scales. Indeed, the 23/9-dimensional regime necessarily breaks up at the outer spatial scales. The corresponding transition range, which can be called "macroweather", seems to have many interesting properties, e.g. it rather corresponds to a fractional differentiation in time with a roughly flat frequency spectrum. Furthermore, this transition yields the possibility to have at much larger time scales scaling space-time climate fluctuations with a much stronger scaling anisotropy between time and space. Lovejoy, S. and D. Schertzer (2013). The Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge Press (in press). Schertzer, D. et al. (1997). Fractals 5(3): 427-471. Schertzer, D. and S. Lovejoy (2011). International Journal of Bifurcation and Chaos 21(12): 3417-3456.

Decomposing Gratitude: Representation and Integration of Cognitive Antecedents of Gratitude in the Brain.

PubMed

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

2018-05-23

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

Preservation of mitochondrial functional integrity in mitochondria isolated from small cryopreserved mouse brain areas.

PubMed

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

2014-01-01

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

Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation.

PubMed

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

2018-06-01

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

Early brain development toward shaping of human mind: an integrative psychoneurodevelopmental model in prenatal and perinatal medicine.

PubMed

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

2013-01-01

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

Traits Without Borders: Integrating Functional Diversity Across Scales.

PubMed

Carmona, Carlos P; de Bello, Francesco; Mason, Norman W H; Lepš, Jan

2016-05-01

Owing to the conceptual complexity of functional diversity (FD), a multitude of different methods are available for measuring it, with most being operational at only a small range of spatial scales. This causes uncertainty in ecological interpretations and limits the potential to generalize findings across studies or compare patterns across scales. We solve this problem by providing a unified framework expanding on and integrating existing approaches. The framework, based on trait probability density (TPD), is the first to fully implement the Hutchinsonian concept of the niche as a probabilistic hypervolume in estimating FD. This novel approach could revolutionize FD-based research by allowing quantification of the various FD components from organismal to macroecological scales, and allowing seamless transitions between scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

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

2016-11-03

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

Dapsone protects brain microvascular integrity from high-fat diet induced LDL oxidation.

PubMed

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

2018-06-07

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

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

PubMed

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

2016-01-12

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

Network integrity of the parental brain in infancy supports the development of children's social competencies.

PubMed

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

2016-11-01

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

The Autism Brain Imaging Data Exchange: Towards Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism

PubMed Central

Di Martino, Adriana; Yan, Chao-Gan; Li, Qingyang; Denio, Erin; Castellanos, Francisco X.; Alaerts, Kaat; Anderson, Jeffrey S.; Assaf, Michal; Bookheimer, Susan Y.; Dapretto, Mirella; Deen, Ben; Delmonte, Sonja; Dinstein, Ilan; Ertl-Wagner, Birgit; Fair, Damien A.; Gallagher, Louise; Kennedy, Daniel P.; Keown, Christopher L.; Keysers, Christian; Lainhart, Janet E.; Lord, Catherine; Luna, Beatriz; Menon, Vinod; Minshew, Nancy; Monk, Christopher S.; Mueller, Sophia; Müller, Ralph-Axel; Nebel, Mary Beth; Nigg, Joel T.; O’Hearn, Kirsten; Pelphrey, Kevin A.; Peltier, Scott J.; Rudie, Jeffrey D.; Sunaert, Stefan; Thioux, Marc; Tyszka, J. Michael; Uddin, Lucina Q.; Verhoeven, Judith S.; Wenderoth, Nicole; Wiggins, Jillian L.; Mostofsky, Stewart H.; Milham, Michael P.

2014-01-01

Autism spectrum disorders (ASD) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, life-long nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. While the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE) – a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) datasets with corresponding structural MRI and phenotypic information from 539 individuals with ASD and 573 age-matched typical controls (TC; 7–64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 males with ASD and 403 male age-matched TC. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo and hyperconnectivity in the ASD literature; both were detected, though hypoconnectivity dominated, particularly for cortico-cortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASD (mid and posterior insula, posterior cingulate cortex), and highlighted less commonly explored regions such as thalamus. The survey of the ABIDE R-fMRI datasets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international datasets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies. PMID:23774715

Neurodevelopmental alterations of large-scale structural networks in children with new-onset epilepsy

PubMed Central

Bonilha, Leonardo; Tabesh, Ali; Dabbs, Kevin; Hsu, David A.; Stafstrom, Carl E.; Hermann, Bruce P.; Lin, Jack J.

2014-01-01

Recent neuroimaging and behavioral studies have revealed that children with new onset epilepsy already exhibit brain structural abnormalities and cognitive impairment. How the organization of large-scale brain structural networks is altered near the time of seizure onset and whether network changes are related to cognitive performances remain unclear. Recent studies also suggest that regional brain volume covariance reflects synchronized brain developmental changes. Here, we test the hypothesis that epilepsy during early-life is associated with abnormalities in brain network organization and cognition. We used graph theory to study structural brain networks based on regional volume covariance in 39 children with new-onset seizures and 28 healthy controls. Children with new-onset epilepsy showed a suboptimal topological structural organization with enhanced network segregation and reduced global integration compared to controls. At the regional level, structural reorganization was evident with redistributed nodes from the posterior to more anterior head regions. The epileptic brain network was more vulnerable to targeted but not random attacks. Finally, a subgroup of children with epilepsy, namely those with lower IQ and poorer executive function, had a reduced balance between network segregation and integration. Taken together, the findings suggest that the neurodevelopmental impact of new onset childhood epilepsies alters large-scale brain networks, resulting in greater vulnerability to network failure and cognitive impairment. PMID:24453089

Neurodevelopmental alterations of large-scale structural networks in children with new-onset epilepsy.

PubMed

Bonilha, Leonardo; Tabesh, Ali; Dabbs, Kevin; Hsu, David A; Stafstrom, Carl E; Hermann, Bruce P; Lin, Jack J

2014-08-01

Recent neuroimaging and behavioral studies have revealed that children with new onset epilepsy already exhibit brain structural abnormalities and cognitive impairment. How the organization of large-scale brain structural networks is altered near the time of seizure onset and whether network changes are related to cognitive performances remain unclear. Recent studies also suggest that regional brain volume covariance reflects synchronized brain developmental changes. Here, we test the hypothesis that epilepsy during early-life is associated with abnormalities in brain network organization and cognition. We used graph theory to study structural brain networks based on regional volume covariance in 39 children with new-onset seizures and 28 healthy controls. Children with new-onset epilepsy showed a suboptimal topological structural organization with enhanced network segregation and reduced global integration compared with controls. At the regional level, structural reorganization was evident with redistributed nodes from the posterior to more anterior head regions. The epileptic brain network was more vulnerable to targeted but not random attacks. Finally, a subgroup of children with epilepsy, namely those with lower IQ and poorer executive function, had a reduced balance between network segregation and integration. Taken together, the findings suggest that the neurodevelopmental impact of new onset childhood epilepsies alters large-scale brain networks, resulting in greater vulnerability to network failure and cognitive impairment. Copyright © 2014 Wiley Periodicals, Inc.

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

PubMed

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

2016-01-01

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

Timing of Formal Phase Safety Reviews for Large-Scale Integrated Hazard Analysis

NASA Technical Reports Server (NTRS)

Massie, Michael J.; Morris, A. Terry

2010-01-01

Integrated hazard analysis (IHA) is a process used to identify and control unacceptable risk. As such, it does not occur in a vacuum. IHA approaches must be tailored to fit the system being analyzed. Physical, resource, organizational and temporal constraints on large-scale integrated systems impose additional direct or derived requirements on the IHA. The timing and interaction between engineering and safety organizations can provide either benefits or hindrances to the overall end product. The traditional approach for formal phase safety review timing and content, which generally works well for small- to moderate-scale systems, does not work well for very large-scale integrated systems. This paper proposes a modified approach to timing and content of formal phase safety reviews for IHA. Details of the tailoring process for IHA will describe how to avoid temporary disconnects in major milestone reviews and how to maintain a cohesive end-to-end integration story particularly for systems where the integrator inherently has little to no insight into lower level systems. The proposal has the advantage of allowing the hazard analysis development process to occur as technical data normally matures.

Reliability of a novel, semi-quantitative scale for classification of structural brain magnetic resonance imaging in children with cerebral palsy.

PubMed

Fiori, Simona; Cioni, Giovanni; Klingels, Katrjin; Ortibus, Els; Van Gestel, Leen; Rose, Stephen; Boyd, Roslyn N; Feys, Hilde; Guzzetta, Andrea

2014-09-01

To describe the development of a novel rating scale for classification of brain structural magnetic resonance imaging (MRI) in children with cerebral palsy (CP) and to assess its interrater and intrarater reliability. The scale consists of three sections. Section 1 contains descriptive information about the patient and MRI. Section 2 contains the graphical template of brain hemispheres onto which the lesion is transposed. Section 3 contains the scoring system for the quantitative analysis of the lesion characteristics, grouped into different global scores and subscores that assess separately side, regions, and depth. A larger interrater and intrarater reliability study was performed in 34 children with CP (22 males, 12 females; mean age at scan of 9 y 5 mo [SD 3 y 3 mo], range 4 y-16 y 11 mo; Gross Motor Function Classification System level I, [n=22], II [n=10], and level III [n=2]). Very high interrater and intrarater reliability of the total score was found with indices above 0.87. Reliability coefficients of the lobar and hemispheric subscores ranged between 0.53 and 0.95. Global scores for hemispheres, basal ganglia, brain stem, and corpus callosum showed reliability coefficients above 0.65. This study presents the first visual, semi-quantitative scale for classification of brain structural MRI in children with CP. The high degree of reliability of the scale supports its potential application for investigating the relationship between brain structure and function and examining treatment response according to brain lesion severity in children with CP. © 2014 Mac Keith Press.

Differences between child and adult large-scale functional brain networks for reading tasks.

PubMed

Liu, Xin; Gao, Yue; Di, Qiqi; Hu, Jiali; Lu, Chunming; Nan, Yun; Booth, James R; Liu, Li

2018-02-01

Reading is an important high-level cognitive function of the human brain, requiring interaction among multiple brain regions. Revealing differences between children's large-scale functional brain networks for reading tasks and those of adults helps us to understand how the functional network changes over reading development. Here we used functional magnetic resonance imaging data of 17 adults (19-28 years old) and 16 children (11-13 years old), and graph theoretical analyses to investigate age-related changes in large-scale functional networks during rhyming and meaning judgment tasks on pairs of visually presented Chinese characters. We found that: (1) adults had stronger inter-regional connectivity and nodal degree in occipital regions, while children had stronger inter-regional connectivity in temporal regions, suggesting that adults rely more on visual orthographic processing whereas children rely more on auditory phonological processing during reading. (2) Only adults showed between-task differences in inter-regional connectivity and nodal degree, whereas children showed no task differences, suggesting the topological organization of adults' reading network is more specialized. (3) Children showed greater inter-regional connectivity and nodal degree than adults in multiple subcortical regions; the hubs in children were more distributed in subcortical regions while the hubs in adults were more distributed in cortical regions. These findings suggest that reading development is manifested by a shift from reliance on subcortical to cortical regions. Taken together, our study suggests that Chinese reading development is supported by developmental changes in brain connectivity properties, and some of these changes may be domain-general while others may be specific to the reading domain. © 2017 Wiley Periodicals, Inc.

Cross-scale phenological data integration to benefit resource management and monitoring

USGS Publications Warehouse

Richardson, Andrew D.; Weltzin, Jake F.; Morisette, Jeffrey T.

2017-01-01

Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions.A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.

Disruption of White Matter Integrity in Adult Survivors of Childhood Brain Tumors: Correlates with Long-Term Intellectual Outcomes.

PubMed

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

2015-01-01

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

Prenatal Exposure of Guinea Pigs to the Organophosphorus Pesticide Chlorpyrifos Disrupts the Structural and Functional Integrity of the Brain

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2017-10-23

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

A hierarchy of time-scales and the brain.

PubMed

Kiebel, Stefan J; Daunizeau, Jean; Friston, Karl J

2008-11-01

In this paper, we suggest that cortical anatomy recapitulates the temporal hierarchy that is inherent in the dynamics of environmental states. Many aspects of brain function can be understood in terms of a hierarchy of temporal scales at which representations of the environment evolve. The lowest level of this hierarchy corresponds to fast fluctuations associated with sensory processing, whereas the highest levels encode slow contextual changes in the environment, under which faster representations unfold. First, we describe a mathematical model that exploits the temporal structure of fast sensory input to track the slower trajectories of their underlying causes. This model of sensory encoding or perceptual inference establishes a proof of concept that slowly changing neuronal states can encode the paths or trajectories of faster sensory states. We then review empirical evidence that suggests that a temporal hierarchy is recapitulated in the macroscopic organization of the cortex. This anatomic-temporal hierarchy provides a comprehensive framework for understanding cortical function: the specific time-scale that engages a cortical area can be inferred by its location along a rostro-caudal gradient, which reflects the anatomical distance from primary sensory areas. This is most evident in the prefrontal cortex, where complex functions can be explained as operations on representations of the environment that change slowly. The framework provides predictions about, and principled constraints on, cortical structure-function relationships, which can be tested by manipulating the time-scales of sensory input.

Integrated optic head for sensing a two-dimensional displacement of a grating scale

NASA Astrophysics Data System (ADS)

Ura, Shogo; Endoh, Toshiaki; Suhara, Toshiaki; Nishihara, Hiroshi

1996-11-01

An integrated optic sensor head was proposed for sensing a two-dimensional displacement of a scale consisting of crossed gratings. Two interferometers, crossing each other, are constructed by the integration of two pairs of linearly focusing grating couplers (LFGC's) and two pairs of photodiodes (PD's) on a Si substrate. Four beams radiated by the LFGC's from the sensor head overlap on the grating scale, and the beams are diffracted by the grating scale and interfere on the PD's. The period of the interference signal variation is just half of the scale grating period. The device was designed and fabricated with a grating scale of 3.2- mu m period, and the sensing principle was experimentally confirmed.

A new neuroinformatics approach to personalized medicine in neurology: The Virtual Brain

PubMed Central

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

2017-01-01

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

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.

PubMed

Di Martino, A; Yan, C-G; Li, Q; Denio, E; Castellanos, F X; Alaerts, K; Anderson, J S; Assaf, M; Bookheimer, S Y; Dapretto, M; Deen, B; Delmonte, S; Dinstein, I; Ertl-Wagner, B; Fair, D A; Gallagher, L; Kennedy, D P; Keown, C L; Keysers, C; Lainhart, J E; Lord, C; Luna, B; Menon, V; Minshew, N J; Monk, C S; Mueller, S; Müller, R-A; Nebel, M B; Nigg, J T; O'Hearn, K; Pelphrey, K A; Peltier, S J; Rudie, J D; Sunaert, S; Thioux, M; Tyszka, J M; Uddin, L Q; Verhoeven, J S; Wenderoth, N; Wiggins, J L; Mostofsky, S H; Milham, M P

2014-06-01

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

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

2015-01-01

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

Network integrity of the parental brain in infancy supports the development of children’s social competencies

PubMed Central

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

2016-01-01

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

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

PubMed

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

2018-01-01

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

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution

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

PubMed Central

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

2009-01-01

We draw on the theory of allostasis to develop an integrative model of the current stress process that highlights the brain as a dynamically adapting interface between the changing environment and the biological self. We review evidence that the core emotional regions of the brain constitute the primary mediator of the well-established association between stress and health, as well as the neural focus of “wear and tear” due to ongoing adaptation. This mediation, in turn, allows us to model the interplay over time between context, current stressor exposure, internal regulation of bodily processes, and health outcomes. We illustrate how this approach facilitates the integration of current findings in human neuroscience and genetics with key constructs from stress models from the social and life sciences, with implications for future research and the design of interventions targeting individuals at risk. PMID:20063966

Distinct patterns of brain atrophy in Genetic Frontotemporal Dementia Initiative (GENFI) cohort revealed by visual rating scales.

PubMed

Fumagalli, Giorgio G; Basilico, Paola; Arighi, Andrea; Bocchetta, Martina; Dick, Katrina M; Cash, David M; Harding, Sophie; Mercurio, Matteo; Fenoglio, Chiara; Pietroboni, Anna M; Ghezzi, Laura; van Swieten, John; Borroni, Barbara; de Mendonça, Alexandre; Masellis, Mario; Tartaglia, Maria C; Rowe, James B; Graff, Caroline; Tagliavini, Fabrizio; Frisoni, Giovanni B; Laforce, Robert; Finger, Elizabeth; Sorbi, Sandro; Scarpini, Elio; Rohrer, Jonathan D; Galimberti, Daniela

2018-05-24

In patients with frontotemporal dementia, it has been shown that brain atrophy occurs earliest in the anterior cingulate, insula and frontal lobes. We used visual rating scales to investigate whether identifying atrophy in these areas may be helpful in distinguishing symptomatic patients carrying different causal mutations in the microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame (C9ORF72) genes. We also analysed asymptomatic carriers to see whether it was possible to visually identify brain atrophy before the appearance of symptoms. Magnetic resonance imaging of 343 subjects (63 symptomatic mutation carriers, 132 presymptomatic mutation carriers and 148 control subjects) from the Genetic Frontotemporal Dementia Initiative study were analysed by two trained raters using a protocol of six visual rating scales that identified atrophy in key regions of the brain (orbitofrontal, anterior cingulate, frontoinsula, anterior and medial temporal lobes and posterior cortical areas). Intra- and interrater agreement were greater than 0.73 for all the scales. Voxel-based morphometric analysis demonstrated a strong correlation between the visual rating scale scores and grey matter atrophy in the same region for each of the scales. Typical patterns of atrophy were identified: symmetric anterior and medial temporal lobe involvement for MAPT, asymmetric frontal and parietal loss for GRN, and a more widespread pattern for C9ORF72. Presymptomatic MAPT carriers showed greater atrophy in the medial temporal region than control subjects, but the visual rating scales could not identify presymptomatic atrophy in GRN or C9ORF72 carriers. These simple-to-use and reproducible scales may be useful tools in the clinical setting for the discrimination of different mutations of frontotemporal dementia, and they may even help to identify atrophy prior to onset in those with MAPT mutations.

HMC algorithm with multiple time scale integration and mass preconditioning

NASA Astrophysics Data System (ADS)

Urbach, C.; Jansen, K.; Shindler, A.; Wenger, U.

2006-01-01

We present a variant of the HMC algorithm with mass preconditioning (Hasenbusch acceleration) and multiple time scale integration. We have tested this variant for standard Wilson fermions at β=5.6 and at pion masses ranging from 380 to 680 MeV. We show that in this situation its performance is comparable to the recently proposed HMC variant with domain decomposition as preconditioner. We give an update of the "Berlin Wall" figure, comparing the performance of our variant of the HMC algorithm to other published performance data. Advantages of the HMC algorithm with mass preconditioning and multiple time scale integration are that it is straightforward to implement and can be used in combination with a wide variety of lattice Dirac operators.

Depression Anxiety Stress Scales (DASS-21): Factor Structure in Traumatic Brain Injury Rehabilitation.

PubMed

Randall, Diane; Thomas, Matt; Whiting, Diane; McGrath, Andrew

To confirm the construct validity of the Depression Anxiety Stress Scales-21 (DASS-21) by investigating the fit of published factor structures in a sample of adults with moderate to severe traumatic brain injury (posttraumatic amnesia > 24 hours). Archival data from 504 patient records at the Brain Injury Rehabilitation Unit at Liverpool Hospital, Australia. Participants were aged between 16 and 71 years and were engaged in a specialist rehabilitation program. The DASS-21. Two of the 6 models had adequate fit using structural equation modeling. The data best fit Henry and Crawford's quadripartite model, which comprised a Depression, Anxiety and Stress factor, as well as a General Distress factor. The data also adequately fit Lovibond and Lovibond's original 3-factor model, and the internal consistencies of each factor were very good (α = 0.82-0.90). This study confirms the structure and construct validity of the DASS-21 and provides support for its use as a screening tool in traumatic brain injury rehabilitation.

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

PubMed Central

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

2015-01-01

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

Brain scaling in mammalian evolution as a consequence of concerted and mosaic changes in numbers of neurons and average neuronal cell size

PubMed Central

Herculano-Houzel, Suzana; Manger, Paul R.; Kaas, Jon H.

2014-01-01

Enough species have now been subject to systematic quantitative analysis of the relationship between the morphology and cellular composition of their brain that patterns begin to emerge and shed light on the evolutionary path that led to mammalian brain diversity. Based on an analysis of the shared and clade-specific characteristics of 41 modern mammalian species in 6 clades, and in light of the phylogenetic relationships among them, here we propose that ancestral mammal brains were composed and scaled in their cellular composition like modern afrotherian and glire brains: with an addition of neurons that is accompanied by a decrease in neuronal density and very little modification in glial cell density, implying a significant increase in average neuronal cell size in larger brains, and the allocation of approximately 2 neurons in the cerebral cortex and 8 neurons in the cerebellum for every neuron allocated to the rest of brain. We also propose that in some clades the scaling of different brain structures has diverged away from the common ancestral layout through clade-specific (or clade-defining) changes in how average neuronal cell mass relates to numbers of neurons in each structure, and how numbers of neurons are differentially allocated to each structure relative to the number of neurons in the rest of brain. Thus, the evolutionary expansion of mammalian brains has involved both concerted and mosaic patterns of scaling across structures. This is, to our knowledge, the first mechanistic model that explains the generation of brains large and small in mammalian evolution, and it opens up new horizons for seeking the cellular pathways and genes involved in brain evolution. PMID:25157220

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

PubMed Central

Berretta, Regina; Moscato, Pablo

2016-01-01

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

High-throughput screening for identification of blood-brain barrier integrity enhancers: a drug repurposing opportunity to rectify vascular amyloid toxicity

PubMed Central

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

2016-01-01

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

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

NASA Astrophysics Data System (ADS)

Yue, Liu; Hang, Mend

2018-01-01

With the rapid development and construction of large-scale wind farms and grid-connected operation, the series compensation wind power AC transmission is gradually becoming the main way of power usage and improvement of wind power availability and grid stability, but the integration of wind farm will change the SSO (Sub-Synchronous oscillation) damping characteristics of synchronous generator system. Regarding the above SSO problem caused by integration of large-scale wind farms, this paper focusing on doubly fed induction generator (DFIG) based wind farms, aim to summarize the SSO mechanism in large-scale wind power integrated system with series compensation, which can be classified as three types: sub-synchronous control interaction (SSCI), sub-synchronous torsional interaction (SSTI), sub-synchronous resonance (SSR). Then, SSO modelling and analysis methods are categorized and compared by its applicable areas. Furthermore, this paper summarizes the suppression measures of actual SSO projects based on different control objectives. Finally, the research prospect on this field is explored.

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

PubMed

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

2006-05-01

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

A regulatory toolbox of MiniPromoters to drive selective expression in the brain

PubMed Central

Portales-Casamar, Elodie; Swanson, Douglas J.; Liu, Li; de Leeuw, Charles N.; Banks, Kathleen G.; Ho Sui, Shannan J.; Fulton, Debra L.; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J.; Babyak, Nazar; Black, Sonia F.; Bonaguro, Russell J.; Brauer, Erich; Candido, Tara R.; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C. Y.; Chopra, Vik; Docking, T. Roderick; Dreolini, Lisa; D'Souza, Cletus A.; Flynn, Erin K.; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G.; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y.; Lim, Jonathan S.; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J.; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L.; Schmouth, Jean-François; Swanson, Magdalena I.; Tam, Bonny; Ticoll, Amy; Turner, Jenna L.; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F.; Wilson, Gary; Wong, Bibiana K. Y.; Wong, Siaw H.; Wong, Tony Y. T.; Yang, George S.; Ypsilanti, Athena R.; Jones, Steven J. M.; Holt, Robert A.; Goldowitz, Daniel; Wasserman, Wyeth W.; Simpson, Elizabeth M.

2010-01-01

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination “knockins” in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5′ of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type–specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies. PMID:20807748

A regulatory toolbox of MiniPromoters to drive selective expression in the brain.

PubMed

Portales-Casamar, Elodie; Swanson, Douglas J; Liu, Li; de Leeuw, Charles N; Banks, Kathleen G; Ho Sui, Shannan J; Fulton, Debra L; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J; Babyak, Nazar; Black, Sonia F; Bonaguro, Russell J; Brauer, Erich; Candido, Tara R; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C Y; Chopra, Vik; Docking, T Roderick; Dreolini, Lisa; D'Souza, Cletus A; Flynn, Erin K; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y; Lim, Jonathan S; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L; Schmouth, Jean-François; Swanson, Magdalena I; Tam, Bonny; Ticoll, Amy; Turner, Jenna L; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F; Wilson, Gary; Wong, Bibiana K Y; Wong, Siaw H; Wong, Tony Y T; Yang, George S; Ypsilanti, Athena R; Jones, Steven J M; Holt, Robert A; Goldowitz, Daniel; Wasserman, Wyeth W; Simpson, Elizabeth M

2010-09-21

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination "knockins" in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5' of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type-specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies.

Dexmedetomidine Disrupts the Local and Global Efficiencies of Large-scale Brain Networks.

PubMed

Hashmi, Javeria A; Loggia, Marco L; Khan, Sheraz; Gao, Lei; Kim, Jieun; Napadow, Vitaly; Brown, Emery N; Akeju, Oluwaseun

2017-03-01

A clear understanding of the neural basis of consciousness is fundamental to research in clinical and basic neuroscience disciplines and anesthesia. Recently, decreased efficiency of information integration was suggested as a core network feature of propofol-induced unconsciousness. However, it is unclear whether this finding can be generalized to dexmedetomidine, which has a different molecular target. Dexmedetomidine was administered as a 1-μg/kg bolus over 10 min, followed by a 0.7-μg · kg · h infusion to healthy human volunteers (age range, 18 to 36 yr; n = 15). Resting-state functional magnetic resonance imaging data were acquired during baseline, dexmedetomidine-induced altered arousal, and recovery states. Zero-lag correlations between resting-state functional magnetic resonance imaging signals extracted from 131 brain parcellations were used to construct weighted brain networks. Network efficiency, degree distribution, and node strength were computed using graph analysis. Parcellated brain regions were also mapped to known resting-state networks to study functional connectivity changes. Dexmedetomidine significantly reduced the local and global efficiencies of graph theory-derived networks. Dexmedetomidine also reduced the average brain connectivity strength without impairing the degree distribution. Functional connectivity within and between all resting-state networks was modulated by dexmedetomidine. Dexmedetomidine is associated with a significant drop in the capacity for efficient information transmission at both the local and global levels. These changes result from reductions in the strength of connectivity and also manifest as reduced within and between resting-state network connectivity. These findings strengthen the hypothesis that conscious processing relies on an efficient system of information transfer in the brain.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Brain networks engaged in audiovisual integration during speech perception revealed by persistent homology-based network filtration.

PubMed

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

2015-05-01

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

Microfluidic large-scale integration: the evolution of design rules for biological automation.

PubMed

Melin, Jessica; Quake, Stephen R

2007-01-01

Microfluidic large-scale integration (mLSI) refers to the development of microfluidic chips with thousands of integrated micromechanical valves and control components. This technology is utilized in many areas of biology and chemistry and is a candidate to replace today's conventional automation paradigm, which consists of fluid-handling robots. We review the basic development of mLSI and then discuss design principles of mLSI to assess the capabilities and limitations of the current state of the art and to facilitate the application of mLSI to areas of biology. Many design and practical issues, including economies of scale, parallelization strategies, multiplexing, and multistep biochemical processing, are discussed. Several microfluidic components used as building blocks to create effective, complex, and highly integrated microfluidic networks are also highlighted.

The Development and Validation of the Religious/Spiritually Integrated Practice Assessment Scale

ERIC Educational Resources Information Center

Oxhandler, Holly K.; Parrish, Danielle E.

2016-01-01

Objective: This article describes the development and validation of the Religious/Spiritually Integrated Practice Assessment Scale (RSIPAS). The RSIPAS is designed to assess social work practitioners' self-efficacy, attitudes, behaviors, and perceived feasibility concerning the assessment or integration of clients' religious and spiritual beliefs…

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Large-scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy.

PubMed

de Campos, Brunno Machado; Coan, Ana Carolina; Lin Yasuda, Clarissa; Casseb, Raphael Fernandes; Cendes, Fernando

2016-09-01

Mesial temporal lobe epilepsy (MTLE) with hippocampus sclerosis (HS) is associated with functional and structural alterations extending beyond the temporal regions and abnormal pattern of brain resting state networks (RSNs) connectivity. We hypothesized that the interaction of large-scale RSNs is differently affected in patients with right- and left-MTLE with HS compared to controls. We aimed to determine and characterize these alterations through the analysis of 12 RSNs, functionally parceled in 70 regions of interest (ROIs), from resting-state functional-MRIs of 99 subjects (52 controls, 26 right- and 21 left-MTLE patients with HS). Image preprocessing and statistical analysis were performed using UF(2) C-toolbox, which provided ROI-wise results for intranetwork and internetwork connectivity. Intranetwork abnormalities were observed in the dorsal default mode network (DMN) in both groups of patients and in the posterior salience network in right-MTLE. Both groups showed abnormal correlation between the dorsal-DMN and the posterior salience, as well as between the dorsal-DMN and the executive-control network. Patients with left-MTLE also showed reduced correlation between the dorsal-DMN and visuospatial network and increased correlation between bilateral thalamus and the posterior salience network. The ipsilateral hippocampus stood out as a central area of abnormalities. Alterations on left-MTLE expressed a low cluster coefficient, whereas the altered connections on right-MTLE showed low cluster coefficient in the DMN but high in the posterior salience regions. Both right- and left-MTLE patients with HS have widespread abnormal interactions of large-scale brain networks; however, all parameters evaluated indicate that left-MTLE has a more intricate bihemispheric dysfunction compared to right-MTLE. Hum Brain Mapp 37:3137-3152, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by

On the Number of Neurons and Time Scale of Integration Underlying the Formation of Percepts in the Brain

PubMed Central

Wohrer, Adrien; Machens, Christian K.

2015-01-01

All of our perceptual experiences arise from the activity of neural populations. Here we study the formation of such percepts under the assumption that they emerge from a linear readout, i.e., a weighted sum of the neurons’ firing rates. We show that this assumption constrains the trial-to-trial covariance structure of neural activities and animal behavior. The predicted covariance structure depends on the readout parameters, and in particular on the temporal integration window w and typical number of neurons K used in the formation of the percept. Using these predictions, we show how to infer the readout parameters from joint measurements of a subject’s behavior and neural activities. We consider three such scenarios: (1) recordings from the complete neural population, (2) recordings of neuronal sub-ensembles whose size exceeds K, and (3) recordings of neuronal sub-ensembles that are smaller than K. Using theoretical arguments and artificially generated data, we show that the first two scenarios allow us to recover the typical spatial and temporal scales of the readout. In the third scenario, we show that the readout parameters can only be recovered by making additional assumptions about the structure of the full population activity. Our work provides the first thorough interpretation of (feed-forward) percept formation from a population of sensory neurons. We discuss applications to experimental recordings in classic sensory decision-making tasks, which will hopefully provide new insights into the nature of perceptual integration. PMID:25793393

Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof-of-concept and roadmap for future studies

PubMed Central

Anttila, Verneri; Hibar, Derrek P; van Hulzen, Kimm J E; Arias-Vasquez, Alejandro; Smoller, Jordan W; Nichols, Thomas E; Neale, Michael C; McIntosh, Andrew M; Lee, Phil; McMahon, Francis J; Meyer-Lindenberg, Andreas; Mattheisen, Manuel; Andreassen, Ole A; Gruber, Oliver; Sachdev, Perminder S; Roiz-Santiañez, Roberto; Saykin, Andrew J; Ehrlich, Stefan; Mather, Karen A; Turner, Jessica A; Schwarz, Emanuel; Thalamuthu, Anbupalam; Shugart, Yin Yao; Ho, Yvonne YW; Martin, Nicholas G; Wright, Margaret J

2016-01-01

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between schizophrenia cases and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. The current study provides proof-of-concept (albeit based on a limited set of structural brain measures), and defines a roadmap for future studies investigating the genetic covariance between structural/functional brain phenotypes and risk for psychiatric disorders. PMID:26854805

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

PubMed

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

2015-09-01

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

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

PubMed

Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Integrating Retraction Modeling Into an Atlas-Based Framework for Brain Shift Prediction

PubMed Central

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

2015-01-01

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

Recent developments in microfluidic large scale integration.

PubMed

Araci, Ismail Emre; Brisk, Philip

2014-02-01

In 2002, Thorsen et al. integrated thousands of micromechanical valves on a single microfluidic chip and demonstrated that the control of the fluidic networks can be simplified through multiplexors [1]. This enabled realization of highly parallel and automated fluidic processes with substantial sample economy advantage. Moreover, the fabrication of these devices by multilayer soft lithography was easy and reliable hence contributed to the power of the technology; microfluidic large scale integration (mLSI). Since then, mLSI has found use in wide variety of applications in biology and chemistry. In the meantime, efforts to improve the technology have been ongoing. These efforts mostly focus on; novel materials, components, micromechanical valve actuation methods, and chip architectures for mLSI. In this review, these technological advances are discussed and, recent examples of the mLSI applications are summarized. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effect of meditation on psychological distress and brain functioning: A randomized controlled study.

PubMed

Travis, Fred; Valosek, Laurent; Konrad, Arthur; Link, Janice; Salerno, John; Scheller, Ray; Nidich, Sanford

2018-06-21

Psychological stability and brain integration are important factors related to physical and mental health and organization effectiveness. This study tested whether a mind-body technique, the Transcendental Meditation (TM) program could increase EEG brain integration and positive affect, and decrease psychological distress in government employees. Ninety-six central office administrators and staff at the San Francisco Unified School District were randomly assigned to either immediate start of the TM program or to a wait-list control group. At baseline and four-month posttest, participants completed an online version of the Profile of Mood States questionnaire (POMS). In addition, a subset of this population (N = 79) had their EEG recorded at baseline and at four-month posttest to calculate Brain Integration Scale (BIS) scores. At posttest, TM participants significantly decreased on the POMS Total Mood Disturbance and anxiety, anger, depression, fatigue, and confusion subscales, and significantly increased in the POMS vigor subscale. TM participants in the EEG-subgroup also significantly increased in BIS scores. Compliance with meditation practice was high (93%). Findings indicate the feasibility and effectiveness of implementing the TM program to improve brain integration and positive affect and reduce psychological distress in government administrators and staff. Copyright © 2018. Published by Elsevier Inc.

Determinants of Glasgow outcome scale in patients with severe traumatic brain injury for better quality of life

NASA Astrophysics Data System (ADS)

Dharmajaya, R.; Sari, D. K.; Ganie, R. A.

2018-03-01

Primary and secondary brain injury may occur with severe traumatic brain injury. Secondary traumatic brain injury results in a more severe effect compared to primary traumatic brain injury. Therefore, prevention of secondary traumatic brain injury is necessary to obtain maximum therapeutic results and accurate determination of prognosis and better quality of life. This study aimed to determine accurate and noninvasive prognostic factors in patients with severe traumatic brain injury. It was a cohort study on 16 subjects. Intracranial pressure was monitored within the first 24 hours after traumatic brain injury. Examination of Brain-Derived Neurotrophic Factor (BDNF) and S100B protein were conducted four times. The severity of outcome was evaluated using Glasgow Outcome Scale (GOS) three months after traumatic brain injury. Intracranial pressure measurement performed 24 hours after traumatic brain injury, low S100B protein (<2μg/L) 120 hours after injury and increased BDNF (>6.16pg/ml) 48 hours after injury indicate good prognosis and were shown to be significant predictors (p<0.05) for determining the quality of GOS. The conclusion is patient with a moderate increase in intracranial pressure Intracranial pressure S100B protein, being inexpensive and non-invasive, can substitute BDNF and intracranial pressure measurements as a tool for determining prognosis 120 hours following traumatic brain injury.

Left Brain/Right Brain Learning for Adult Education.

ERIC Educational Resources Information Center

Garvin, Barbara

1986-01-01

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

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

PubMed

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

2016-07-06

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

When Can Information from Ordinal Scale Variables Be Integrated?

ERIC Educational Resources Information Center

Kemp, Simon; Grace, Randolph C.

2010-01-01

Many theoretical constructs of interest to psychologists are multidimensional and derive from the integration of several input variables. We show that input variables that are measured on ordinal scales cannot be combined to produce a stable weakly ordered output variable that allows trading off the input variables. Instead a partial order is…

Scale relativity theory and integrative systems biology: 2. Macroscopic quantum-type mechanics.

PubMed

Nottale, Laurent; Auffray, Charles

2008-05-01

In these two companion papers, we provide an overview and a brief history of the multiple roots, current developments and recent advances of integrative systems biology and identify multiscale integration as its grand challenge. Then we introduce the fundamental principles and the successive steps that have been followed in the construction of the scale relativity theory, which aims at describing the effects of a non-differentiable and fractal (i.e., explicitly scale dependent) geometry of space-time. The first paper of this series was devoted, in this new framework, to the construction from first principles of scale laws of increasing complexity, and to the discussion of some tentative applications of these laws to biological systems. In this second review and perspective paper, we describe the effects induced by the internal fractal structures of trajectories on motion in standard space. Their main consequence is the transformation of classical dynamics into a generalized, quantum-like self-organized dynamics. A Schrödinger-type equation is derived as an integral of the geodesic equation in a fractal space. We then indicate how gauge fields can be constructed from a geometric re-interpretation of gauge transformations as scale transformations in fractal space-time. Finally, we introduce a new tentative development of the theory, in which quantum laws would hold also in scale space, introducing complexergy as a measure of organizational complexity. Initial possible applications of this extended framework to the processes of morphogenesis and the emergence of prokaryotic and eukaryotic cellular structures are discussed. Having founded elements of the evolutionary, developmental, biochemical and cellular theories on the first principles of scale relativity theory, we introduce proposals for the construction of an integrative theory of life and for the design and implementation of novel macroscopic quantum-type experiments and devices, and discuss their potential

Integral criteria for large-scale multiple fingerprint solutions

NASA Astrophysics Data System (ADS)

Ushmaev, Oleg S.; Novikov, Sergey O.

2004-08-01

We propose the definition and analysis of the optimal integral similarity score criterion for large scale multmodal civil ID systems. Firstly, the general properties of score distributions for genuine and impostor matches for different systems and input devices are investigated. The empirical statistics was taken from the real biometric tests. Then we carry out the analysis of simultaneous score distributions for a number of combined biometric tests and primary for ultiple fingerprint solutions. The explicit and approximate relations for optimal integral score, which provides the least value of the FRR while the FAR is predefined, have been obtained. The results of real multiple fingerprint test show good correspondence with the theoretical results in the wide range of the False Acceptance and the False Rejection Rates.

Hardware in the Loop at Megawatt-Scale Power | Energy Systems Integration

Science.gov Websites

Facility | NREL Hardware in the Loop at Megawatt-Scale Power Hardware in the Loop at Megawatt -Scale Power Hardware-in-the-loop simulation is not new, but the Energy System Integration Facility's -in-the-loop co-simulation. For more information, read the power hardware-in-the-loop factsheet. Text

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

Neurodegeneration from mitochondrial insufficiency: nutrients, stem cells, growth factors, and prospects for brain rebuilding using integrative management.

PubMed

Kidd, Parris M

2005-12-01

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

Differentiating unipolar and bipolar depression by alterations in large-scale brain networks.

PubMed

Goya-Maldonado, Roberto; Brodmann, Katja; Keil, Maria; Trost, Sarah; Dechent, Peter; Gruber, Oliver

2016-02-01

Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolar patients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolar patients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.

PubMed

Somasundaram, Karuppanagounder; Ezhilarasan, Kamalanathan

2015-01-01

To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. The proposed method is based on gray scale transformation and morphological operations. The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

PubMed

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

Patients' experiences and care needs during the diagnostic phase of an Integrated Brain Cancer Pathway: A Case Study.

PubMed

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

2018-03-31

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

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

PubMed Central

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

2015-01-01

In recent years there has been a resurgence of interest in brain barriers and various roles their intrinsic mechanisms may play in neurological disorders. Such studies require suitable models and markers to demonstrate integrity and functional changes at the interfaces between blood, brain, and cerebrospinal fluid. Studies of brain barrier mechanisms and measurements of plasma volume using dyes have a long-standing history, dating back to the late nineteenth-century. Their use in blood-brain barrier studies continues in spite of their known serious limitations in in vivo applications. These were well known when first introduced, but seem to have been forgotten since. Understanding these limitations is important because Evans blue is still the most commonly used marker of brain barrier integrity and those using it seem oblivious to problems arising from its in vivo application. The introduction of HRP in the mid twentieth-century was an important advance because its reaction product can be visualized at the electron microscopical level, but it also has limitations. Advantages and disadvantages of these markers will be discussed together with a critical evaluation of alternative approaches. There is no single marker suitable for all purposes. A combination of different sized, visualizable dextrans and radiolabeled molecules currently seems to be the most appropriate approach for qualitative and quantitative assessment of barrier integrity. PMID:26578854

Community integration 2 years after moderate and severe traumatic brain injury.

PubMed

Sandhaug, Maria; Andelic, Nada; Langhammer, Birgitta; Mygland, Aase

2015-01-01

The aim of this study was to examine community integration by the Community Integration Questionnaire (CIQ) 2 years after injury in a divided TBI sample of moderately and severely injured patients. The second aim was to identify social-demographic, injury-related and rehabilitation associated predictors of CIQ. A cohort study. Outpatient follow-up. Fifty-seven patients with moderate (n = 21) or severe (n = 36) TBI were examined with the Community Integration Questionnaire (CIQ) at 2 years after injury. Possible predictors were analysed in a regression model using CIQ total score at 2 years as the outcome measure. The Community Integration Questionnaire. At 2 years follow-up, there was significant difference between the moderately and severely injured patients in the productivity scores (p < 0.003), while difference in the total CIQ scores approached the significance level (p = 0.074). Significant predictors of a higher CIQ score were living with a spouse, higher Glasgow Coma Scale (GCS) in the acute phase, shorter Post-Traumatic Amnesia (PTA), longer rehabilitation stay (LOS) and use of rehabilitation service. Use of rehabilitation service (B = 7.766) and living with a spouse (B = 4.251) had the largest influence. This means that living with a spouse, better score on the GCS scale, shorter PTA, longer LOS and use of rehabilitation service after discharge equated to better community integration 2 years after TBI Conclusions: Two years after TBI the moderately injured patients have a higher productivity level than the severely injured patients. Marital status, injury severity and rehabilitation after injury were associated with community integration 2 years after TBI.

A genome-scale map of expression for a mouse brain section obtained using voxelation

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

Chin, Mark H.; Geng, Alex B.; Khan, Arshad H.

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases. We have reconstructed 2- dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 mm3. Good reliability of the microarray results were confirmed using multiple replicates, subsequent quantitative RT-PCR voxelation, mass spectrometry voxelation and publicly available in situ hybridization data. Known and novel genes were identified with expression patterns localized to defined substructures within the brain. In addition, genesmore » with unexpected patterns were identified and cluster analysis identified a set of genes with a gradient of dorsal/ventral expression not restricted to known anatomical boundaries. The genome-scale maps of gene expression obtained using voxelation will be a valuable tool for the neuroscience community.« less

TVB-EduPack—An Interactive Learning and Scripting Platform for The Virtual Brain

PubMed Central

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

2015-01-01

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

St. Louis Initiative for Integrated Care Excellence (SLI(2)CE): integrated-collaborative care on a large scale model.

PubMed

Brawer, Peter A; Martielli, Richard; Pye, Patrice L; Manwaring, Jamie; Tierney, Anna

2010-06-01

The primary care health setting is in crisis. Increasing demand for services, with dwindling numbers of providers, has resulted in decreased access and decreased satisfaction for both patients and providers. Moreover, the overwhelming majority of primary care visits are for behavioral and mental health concerns rather than issues of a purely medical etiology. Integrated-collaborative models of health care delivery offer possible solutions to this crisis. The purpose of this article is to review the existing data available after 2 years of the St. Louis Initiative for Integrated Care Excellence; an example of integrated-collaborative care on a large scale model within a regional Veterans Affairs Health Care System. There is clear evidence that the SLI(2)CE initiative rather dramatically increased access to health care, and modified primary care practitioners' willingness to address mental health issues within the primary care setting. In addition, data suggests strong fidelity to a model of integrated-collaborative care which has been successful in the past. Integrated-collaborative care offers unique advantages to the traditional view and practice of medical care. Through careful implementation and practice, success is possible on a large scale model. PsycINFO Database Record (c) 2010 APA, all rights reserved.

The importance of integration and scale in the arbuscular mycorrhizal symbiosis.

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

Miller, R. M.; Kling, M.; Environmental Research

The arbuscular mycorrhizal (AM) fungus contributes to system processes and functions at various hierarchical organizational levels, through their establishment of linkages and feedbacks between whole-plants and nutrient cycles. Even though these fungal mediated feedbacks and linkages involve lower-organizational level processes (e.g. photo-assimilate partitioning, interfacial assimilate uptake and transport mechanisms, intraradical versus extraradical fungal growth), they influence higher-organizational scales that affect community and ecosystem behavior (e.g. whole-plant photosynthesis, biodiversity, nutrient and carbon cycling, soil structure). Hence, incorporating AM fungi into research directed at understanding many of the diverse environmental issues confronting society will require knowledge of how these fungi respond tomore » or initiate changes in vegetation dynamics, soil fertility or both. Within the last few years, the rapid advancement in the development of analytical tools has increased the resolution by which we are able to quantify the mycorrhizal symbiosis. It is important that these tools are applied within a conceptual framework that is temporally and spatially relevant to fungus and host. Unfortunately, many of the studies being conducted on the mycorrhizal symbiosis at lower organizational scales are concerned with questions directed solely at understanding fungus or host without awareness of what the plant physiologist or ecologist needs for integrating the mycorrhizal association into larger organizational scales or process levels. We show by using the flow of C from plant-to-fungus-to-soil, that through thoughtful integration, we have the ability to bridge different organizational scales. Thus, an essential need of mycorrhizal research is not only to better integrate the various disciplines of mycorrhizal research, but also to identify those relevant links and scales needing further investigation for understanding the larger

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

PubMed

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

2015-07-01

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

Using Hybrid Techniques for Generating Watershed-scale Flood Models in an Integrated Modeling Framework

NASA Astrophysics Data System (ADS)

Saksena, S.; Merwade, V.; Singhofen, P.

2017-12-01

There is an increasing global trend towards developing large scale flood models that account for spatial heterogeneity at watershed scales to drive the future flood risk planning. Integrated surface water-groundwater modeling procedures can elucidate all the hydrologic processes taking part during a flood event to provide accurate flood outputs. Even though the advantages of using integrated modeling are widely acknowledged, the complexity of integrated process representation, computation time and number of input parameters required have deterred its application to flood inundation mapping, especially for large watersheds. This study presents a faster approach for creating watershed scale flood models using a hybrid design that breaks down the watershed into multiple regions of variable spatial resolution by prioritizing higher order streams. The methodology involves creating a hybrid model for the Upper Wabash River Basin in Indiana using Interconnected Channel and Pond Routing (ICPR) and comparing the performance with a fully-integrated 2D hydrodynamic model. The hybrid approach involves simplification procedures such as 1D channel-2D floodplain coupling; hydrologic basin (HUC-12) integration with 2D groundwater for rainfall-runoff routing; and varying spatial resolution of 2D overland flow based on stream order. The results for a 50-year return period storm event show that hybrid model (NSE=0.87) performance is similar to the 2D integrated model (NSE=0.88) but the computational time is reduced to half. The results suggest that significant computational efficiency can be obtained while maintaining model accuracy for large-scale flood models by using hybrid approaches for model creation.

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

PubMed

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

2013-04-01

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

Dynamic Monitoring of Blood-Brain Barrier Integrity using Water Exchange Index (WEI) During Mannitol and CO2 Challenges in Mouse Brain

PubMed Central

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

2012-01-01

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

Evaluation of laser speckle contrast imaging as an intrinsic method to monitor blood brain barrier integrity

PubMed Central

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

2013-01-01

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

Large-scale imaging in small brains.

PubMed

Ahrens, Misha B; Engert, Florian

2015-06-01

The dense connectivity in the brain means that one neuron's activity can influence many others. To observe this interconnected system comprehensively, an aspiration within neuroscience is to record from as many neurons as possible at the same time. There are two useful routes toward this goal: one is to expand the spatial extent of functional imaging techniques, and the second is to use animals with small brains. Here we review recent progress toward imaging many neurons and complete populations of identified neurons in small vertebrates and invertebrates. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reducing the two-loop large-scale structure power spectrum to low-dimensional, radial integrals

DOE PAGES

Schmittfull, Marcel; Vlah, Zvonimir

2016-11-28

Modeling the large-scale structure of the universe on nonlinear scales has the potential to substantially increase the science return of upcoming surveys by increasing the number of modes available for model comparisons. One way to achieve this is to model nonlinear scales perturbatively. Unfortunately, this involves high-dimensional loop integrals that are cumbersome to evaluate. Here, trying to simplify this, we show how two-loop (next-to-next-to-leading order) corrections to the density power spectrum can be reduced to low-dimensional, radial integrals. Many of those can be evaluated with a one-dimensional fast Fourier transform, which is significantly faster than the five-dimensional Monte-Carlo integrals thatmore » are needed otherwise. The general idea of this fast fourier transform perturbation theory method is to switch between Fourier and position space to avoid convolutions and integrate over orientations, leaving only radial integrals. This reformulation is independent of the underlying shape of the initial linear density power spectrum and should easily accommodate features such as those from baryonic acoustic oscillations. We also discuss how to account for halo bias and redshift space distortions.« less

Developing a comprehensive framework of community integration for people with acquired brain injury: a conceptual analysis.

PubMed

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

2018-03-06

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

Fabrication of nano-scale Cu bond pads with seal design in 3D integration applications.

PubMed

Chen, K N; Tsang, C K; Wu, W W; Lee, S H; Lu, J Q

2011-04-01

A method to fabricate nano-scale Cu bond pads for improving bonding quality in 3D integration applications is reported. The effect of Cu bonding quality on inter-level via structural reliability for 3D integration applications is investigated. We developed a Cu nano-scale-height bond pad structure and fabrication process for improved bonding quality by recessing oxides using a combination of SiO2 CMP process and dilute HF wet etching. In addition, in order to achieve improved wafer-level bonding, we introduced a seal design concept that prevents corrosion and provides extra mechanical support. Demonstrations of these concepts and processes provide the feasibility of reliable nano-scale 3D integration applications.

Psychometric properties of the Multidimensional Assessment of Fatigue scale in traumatic brain injury: an NIDRR Traumatic Brain Injury Model Systems study.

PubMed

Lequerica, Anthony; Bushnik, Tamara; Wright, Jerry; Kolakowsky-Hayner, Stephanie A; Hammond, Flora M; Dijkers, Marcel P; Cantor, Joshua

2012-01-01

To investigate the psychometric properties of the Multidimensional Assessment of Fatigue (MAF) scale in a traumatic brain injury (TBI) sample. Prospective survey study. Community. One hundred sixty-seven individuals with TBI admitted for inpatient rehabilitation, enrolled into the TBI Model Systems national database, and followed up at either the first or second year postinjury. Not applicable. Multidimensional Assessment of Fatigue. The initial analysis, using items 1 to 14, which are based on a 10-point rating scale, found that only 1 item ("walking") misfit the overall construct of fatigue in this TBI population. However, this 10-point rating scale was found to have disordered thresholds. When ratings were collapsed into 4 response categories, all MAF items used to calculate the Global Fatigue Index formed a unidimensional scale. Findings generally support the unidimensionality of the MAF when used in a TBI population but call into question the use of a 10-point rating scale for items 1 to 14. Further study is needed to investigate the use of a 4-category rating scale across all items and the fit of the "walking" item for a measure of fatigue among individuals with TBI.

Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework

PubMed Central

Talluto, Matthew V.; Boulangeat, Isabelle; Ameztegui, Aitor; Aubin, Isabelle; Berteaux, Dominique; Butler, Alyssa; Doyon, Frédérik; Drever, C. Ronnie; Fortin, Marie-Josée; Franceschini, Tony; Liénard, Jean; McKenney, Dan; Solarik, Kevin A.; Strigul, Nikolay; Thuiller, Wilfried; Gravel, Dominique

2016-01-01

Aim Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. Location Eastern North America (as an example). Methods Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America. Results For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. Main conclusions We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can

Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework.

PubMed

Talluto, Matthew V; Boulangeat, Isabelle; Ameztegui, Aitor; Aubin, Isabelle; Berteaux, Dominique; Butler, Alyssa; Doyon, Frédérik; Drever, C Ronnie; Fortin, Marie-Josée; Franceschini, Tony; Liénard, Jean; McKenney, Dan; Solarik, Kevin A; Strigul, Nikolay; Thuiller, Wilfried; Gravel, Dominique

2016-02-01

Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. Eastern North America (as an example). Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple ( Acer saccharum ), an abundant tree native to eastern North America. For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

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

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

MAINTAINING DATA QUALITY IN THE PERFORMANCE OF A LARGE SCALE INTEGRATED MONITORING EFFORT

EPA Science Inventory

Macauley, John M. and Linda C. Harwell. In press. Maintaining Data Quality in the Performance of a Large Scale Integrated Monitoring Effort (Abstract). To be presented at EMAP Symposium 2004: Integrated Monitoring and Assessment for Effective Water Quality Management, 3-7 May 200...

[Impact of acquired brain injury towards the community integration: employment outcome, disability and dependence two years after injury].

PubMed

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

2016-06-16

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

Lateralized Feeding Behavior is Associated with Asymmetrical Neuroanatomy and Lateralized Gene Expressions in the Brain in Scale-Eating Cichlid Fish

PubMed Central

Lee, Hyuk Je; Schneider, Ralf F; Manousaki, Tereza; Kang, Ji Hyoun; Lein, Etienne; Franchini, Paolo

2017-01-01

Abstract Lateralized behavior (“handedness”) is unusual, but consistently found across diverse animal lineages, including humans. It is thought to reflect brain anatomical and/or functional asymmetries, but its neuro-molecular mechanisms remain largely unknown. Lake Tanganyika scale-eating cichlid fish, Perissodus microlepis show pronounced asymmetry in their jaw morphology as well as handedness in feeding behavior—biting scales preferentially only from one or the other side of their victims. This makes them an ideal model in which to investigate potential laterality in neuroanatomy and transcription in the brain in relation to behavioral handedness. After determining behavioral handedness in P. microlepis (preferred attack side), we estimated the volume of the hemispheres of brain regions and captured their gene expression profiles. Our analyses revealed that the degree of behavioral handedness is mirrored at the level of neuroanatomical asymmetry, particularly in the tectum opticum. Transcriptome analyses showed that different brain regions (tectum opticum, telencephalon, hypothalamus, and cerebellum) display distinct expression patterns, potentially reflecting their developmental interrelationships. For numerous genes in each brain region, their extent of expression differences between hemispheres was found to be correlated with the degree of behavioral lateralization. Interestingly, the tectum opticum and telencephalon showed divergent biases on the direction of up- or down-regulation of the laterality candidate genes (e.g., grm2) in the hemispheres, highlighting the connection of handedness with gene expression profiles and the different roles of these brain regions. Hence, handedness in predation behavior may be caused by asymmetric size of brain hemispheres and also by lateralized gene expressions in the brain. PMID:29069363

The social brain: scale-invariant layering of Erdős-Rényi networks in small-scale human societies.

PubMed

Harré, Michael S; Prokopenko, Mikhail

2016-05-01

The cognitive ability to form social links that can bind individuals together into large cooperative groups for safety and resource sharing was a key development in human evolutionary and social history. The 'social brain hypothesis' argues that the size of these social groups is based on a neurologically constrained capacity for maintaining long-term stable relationships. No model to date has been able to combine a specific socio-cognitive mechanism with the discrete scale invariance observed in ethnographic studies. We show that these properties result in nested layers of self-organizing Erdős-Rényi networks formed by each individual's ability to maintain only a small number of social links. Each set of links plays a specific role in the formation of different social groups. The scale invariance in our model is distinct from previous 'scale-free networks' studied using much larger social groups; here, the scale invariance is in the relationship between group sizes, rather than in the link degree distribution. We also compare our model with a dominance-based hierarchy and conclude that humans were probably egalitarian in hunter-gatherer-like societies, maintaining an average maximum of four or five social links connecting all members in a largest social network of around 132 people. © 2016 The Author(s).

Do large-scale assessments measure students' ability to integrate scientific knowledge?

NASA Astrophysics Data System (ADS)

Lee, Hee-Sun

2010-03-01

Large-scale assessments are used as means to diagnose the current status of student achievement in science and compare students across schools, states, and countries. For efficiency, multiple-choice items and dichotomously-scored open-ended items are pervasively used in large-scale assessments such as Trends in International Math and Science Study (TIMSS). This study investigated how well these items measure secondary school students' ability to integrate scientific knowledge. This study collected responses of 8400 students to 116 multiple-choice and 84 open-ended items and applied an Item Response Theory analysis based on the Rasch Partial Credit Model. Results indicate that most multiple-choice items and dichotomously-scored open-ended items can be used to determine whether students have normative ideas about science topics, but cannot measure whether students integrate multiple pieces of relevant science ideas. Only when the scoring rubric is redesigned to capture subtle nuances of student open-ended responses, open-ended items become a valid and reliable tool to assess students' knowledge integration ability.

Large-scale imaging in small brains

PubMed Central

Ahrens, Misha B.; Engert, Florian

2016-01-01

The dense connectivity in the brain and arrangements of cells into circuits means that one neuron’s activity can influence many others. To observe this interconnected system comprehensively, an aspiration within neuroscience is to record from as many neurons as possible at the same time. There are two useful routes toward this goal: one is to expand the spatial extent of functional imaging techniques, and the second is to use animals with small brains. Here we review recent progress toward imaging many neurons and complete populations of identified neurons in small vertebrates and invertebrates. PMID:25636154

Patient navigation for traumatic brain injury promotes community re-integration and reduces re-hospitalizations.

PubMed

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

2017-01-01

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

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

PubMed

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

2016-07-01

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

A Multi-Scale, Integrated Approach to Representing Watershed Systems

NASA Astrophysics Data System (ADS)

Ivanov, Valeriy; Kim, Jongho; Fatichi, Simone; Katopodes, Nikolaos

2014-05-01

Understanding and predicting process dynamics across a range of scales are fundamental challenges for basic hydrologic research and practical applications. This is particularly true when larger-spatial-scale processes, such as surface-subsurface flow and precipitation, need to be translated to fine space-time scale dynamics of processes, such as channel hydraulics and sediment transport, that are often of primary interest. Inferring characteristics of fine-scale processes from uncertain coarse-scale climate projection information poses additional challenges. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion, and sediment transport, tRIBS+VEGGIE-FEaST. The model targets to take the advantage of the current generation of wealth of data representing watershed topography, vegetation, soil, and landuse, as well as to explore the hydrological effects of physical factors and their feedback mechanisms over a range of scales. We illustrate how the modeling system connects precipitation-hydrologic runoff partition process to the dynamics of flow, erosion, and sedimentation, and how the soil's substrate condition can impact the latter processes, resulting in a non-unique response. We further illustrate an approach to using downscaled climate change information with a process-based model to infer the moments of hydrologic variables in future climate conditions and explore the impact of climate information uncertainty.

An integrated approach to reconstructing genome-scale transcriptional regulatory networks

DOE PAGES

Imam, Saheed; Noguera, Daniel R.; Donohue, Timothy J.; ...

2015-02-27

Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied γ-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making themmore » highly complementary. We leveraged this new workflow and observations to build a large-scale TRN model for the α-Proteobacterium Rhodobacter sphaeroides that comprises 120 gene clusters, 1211 genes (including 93 TFs), 1858 predicted protein-DNA interactions and 76 DNA binding motifs. We found that ~67% of the predicted gene clusters in this TRN are enriched for functions ranging from photosynthesis or central carbon metabolism to environmental stress responses. We also found that members of many of the predicted gene clusters were consistent with prior knowledge in R. sphaeroides and/or other bacteria. Experimental validation of predictions from this R. sphaeroides TRN model showed that high precision and recall was also obtained for TFs involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341). In addition, this integrative approach enabled generation of TRNs with increased information content relative to R. sphaeroides TRN models built via other approaches. We also show how this approach can be used to simultaneously produce TRN models for each related organism used in the comparative genomics analysis. Our results highlight the advantages of

The Integrative Psychotherapy Alliance: Family, Couple and Individual Therapy Scales.

ERIC Educational Resources Information Center

Pinsof, William M.; Catherall, Donald R.

1986-01-01

Presents an integrative definition of the therapeutic alliance that conceptualizes individual, couple and family therapy as occurring within the same systemic framework. The implications of this concept for therapy reserach are examined. Three new systematically oriented scales to measure the alliance are presented along with some preliminary data…

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

PubMed

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

2016-06-01

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

A 3D Real-Scale, Biomimetic, and Biohybrid Model of the Blood-Brain Barrier Fabricated through Two-Photon Lithography.

PubMed

Marino, Attilio; Tricinci, Omar; Battaglini, Matteo; Filippeschi, Carlo; Mattoli, Virgilio; Sinibaldi, Edoardo; Ciofani, Gianni

2018-02-01

The investigation of the crossing of exogenous substances through the blood-brain barrier (BBB) is object of intensive research in biomedicine, and one of the main obstacles for reliable in vitro evaluations is represented by the difficulties at the base of developing realistic models of the barrier, which could resemble as most accurately as possible the in vivo environment. Here, for the first time, a 1:1 scale, biomimetic, and biohybrid BBB model is proposed. Microtubes inspired to the brain capillaries were fabricated through two-photon lithography and used as scaffolds for the co-culturing of endothelial-like bEnd.3 and U87 glioblastoma cells. The constructs show the maturation of tight junctions, good performances in terms of hindering dextran diffusion through the barrier, and a satisfactory trans-endothelial electrical resistance. Moreover, a mathematical model is developed, which assists in both the design of the 3D microfluidic chip and its characterization. Overall, these results show the effective formation of a bioinspired cellular barrier based on microtubes reproducing brain microcapillaries to scale. This system will be exploited as a realistic in vitro model for the investigation of BBB crossing of nanomaterials and drugs, envisaging therapeutic and diagnostic applications for several brain pathologies, including brain cancer. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly Crumpled All-Carbon Transistors for Brain Activity Recording.

PubMed

Yang, Long; Zhao, Yan; Xu, Wenjing; Shi, Enzheng; Wei, Wenjing; Li, Xinming; Cao, Anyuan; Cao, Yanping; Fang, Ying

2017-01-11

Neural probes based on graphene field-effect transistors have been demonstrated. Yet, the minimum detectable signal of graphene transistor-based probes is inversely proportional to the square root of the active graphene area. This fundamentally limits the scaling of graphene transistor-based neural probes for improved spatial resolution in brain activity recording. Here, we address this challenge using highly crumpled all-carbon transistors formed by compressing down to 16% of its initial area. All-carbon transistors, chemically synthesized by seamless integration of graphene channels and hybrid graphene/carbon nanotube electrodes, maintained structural integrity and stable electronic properties under large mechanical deformation, whereas stress-induced cracking and junction failure occurred in conventional graphene/metal transistors. Flexible, highly crumpled all-carbon transistors were further verified for in vivo recording of brain activity in rats. These results highlight the importance of advanced material and device design concepts to make improvements in neuroelectronics.

Wafer-scale integrated micro-supercapacitors on an ultrathin and highly flexible biomedical platform.

PubMed

Maeng, Jimin; Meng, Chuizhou; Irazoqui, Pedro P

2015-02-01

We present wafer-scale integrated micro-supercapacitors on an ultrathin and highly flexible parylene platform, as progress toward sustainably powering biomedical microsystems suitable for implantable and wearable applications. All-solid-state, low-profile (<30 μm), and high-density (up to ~500 μF/mm(2)) micro-supercapacitors are formed on an ultrathin (~20 μm) freestanding parylene film by a wafer-scale parylene packaging process in combination with a polyaniline (PANI) nanowire growth technique assisted by surface plasma treatment. These micro-supercapacitors are highly flexible and shown to be resilient toward flexural stress. Further, direct integration of micro-supercapacitors into a radio frequency (RF) rectifying circuit is achieved on a single parylene platform, yielding a complete RF energy harvesting microsystem. The system discharging rate is shown to improve by ~17 times in the presence of the integrated micro-supercapacitors. This result suggests that the integrated micro-supercapacitor technology described herein is a promising strategy for sustainably powering biomedical microsystems dedicated to implantable and wearable applications.

An Integrated Assessment of Location-Dependent Scaling for Microalgae Biofuel Production Facilities

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

Coleman, Andre M.; Abodeely, Jared; Skaggs, Richard

Successful development of a large-scale microalgae-based biofuels industry requires comprehensive analysis and understanding of the feedstock supply chain—from facility siting/design through processing/upgrading of the feedstock to a fuel product. The evolution from pilot-scale production facilities to energy-scale operations presents many multi-disciplinary challenges, including a sustainable supply of water and nutrients, operational and infrastructure logistics, and economic competitiveness with petroleum-based fuels. These challenges are addressed in part by applying the Integrated Assessment Framework (IAF)—an integrated multi-scale modeling, analysis, and data management suite—to address key issues in developing and operating an open-pond facility by analyzing how variability and uncertainty in space andmore » time affect algal feedstock production rates, and determining the site-specific “optimum” facility scale to minimize capital and operational expenses. This approach explicitly and systematically assesses the interdependence of biofuel production potential, associated resource requirements, and production system design trade-offs. The IAF was applied to a set of sites previously identified as having the potential to cumulatively produce 5 billion-gallons/year in the southeastern U.S. and results indicate costs can be reduced by selecting the most effective processing technology pathway and scaling downstream processing capabilities to fit site-specific growing conditions, available resources, and algal strains.« less

An integrated assessment of location-dependent scaling for microalgae biofuel production facilities

DOE PAGES

Coleman, André M.; Abodeely, Jared M.; Skaggs, Richard L.; ...

2014-06-19

Successful development of a large-scale microalgae-based biofuels industry requires comprehensive analysis and understanding of the feedstock supply chain—from facility siting and design through processing and upgrading of the feedstock to a fuel product. The evolution from pilot-scale production facilities to energy-scale operations presents many multi-disciplinary challenges, including a sustainable supply of water and nutrients, operational and infrastructure logistics, and economic competitiveness with petroleum-based fuels. These challenges are partially addressed by applying the Integrated Assessment Framework (IAF) – an integrated multi-scale modeling, analysis, and data management suite – to address key issues in developing and operating an open-pond microalgae production facility.more » This is done by analyzing how variability and uncertainty over space and through time affect feedstock production rates, and determining the site-specific “optimum” facility scale to minimize capital and operational expenses. This approach explicitly and systematically assesses the interdependence of biofuel production potential, associated resource requirements, and production system design trade-offs. To provide a baseline analysis, the IAF was applied in this paper to a set of sites in the southeastern U.S. with the potential to cumulatively produce 5 billion gallons per year. Finally, the results indicate costs can be reduced by scaling downstream processing capabilities to fit site-specific growing conditions, available and economically viable resources, and specific microalgal strains.« less

A mesoscale connectome of the mouse brain

PubMed Central

Oh, Seung Wook; Harris, Julie A.; Ng, Lydia; Winslow, Brent; Cain, Nicholas; Mihalas, Stefan; Wang, Quanxin; Lau, Chris; Kuan, Leonard; Henry, Alex M.; Mortrud, Marty T.; Ouellette, Benjamin; Nguyen, Thuc Nghi; Sorensen, Staci A.; Slaughterbeck, Clifford R.; Wakeman, Wayne; Li, Yang; Feng, David; Ho, Anh; Nicholas, Eric; Hirokawa, Karla E.; Bohn, Phillip; Joines, Kevin M.; Peng, Hanchuan; Hawrylycz, Michael J.; Phillips, John W.; Hohmann, John G.; Wohnoutka, Paul; Gerfen, Charles R.; Koch, Christof; Bernard, Amy; Dang, Chinh; Jones, Allan R.; Zeng, Hongkui

2016-01-01

Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease. PMID:24695228

A comparison of participation outcome measures and the International Classification of Functioning, Disability and Health Core Sets for traumatic brain injury.

PubMed

Chung, Pearl; Yun, Sarah Jin; Khan, Fary

2014-02-01

To compare the contents of participation outcome measures in traumatic brain injury with the International Classification of Functioning, Disability and Health (ICF) Core Sets for traumatic brain injury. A systematic search with an independent review process selected relevant articles to identify outcome measures in participation in traumatic brain injury. Instruments used in two or more studies were linked to the ICF categories, which identified categories in participation for comparison with the ICF Core Sets for traumatic brain injury. Selected articles (n = 101) identified participation instruments used in two or more studies (n = 9): Community Integration Questionnaire, Craig Handicap Assessment and Reporting Technique, Mayo-Portland Adaptability Inventory-4 Participation Index, Sydney Psychosocial Reintegration Scale Version-2, Participation Assessment with Recombined Tool-Objective, Community Integration Measure, Participation Objective Participation Subjective, Community Integration Questionnaire-2, and Quality of Community Integration Questionnaire. Each instrument was linked to 4-35 unique second-level ICF categories, of which 39-100% related to participation. Instruments addressed 86-100% and 50-100% of the participation categories in the Comprehensive and Brief ICF Core Sets for traumatic brain injury, respectively. Participation measures in traumatic brain injury were compared with the ICF Core Sets for traumatic brain injury. The ICF Core Sets for traumatic brain injury could contribute to the development and selection of participation measures.

Basic difference between brain and computer: integration of asynchronous processes implemented as hardware model of the retina.

PubMed

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

2007-01-01

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

Friends with social benefits: host-microbe interactions as a driver of brain evolution and development?

PubMed Central

Stilling, Roman M.; Bordenstein, Seth R.; Dinan, Timothy G.; Cryan, John F.

2014-01-01

The tight association of the human body with trillions of colonizing microbes that we observe today is the result of a long evolutionary history. Only very recently have we started to understand how this symbiosis also affects brain function and behavior. In this hypothesis and theory article, we propose how host-microbe associations potentially influenced mammalian brain evolution and development. In particular, we explore the integration of human brain development with evolution, symbiosis, and RNA biology, which together represent a “social triangle” that drives human social behavior and cognition. We argue that, in order to understand how inter-kingdom communication can affect brain adaptation and plasticity, it is inevitable to consider epigenetic mechanisms as important mediators of genome-microbiome interactions on an individual as well as a transgenerational time scale. Finally, we unite these interpretations with the hologenome theory of evolution. Taken together, we propose a tighter integration of neuroscience fields with host-associated microbiology by taking an evolutionary perspective. PMID:25401092

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

PubMed

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

2018-01-01

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

Lateralized Feeding Behavior is Associated with Asymmetrical Neuroanatomy and Lateralized Gene Expressions in the Brain in Scale-Eating Cichlid Fish.

PubMed

Lee, Hyuk Je; Schneider, Ralf F; Manousaki, Tereza; Kang, Ji Hyoun; Lein, Etienne; Franchini, Paolo; Meyer, Axel

2017-11-01

Lateralized behavior ("handedness") is unusual, but consistently found across diverse animal lineages, including humans. It is thought to reflect brain anatomical and/or functional asymmetries, but its neuro-molecular mechanisms remain largely unknown. Lake Tanganyika scale-eating cichlid fish, Perissodus microlepis show pronounced asymmetry in their jaw morphology as well as handedness in feeding behavior-biting scales preferentially only from one or the other side of their victims. This makes them an ideal model in which to investigate potential laterality in neuroanatomy and transcription in the brain in relation to behavioral handedness. After determining behavioral handedness in P. microlepis (preferred attack side), we estimated the volume of the hemispheres of brain regions and captured their gene expression profiles. Our analyses revealed that the degree of behavioral handedness is mirrored at the level of neuroanatomical asymmetry, particularly in the tectum opticum. Transcriptome analyses showed that different brain regions (tectum opticum, telencephalon, hypothalamus, and cerebellum) display distinct expression patterns, potentially reflecting their developmental interrelationships. For numerous genes in each brain region, their extent of expression differences between hemispheres was found to be correlated with the degree of behavioral lateralization. Interestingly, the tectum opticum and telencephalon showed divergent biases on the direction of up- or down-regulation of the laterality candidate genes (e.g., grm2) in the hemispheres, highlighting the connection of handedness with gene expression profiles and the different roles of these brain regions. Hence, handedness in predation behavior may be caused by asymmetric size of brain hemispheres and also by lateralized gene expressions in the brain. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

The multiple time scales of sleep dynamics as a challenge for modelling the sleeping brain.

PubMed

Olbrich, Eckehard; Claussen, Jens Christian; Achermann, Peter

2011-10-13

A particular property of the sleeping brain is that it exhibits dynamics on very different time scales ranging from the typical sleep oscillations such as sleep spindles and slow waves that can be observed in electroencephalogram (EEG) segments of several seconds duration over the transitions between the different sleep stages on a time scale of minutes to the dynamical processes involved in sleep regulation with typical time constants in the range of hours. There is an increasing body of work on mathematical and computational models addressing these different dynamics, however, usually considering only processes on a single time scale. In this paper, we review and present a new analysis of the dynamics of human sleep EEG at the different time scales and relate the findings to recent modelling efforts pointing out both the achievements and remaining challenges.

Functional connectivity in the resting brain as biological correlate of the Affective Neuroscience Personality Scales.

PubMed

Deris, Nadja; Montag, Christian; Reuter, Martin; Weber, Bernd; Markett, Sebastian

2017-02-15

According to Jaak Panksepp's Affective Neuroscience Theory and the derived self-report measure, the Affective Neuroscience Personality Scales (ANPS), differences in the responsiveness of primary emotional systems form the basis of human personality. In order to investigate neuronal correlates of personality, the underlying neuronal circuits of the primary emotional systems were analyzed in the present fMRI-study by associating the ANPS to functional connectivity in the resting brain. N=120 healthy participants were invited for the present study. The results were reinvestigated in an independent, smaller sample of N=52 participants. A seed-based whole brain approach was conducted with seed-regions bilaterally in the basolateral and superficial amygdalae. The selection of seed-regions was based on meta-analytic data on affective processing and the Juelich histological atlas. Multiple regression analyses on the functional connectivity maps revealed associations with the SADNESS-scale in both samples. Functional resting-state connectivity between the left basolateral amygdala and a cluster in the postcentral gyrus, and between the right basolateral amygdala and clusters in the superior parietal lobe and subgyral in the parietal lobe was associated with SADNESS. No other ANPS-scale revealed replicable results. The present findings give first insights into the neuronal basis of the SADNESS-scale of the ANPS and support the idea of underlying neuronal circuits. In combination with previous research on genetic associations of the ANPS functional resting-state connectivity is discussed as a possible endophenotype of personality. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2013-01-01

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

Financial hardship after traumatic brain injury: a brief scale for family caregivers.

PubMed

Sabella, Scott A; Andrzejewski, Joshua H; Wallgren, Alexandrea

2018-05-02

Financial hardship is frequently posited as a significant factor influencing family health and adjustment after brain injury, though traditional methods of measurement have shown limited usefulness. The purpose of this study was to adapt and test the utility of a brief scale of financial hardship (BSFH-BI) for use with family caregivers after TBI. The researchers constructed the BSFH-BI using financial well-being items adapted from three survey instruments. The BSFH-BI questionnaire was completed by 136 family caregivers of individuals with TBIs. Scale utility was evaluated through reliability analysis, factor analysis, and correlations with a measure of life satisfaction. The factor analysis revealed that the BSFH-BI had a meaningful two factor structure consisting of items related to (a) meeting essential living expenses and (b) financial changes after the injury. The scale showed high internal consistency (α = 0.92) and moderate negative correlations with life satisfaction (r s  = -0.58). The preliminary findings indicate that the BSFH-BI can be a reliable and valid scale for use with family caregivers after TBI. The authors recommend further study of financial hardship within models of adaptation to TBI using psychometrically validated instruments such as the BSFH-BI.

Integrating Brain and Biomechanical Models—A New Paradigm for Understanding Neuro-muscular Control

PubMed Central

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

2018-01-01

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

Multidimensional quantum entanglement with large-scale integrated optics.

PubMed

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong; Santagati, Raffaele; Skrzypczyk, Paul; Salavrakos, Alexia; Tura, Jordi; Augusiak, Remigiusz; Mančinska, Laura; Bacco, Davide; Bonneau, Damien; Silverstone, Joshua W; Gong, Qihuang; Acín, Antonio; Rottwitt, Karsten; Oxenløwe, Leif K; O'Brien, Jeremy L; Laing, Anthony; Thompson, Mark G

2018-04-20

The ability to control multidimensional quantum systems is central to the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control, and analyze high-dimensional entanglement. A programmable bipartite entangled system is realized with dimensions up to 15 × 15 on a large-scale silicon photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality, and controllability of our multidimensional technology, and further exploit these abilities to demonstrate previously unexplored quantum applications, such as quantum randomness expansion and self-testing on multidimensional states. Our work provides an experimental platform for the development of multidimensional quantum technologies. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Integrated analytical techniques with high sensitivity for studying brain translocation and potential impairment induced by intranasally instilled copper nanoparticles.

PubMed

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

2014-04-07

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

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

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

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

Adaptation of ICT Integration Approach Scale to Kosovo Culture: A Study of Validity and Reliability Analysis

ERIC Educational Resources Information Center

Kervan, Serdan; Tezci, Erdogan

2018-01-01

The aim of this study is to adapt ICT integration approach scale to Kosovo culture, which measures ICT integration approaches of university faculty to teaching and learning process. The scale developed in Turkish has been translated into Albanian to provide linguistic equivalence. The survey was given to a total of 303 instructors [161 (53.1%)…

Large-scale structural alteration of brain in epileptic children with SCN1A mutation.

PubMed

Lee, Yun-Jeong; Yum, Mi-Sun; Kim, Min-Jee; Shim, Woo-Hyun; Yoon, Hee Mang; Yoo, Il Han; Lee, Jiwon; Lim, Byung Chan; Kim, Ki Joong; Ko, Tae-Sung

2017-01-01

Mutations in SCN1A gene encoding the alpha 1 subunit of the voltage gated sodium channel are associated with several epilepsy syndromes including genetic epilepsy with febrile seizures plus (GEFS +) and severe myoclonic epilepsy of infancy (SMEI). However, in most patients with SCN1A mutation, brain imaging has reported normal or non-specific findings including cerebral or cerebellar atrophy. The aim of this study was to investigate differences in brain morphometry in epileptic children with SCN1A mutation compared to healthy control subjects. We obtained cortical morphology (thickness, and surface area) and brain volume (global, subcortical, and regional) measurements using FreeSurfer (version 5.3.0, https://surfer.nmr.mgh.harvard.edu) and compared measurements of children with epilepsy and SCN1A gene mutation ( n  = 21) with those of age and gender matched healthy controls ( n  = 42). Compared to the healthy control group, children with epilepsy and SCN1A gene mutation exhibited smaller total brain, total gray matter and white matter, cerebellar white matter, and subcortical volumes, as well as mean surface area and mean cortical thickness. A regional analysis revealed significantly reduced gray matter volume in the patient group in the bilateral inferior parietal, left lateral orbitofrontal, left precentral, right postcentral, right isthmus cingulate, right middle temporal area with smaller surface area and white matter volume in some of these areas. However, the regional cortical thickness was not significantly different in two groups. This study showed large-scale developmental brain changes in patients with epilepsy and SCN1A gene mutation, which may be associated with the core symptoms of the patients. Further longitudinal MRI studies with larger cohorts are required to confirm the effect of SCN1A gene mutation on structural brain development.

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

PubMed

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

2017-12-01

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

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

PubMed Central

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

2015-01-01

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

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity.

PubMed

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N

2015-01-01

To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen-Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure-function relationships but requires further validation in other populations of CP.

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity

PubMed Central

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S.; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N.

2015-01-01

Aim To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Methods Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen–Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Results Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. Conclusion The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure–function relationships but requires further validation in other populations of CP. PMID:26106533

Exposure to Lipopolysaccharide and/or Unconjugated Bilirubin Impair the Integrity and Function of Brain Microvascular Endothelial Cells

PubMed Central

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

2012-01-01

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

Probing the extracellular diffusion of antibodies in brain using in vivo integrative optical imaging and ex vivo fluorescence imaging.

PubMed

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

2015-01-10

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

Probing the extracellular diffusion of antibodies in brain using in vivo integrative optical imaging and ex vivo fluorescence imaging

PubMed Central

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

2014-01-01

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

Allometric scaling of fatty acyl chains in fowl liver, lung and kidney, but not in brain phospholipids.

PubMed

Szabó, András; Mézes, Miklós; Romvári, Róbert; Fébel, Hedvig

2010-03-01

The phospholipid (PL) fatty acyl chain (FA) composition (mol%) was determined in the kidney, liver, lung and brain of 8 avian species ranging in body mass from 150g (Japanese quail, Coturnix coturnix japonica) to 19kg (turkey, Meleagris gallopavo). In all organs except the brain, docosahexaenoic acid (C22:6 n3, DHA) was found to show a negative allometric scaling (allometric exponent: B=-0.18; -0.20 and -0.24, for kidney, liver and lung, respectively). With minor inter-organ differences, smaller birds had more n3 FAs and longer FA chains in the renal, hepatic and pulmonary PLs. Comparing our results with literature data on avian skeletal muscle, liver mitochondria and kidney microsomes and divergent mammalian tissues, the present findings in the kidney, liver and lung PLs seem to be a part of a general relationship termed "membranes as metabolic pacemakers". Marked negative allometric scaling was found furthermore for the tissue malondialdehyde concentrations in all organs except the brain (B=-0.17; -0.13 and -0.05, respectively). In the liver and kidney a strong correlation was found between the tissue MDA and DHA levels, expressing the role of DHA in shaping the allometric properties of membrane lipids. 2009 Elsevier Inc. All rights reserved.

Polytrauma transitional rehabilitation programs: Comprehensive rehabilitation for community integration after brain injury.

PubMed

Duchnick, Jennifer J; Ropacki, Susan; Yutsis, Maya; Petska, Kelly; Pawlowski, Carey

2015-08-01

When the U.S. Congress passed the Veterans Health Programs Improvement Act of 2004 and the Consolidated Appropriations Act in 2005, Veterans Affairs (VA) traumatic brain injury centers responded by establishing and developing the polytrauma rehabilitation centers and polytrauma transitional rehabilitation programs (PTRPs) across 4 sites in Minneapolis, Minnesota, Palo Alto, California, Richmond, Virginia, and Tampa, Florida, in 2007. The 5th PTRP was opened in 2011 in San Antonio, Texas. This article presents the context of establishing these programs within a VA system, describes aspects of programmatic design, and shares characteristics and outcomes of individuals served by the first 4 national centers. PTRPs provide specialized, interdisciplinary brain injury rehabilitation to active-duty service members and veterans with complex rehabilitation needs. A total of 286 individuals participated in the first 4 PTRPs during the first 3 years. Admission and discharge data were collected as part of routine care, and data review focused on describing the demographic, injury, and neurobehavioral functioning outcomes across 4 sites. Mayo-Portland Adaptability Inventory Abilities, Adjustment, and Participation subscales and total scale T-scores served as primary functioning outcome measures. Mean scores are presented. Statistical analysis found a significant change in total scale T-score from admission to discharge, consistent with improved patient functional ability. Challenges associated with the development and implementation of programs are discussed. Elements of programming may be applicable for other health care organizations that seek to improve rehabilitation care delivery. (c) 2015 APA, all rights reserved).

Brain Volume as an Integrated Marker for the Risk of Death in a Community-Based Sample: Age Gene/Environment Susceptibility--Reykjavik Study.

PubMed

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

2016-01-01

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

Examination of the Mild Brain Injury Atypical Symptom Scale and the Validity-10 Scale to detect symptom exaggeration in US military service members.

PubMed

Lange, Rael T; Brickell, Tracey A; French, Louis M

2015-01-01

The purpose of this study was to examine the clinical utility of two validity scales designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist-Civilian Version (PCL-C); the Mild Brain Injury Atypical Symptoms Scale (mBIAS) and Validity-10 scale. Participants were 63 U.S. military service members (age: M = 31.9 years, SD = 12.5; 90.5% male) who sustained a mild traumatic brain injury (MTBI) and were prospectively enrolled from Walter Reed National Military Medical Center. Participants were divided into two groups based on the validity scales of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF): (a) symptom validity test (SVT)-Fail (n = 24) and (b) SVT-Pass (n = 39). Participants were evaluated on average 19.4 months postinjury (SD = 27.6). Participants in the SVT-Fail group had significantly higher scores (p < .05) on the mBIAS (d = 0.85), Validity-10 (d = 1.89), NSI (d = 2.23), and PCL-C (d = 2.47), and the vast majority of the MMPI-2-RF scales (d = 0.69 to d = 2.47). Sensitivity, specificity, and predictive power values were calculated across the range of mBIAS and Validity-10 scores to determine the optimal cutoff to detect symptom exaggeration. For the mBIAS, a cutoff score of ≥8 was considered optimal, which resulted in low sensitivity (.17), high specificity (1.0), high positive predictive power (1.0), and moderate negative predictive power (.69). For the Validity-10 scale, a cutoff score of ≥13 was considered optimal, which resulted in moderate-high sensitivity (.63), high specificity (.97), and high positive (.93) and negative predictive power (.83). These findings provide strong support for the use of the Validity-10 as a tool to screen for symptom exaggeration when administering the NSI and PCL-C. The mBIAS, however, was not a reliable tool for this purpose and failed to identify the vast majority of people who exaggerated symptoms.

Scan-stratified case-control sampling for modeling blood-brain barrier integrity in multiple sclerosis.

PubMed

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

2015-09-10

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

White matter tract integrity and intelligence in patients with mental retardation and healthy adults.

PubMed

Yu, Chunshui; Li, Jun; Liu, Yong; Qin, Wen; Li, Yonghui; Shu, Ni; Jiang, Tianzi; Li, Kuncheng

2008-05-01

It is well known that brain structures correlate with intelligence but the association between the integrity of brain white matter tracts and intelligence in patients with mental retardation (MR) and healthy adults remains unknown. The aims of this study are to investigate whether the integrity of corpus callosum (CC), cingulum, uncinate fasciculus (UF), optic radiation (OR) and corticospinal tract (CST) are damaged in patients with MR, and to determine the correlations between the integrity of these tracts and full scale intelligence quotient (FSIQ) in both patients and controls. Fifteen MR patients and 79 healthy controls underwent intelligence tests and diffusion tensor imaging examinations. According to the FSIQ, all healthy controls were divided into general intelligence (GI: FSIQ<120; n=42) and high intelligence (HI: FSIQ> or =120; n=37) groups. Intelligence was assessed by Chinese Revised Wechsler Adult Intelligence Scale, and white matter tract integrity was assessed by fractional anisotropy (FA). MR patients showed significantly lower FA than healthy controls in the CC, UF, OR and CST. However, GI subjects only demonstrated lower FA than HI subjects in the right UF. Partial correlation analysis controlling for age and sex showed that FSIQ scores were significantly correlated with the FA of the bilateral UF, genu and truncus of CC, bilateral OR and left CST. While FSIQ scores were only significantly correlated with the FA of the right UF when further controlling for group. This study indicate that MR patients show extensive damage in the integrity of the brain white matter tracts, and the right UF is an important neural basis of human intelligence.

Integration of micro-/nano-/quantum-scale photonic devices: scientific and technological considerations

NASA Astrophysics Data System (ADS)

Lee, El-Hang; Lee, Seung-Gol; O, Beom Hoan; Park, Se Geun

2004-08-01

Scientific and technological issues and considerations regarding the integration of miniaturized microphotonic devices, circuits and systems in micron, submicron, and quantum scale, are presented. First, we examine the issues regarding the miniaturization of photonic devices including the size effect, proximity effect, energy confinement effect, microcavity effect, optical and quantum interference effect, high field effect, nonlinear effect, noise effect, quantum optical effect, and chaotic effect. Secondly, we examine the issues regarding the interconnection including the optical alignment, minimizing the interconnection losses, and maintaining optical modes. Thirdly, we address the issues regarding the two-dimensional or three-dimensional integration either in a hybrid format or in a monolithic format between active devices and passive devices of varying functions. We find that the concept of optical printed circuit board (O-PCB) that we propose is highly attractive as a platform for micro/nano/quantum-scale photonic integration. We examine the technological issues to be addressed in the process of fabrication, characterization, and packaging for actual implementation of the miniaturization, interconnection and integration. Devices that we have used for our study include: mode conversion schemes, micro-ring and micro-racetrack resonator devices, multimode interference devices, lasers, vertical cavity surface emitting microlasers, and their arrays. Future prospects are also discussed.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant

Integrating Phenological, Trait and Environmental Data For Continental Scale Analysis: A Community Approach

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Walls, R.; Guralnick, R. P.; Rosemartin, A.; Deck, J.; Powers, L. A.

2014-12-01

There is a wealth of biodiversity and environmental data that can provide the basis for addressing global scale questions of societal concern. However, our ability to discover, access and integrate these data for use in broader analyses is hampered by the lack of standardized languages and systems. New tools (e.g. ontologies, data standards, integration tools, unique identifiers) are being developed that enable establishment of a framework for linked and open data. Relative to other domains, these tools are nascent in biodiversity and environmental sciences and will require effort to develop, though work can capitalize on lessons learned from previous efforts. Here we discuss needed next steps to provide consistently described and formatted ecological data for immediate application in ecological analysis, focusing on integrating phenology, trait and environmental data to understand local to continental-scale biophysical processes and inform natural resource management practices. As more sources of data become available at finer spatial and temporal resolution, e.g., from national standardized earth observing systems (e.g., NEON, LTER and LTAR Networks, USA NPN), these challenges will become more acute. Here we provide an overview of the standards and ontology development landscape specifically related to phenological and trait data, and identify requirements to overcome current challenges. Second, we outline a workflow for formatting and integrating existing datasets to address key scientific and resource management questions such as: "What traits determine differential phenological responses to changing environmental conditions?" or "What is the role of granularity of observation, and of spatiotemporal scale, in controlling phenological responses to different driving variables?" Third, we discuss methods to semantically annotate datasets to greatly decrease time needed to assemble heterogeneous data for use in ecological analyses on varying spatial scales. We

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

PubMed Central

Moschella, Melissa

2016-01-01

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

Disruption of blood-brain barrier integrity in postmortem alcoholic brain: preclinical evidence of TLR4 involvement from a binge-like drinking model.

PubMed

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

2017-07-01

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

Improving the integration of recreation management with management of other natural resources by applying concepts of scale from ecology.

PubMed

Morse, Wayde C; Hall, Troy E; Kruger, Linda E

2009-03-01

In this article, we examine how issues of scale affect the integration of recreation management with the management of other natural resources on public lands. We present two theories used to address scale issues in ecology and explore how they can improve the two most widely applied recreation-planning frameworks. The theory of patch dynamics and hierarchy theory are applied to the recreation opportunity spectrum (ROS) and the limits of acceptable change (LAC) recreation-planning frameworks. These frameworks have been widely adopted internationally, and improving their ability to integrate with other aspects of natural resource management has significant social and conservation implications. We propose that incorporating ecologic criteria and scale concepts into these recreation-planning frameworks will improve the foundation for integrated land management by resolving issues of incongruent boundaries, mismatched scales, and multiple-scale analysis. Specifically, we argue that whereas the spatially explicit process of the ROS facilitates integrated decision making, its lack of ecologic criteria, broad extent, and large patch size decrease its usefulness for integration at finer scales. The LAC provides explicit considerations for weighing competing values, but measurement of recreation disturbances within an LAC analysis is often done at too fine a grain and at too narrow an extent for integration with other recreation and resource concerns. We suggest that planners should perform analysis at multiple scales when making management decisions that involve trade-offs among competing values. The United States Forest Service is used as an example to discuss how resource-management agencies can improve this integration.

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

PubMed

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

2010-01-01

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

Wafer-Scale Integration of Graphene-based Electronic, Optoelectronic and Electroacoustic Devices

PubMed Central

Tian, He; Yang, Yi; Xie, Dan; Cui, Ya-Long; Mi, Wen-Tian; Zhang, Yuegang; Ren, Tian-Ling

2014-01-01

In virtue of its superior properties, the graphene-based device has enormous potential to be a supplement or an alternative to the conventional silicon-based device in varies applications. However, the functionality of the graphene devices is still limited due to the restriction of the high cost, the low efficiency and the low quality of the graphene growth and patterning techniques. We proposed a simple one-step laser scribing fabrication method to integrate wafer-scale high-performance graphene-based in-plane transistors, photodetectors, and loudspeakers. The in-plane graphene transistors have a large on/off ratio up to 5.34. And the graphene photodetector arrays were achieved with photo responsivity as high as 0.32 A/W. The graphene loudspeakers realize wide-band sound generation from 1 to 50 kHz. These results demonstrated that the laser scribed graphene could be used for wafer-scale integration of a variety of graphene-based electronic, optoelectronic and electroacoustic devices. PMID:24398542

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

PubMed

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

2016-08-01

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

The Overt Behaviour Scale-Self-Report (OBS-SR) for acquired brain injury: exploratory analysis of reliability and validity.

PubMed

Kelly, Glenn; Simpson, Grahame K; Brown, Suzanne; Kremer, Peter; Gillett, Lauren

2017-05-23

The objectives were to test the properties, via a psychometric study, of the Overt Behaviour Scale-Self-Report (OBS-SR), a version of the OBS-Adult Scale developed to provide a client perspective on challenging behaviours after acquired brain injury. Study sample 1 consisted of 37 patients with primary brain tumour (PBT) and a family-member informant. Sample 2 consisted of 34 clients with other acquired brain injury (mixed brain injury, MBI) and a service-provider informant. Participants completed the OBS-SR (at two time points), and the Awareness Questionnaire (AQ) and Mayo Portland Adaptability Inventory-III (MPAI-III) once; informants completed the OBS-Adult and AQ once only. PBT-informant dyads displayed "good" levels of agreement (ICC 2,k  = .74; OBS-SR global index). Although MBI-informant dyads displayed no agreement (ICC 2,k  = .22; OBS-SR global index), the sub-group (17/29) rated by clinicians as having moderate to good levels of awareness displayed "fair" agreement (ICC 2,k  = .58; OBS-SR global index). Convergent/divergent validity was demonstrated by significant correlations between OBS-SR subscales and MPAI-III subscales with behavioural content (coefficients in the range .36 -.61). Scores had good reliability across one week (ICC 2,k  = .69). The OBS-SR took approximately 15 minutes to complete. It was concluded that the OBS-SR demonstrated acceptable reliability and validity, providing a useful resource in understanding clients' perspectives about their behaviour.

Decision making by relatives about brain death organ donation: an integrative review.

PubMed

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

2012-06-27

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

Scaling theory for information networks.

PubMed

Moses, Melanie E; Forrest, Stephanie; Davis, Alan L; Lodder, Mike A; Brown, James H

2008-12-06

Networks distribute energy, materials and information to the components of a variety of natural and human-engineered systems, including organisms, brains, the Internet and microprocessors. Distribution networks enable the integrated and coordinated functioning of these systems, and they also constrain their design. The similar hierarchical branching networks observed in organisms and microprocessors are striking, given that the structure of organisms has evolved via natural selection, while microprocessors are designed by engineers. Metabolic scaling theory (MST) shows that the rate at which networks deliver energy to an organism is proportional to its mass raised to the 3/4 power. We show that computational systems are also characterized by nonlinear network scaling and use MST principles to characterize how information networks scale, focusing on how MST predicts properties of clock distribution networks in microprocessors. The MST equations are modified to account for variation in the size and density of transistors and terminal wires in microprocessors. Based on the scaling of the clock distribution network, we predict a set of trade-offs and performance properties that scale with chip size and the number of transistors. However, there are systematic deviations between power requirements on microprocessors and predictions derived directly from MST. These deviations are addressed by augmenting the model to account for decentralized flow in some microprocessor networks (e.g. in logic networks). More generally, we hypothesize a set of constraints between the size, power and performance of networked information systems including transistors on chips, hosts on the Internet and neurons in the brain.

[Development of the theoretical framework and the item pool of the peri-operative recovery scale for integrative medicine].

PubMed

Su, Bi-ying; Liu, Shao-nan; Li, Xiao-yan

2011-11-01

To study the train of thoughts and procedures for developing the theoretical framework and the item pool of the peri-operative recovery scale for integrative medicine, thus making preparation for the development of this scale and psychometric testing. Under the guidance for Chinese medicine theories and the guidance for developing psychometric scale, the theoretical framework and the item pool of the scale were initially laid out by literature retrieval, and expert consultation, etc. The scale covered the domains of physical function, mental function, activity function, pain, and general assessment. Besides, social function is involved, which is suitable for pre-operative testing and long-term therapeutic efficacy testing after discharge from hospital. Each domain should cover correlated Zang-Fu organs, qi, blood, and the patient-reported outcomes. Totally 122 items were initially covered in the item pool according to theoretical framework of the scale. The peri-operative recovery scale of integrative medicine was the embodiment of the combination of Chinese medicine theories and patient-reported outcome concepts. The scale could reasonably assess the peri-operative recovery outcomes of patients treated by integrative medicine.

Going the distance: spatial scale of athletic experience affects the accuracy of path integration.

PubMed

Smith, Alastair D; Howard, Christina J; Alcock, Niall; Cater, Kirsten

2010-09-01

Evidence suggests that athletically trained individuals are more accurate than untrained individuals in updating their spatial position through idiothetic cues. We assessed whether training at different spatial scales affects the accuracy of path integration. Groups of rugby players (large-scale training) and martial artists (small-scale training) participated in a triangle-completion task: they were led (blindfolded) along two sides of a right-angled triangle and were required to complete the hypotenuse by returning to the origin. The groups did not differ in their assessment of the distance to the origin, but rugby players were more accurate than martial artists in assessing the correct angle to turn (heading), and landed significantly closer to the origin. These data support evidence that distance and heading components can be dissociated. Furthermore, they suggest that the spatial scale at which an individual is trained may affect the accuracy of one component of path integration but not the other.

Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme.

PubMed

Ovaska, Kristian; Laakso, Marko; Haapa-Paananen, Saija; Louhimo, Riku; Chen, Ping; Aittomäki, Viljami; Valo, Erkka; Núñez-Fontarnau, Javier; Rantanen, Ville; Karinen, Sirkku; Nousiainen, Kari; Lahesmaa-Korpinen, Anna-Maria; Miettinen, Minna; Saarinen, Lilli; Kohonen, Pekka; Wu, Jianmin; Westermarck, Jukka; Hautaniemi, Sampsa

2010-09-07

Coordinated efforts to collect large-scale data sets provide a basis for systems level understanding of complex diseases. In order to translate these fragmented and heterogeneous data sets into knowledge and medical benefits, advanced computational methods for data analysis, integration and visualization are needed. We introduce a novel data integration framework, Anduril, for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance, allows sorting of data based on different parameters, and provides direct links to more detailed data on genes, transcripts or genomic regions. Anduril is open-source; all methods and documentation are freely available. We have integrated multidimensional molecular and clinical data from 338 subjects having glioblastoma multiforme, one of the deadliest and most poorly understood cancers, using Anduril. The central objective of our approach is to identify genetic loci and genes that have significant survival effect. Our results suggest several novel genetic alterations linked to glioblastoma multiforme progression and, more specifically, reveal Moesin as a novel glioblastoma multiforme-associated gene that has a strong survival effect and whose depletion in vitro significantly inhibited cell proliferation. All analysis results are available as a comprehensive website. Our results demonstrate that integrated analysis and visualization of multidimensional and heterogeneous data by Anduril enables drawing conclusions on functional consequences of large-scale molecular data. Many of the identified genetic loci and genes having significant survival effect have not been reported earlier in the context of glioblastoma multiforme. Thus, in addition to

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

PubMed Central

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

2005-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

KA-SB: from data integration to large scale reasoning

PubMed Central

Roldán-García, María del Mar; Navas-Delgado, Ismael; Kerzazi, Amine; Chniber, Othmane; Molina-Castro, Joaquín; Aldana-Montes, José F

2009-01-01

Background The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data. Methods KA-SB is a querying and analysis system for final users based on combining a data integration solution with a reasoner. Thus, the tool has been created with a process divided into two steps: 1) KOMF, the Khaos Ontology-based Mediator Framework, is used to retrieve information from heterogeneous and distributed databases; 2) the integrated information is crystallized in a (persistent and high performance) reasoner (DBOWL). This information could be further analyzed later (by means of querying and reasoning). Results In this paper we present a novel system that combines the use of a mediation system with the reasoning capabilities of a large scale reasoner to provide a way of finding new knowledge and of analyzing the integrated information from different databases, which is retrieved as a set of ontology instances. This tool uses a graphical query interface to build user queries easily, which shows a graphical representation of the ontology and allows users o build queries by clicking on the ontology concepts. Conclusion These kinds of systems (based on KOMF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a process for creating persistent and scalable knowledgebases from sets of OWL instances obtained by integrating heterogeneous data sources with KOMF. This process has been applied to develop a demo tool , which uses the BioPax Level 3 ontology as the integration schema, and integrates UNIPROT, KEGG, CHEBI, BRENDA and SABIORK databases. PMID:19796402

Dimensions of personality disturbance after focal brain damage: investigation with the Iowa Scales of Personality Change.

PubMed

Barrash, Joseph; Asp, Erik; Markon, Kristian; Manzel, Kenneth; Anderson, Steven W; Tranel, Daniel

2011-10-01

This study employed a multistep, rational-empirical approach to identify dimensions of personality disturbance in brain-damaged individuals: (a) Five dimensions were hypothesized based on empirical literature and conceptual grounds; (b) principal components analysis was performed on the Iowa Scales of Personality Change (ISPC) to determine the pattern of covariance among 30 personality characteristics; (c) when discrepancies existed between principal components analysis results and conceptually based dimensions, empirical findings and clinical considerations were weighed to determine assignment of ISPC scales to dimensions; (d) the fit of data to the refined dimensions was assessed by examination of intercorrelations; (e) differential predictions concerning the relationship of dimensions to ventromedial prefrontal cortex (vmPFC) damage were tested. This process resulted in the specification of five dimensions: Disturbed Social Behavior, Executive/Decision-Making Deficits, Diminished Motivation/Hypo-Emotionality, Irascibility, and Distress. In accord with predictions, the 28 participants with vmPFC lesions, compared to 96 participants with focal lesions elsewhere in the brain, had significantly more Disturbed Social Behavior and Executive/Decision-Making Deficits and tended to have more Diminished Motivation/Hypo-Emotionality. Irascibility was not significantly higher among the vmPFC group, and the groups had very similar levels of Distress. The findings indicate that conceptually distinctive dimensions with differential relationships to vmPFC can be derived from the Iowa Scales of Personality Change.

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

PubMed Central

2013-01-01

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

Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

PubMed Central

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

2014-01-01

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

Scales

ScienceCinema

Murray Gibson

2017-12-09

Musical scales involve notes that, sounded simultaneously (chords), sound good together. The result is the left brain meeting the right brain — a Pythagorean interval of overlapping notes. This synergy would suggest less difference between the working of the right brain and the left brain than common wisdom would dictate. The pleasing sound of harmony comes when two notes share a common harmonic, meaning that their frequencies are in simple integer ratios, such as 3/2 (G/C) or 5/4 (E/C).

Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder.

PubMed

Cao, Miao; Shu, Ni; Cao, Qingjiu; Wang, Yufeng; He, Yong

2014-12-01

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopment disorders in childhood. Clinically, the core symptoms of this disorder include inattention, hyperactivity, and impulsivity. Previous studies have documented that these behavior deficits in ADHD children are associated with not only regional brain abnormalities but also changes in functional and structural connectivity among regions. In the past several years, our understanding of how ADHD affects the brain's connectivity has been greatly advanced by mapping topological alterations of large-scale brain networks (i.e., connectomes) using noninvasive neurophysiological and neuroimaging techniques (e.g., electroencephalograph, functional MRI, and diffusion MRI) in combination with graph theoretical approaches. In this review, we summarize the recent progresses of functional and structural brain connectomics in ADHD, focusing on graphic analysis of large-scale brain systems. Convergent evidence suggests that children with ADHD had abnormal small-world properties in both functional and structural brain networks characterized by higher local clustering and lower global integrity, suggesting a disorder-related shift of network topology toward regular configurations. Moreover, ADHD children showed the redistribution of regional nodes and connectivity involving the default-mode, attention, and sensorimotor systems. Importantly, these ADHD-associated alterations significantly correlated with behavior disturbances (e.g., inattention and hyperactivity/impulsivity symptoms) and exhibited differential patterns between clinical subtypes. Together, these connectome-based studies highlight brain network dysfunction in ADHD, thus opening up a new window into our understanding of the pathophysiological mechanisms of this disorder. These works might also have important implications on the development of imaging-based biomarkers for clinical diagnosis and treatment evaluation in ADHD.

Investigating the effects of streamline-based fiber tractography on matrix scaling in brain connective network.

PubMed

Jan, Hengtai; Chao, Yi-Ping; Cho, Kuan-Hung; Kuo, Li-Wei

2013-01-01

Investigating the brain connective network using the modern graph theory has been widely applied in cognitive and clinical neuroscience research. In this study, we aimed to investigate the effects of streamline-based fiber tractography on the change of network properties and established a systematic framework to understand how an adequate network matrix scaling can be determined. The network properties, including degree, efficiency and betweenness centrality, show similar tendency in both left and right hemispheres. By employing the curve-fitting process with exponential law and measuring the residuals, the association between changes of network properties and threshold of track numbers is found and an adequate range of investigating the lateralization of brain network is suggested. The proposed approach can be further applied in clinical applications to improve the diagnostic sensitivity using network analysis with graph theory.

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

PubMed

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

2014-02-01

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

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

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

2013-01-01

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

Simultaneous 11C-Methionine Positron Emission Tomography/Magnetic Resonance Imaging of Suspected Primary Brain Tumors

PubMed Central

Deuschl, Cornelius; Goericke, Sophia; Grueneisen, Johannes; Sawicki, Lino Morris; Goebel, Juliane; El Hindy, Nicolai; Wrede, Karsten; Binse, Ina; Poeppel, Thorsten; Quick, Harald; Forsting, Michael; Hense, Joerg; Umutlu, Lale; Schlamann, Marc

2016-01-01

Introduction The objective of this study was to assess the diagnostic value of integrated 11C- methionine PET/MRI for suspected primary brain tumors, in comparison to MRI alone. Material and Methods Forty-eight consecutive patients with suspected primary brain tumor were prospectively enrolled for an integrated 11C-methionine PET/MRI. Two neuro-radiologists separately evaluated the MRI alone and the integrated PET/MRI data sets regarding most likely diagnosis and diagnostic confidence on a 5-point scale. Reference standard was histopathology or follow-up imaging. Results Fifty-one suspicious lesions were detected: 16 high-grade glioma and 25 low-grade glioma. Ten non-malignant cerebral lesions were described by the reference standard. MRI alone and integrated PET/MRI each correctly classified 42 of the 51 lesions (82.4%) as neoplastic lesions (WHO grade II, III and IV) or non-malignant lesions (infectious and neoplastic lesions). Diagnostic confidence for all lesions, low-grade astrocytoma and high-grade astrocytoma (3.7 vs. 4.2, 3,1 vs. 3.8, 4.0 vs. 4,7) were significantly (p < 0.05) better with integrated PET/MRI than in MRI alone. Conclusions The present study demonstrates the high potential of integrated 11C-methionine-PET/MRI for the assessment of suspected primary brain tumors. Although integrated methionine PET/MRI does not lead to an improvement of correct diagnoses, diagnostic confidence is significantly improved. PMID:27907162

Individual differences and time-varying features of modular brain architecture.

PubMed

Liao, Xuhong; Cao, Miao; Xia, Mingrui; He, Yong

2017-05-15

Recent studies have suggested that human brain functional networks are topologically organized into functionally specialized but inter-connected modules to facilitate efficient information processing and highly flexible cognitive function. However, these studies have mainly focused on group-level network modularity analyses using "static" functional connectivity approaches. How these extraordinary modular brain structures vary across individuals and spontaneously reconfigure over time remain largely unknown. Here, we employed multiband resting-state functional MRI data (N=105) from the Human Connectome Project and a graph-based modularity analysis to systematically investigate individual variability and dynamic properties in modular brain networks. We showed that the modular structures of brain networks dramatically vary across individuals, with higher modular variability primarily in the association cortex (e.g., fronto-parietal and attention systems) and lower variability in the primary systems. Moreover, brain regions spontaneously changed their module affiliations on a temporal scale of seconds, which cannot be simply attributable to head motion and sampling error. Interestingly, the spatial pattern of intra-subject dynamic modular variability largely overlapped with that of inter-subject modular variability, both of which were highly reproducible across repeated scanning sessions. Finally, the regions with remarkable individual/temporal modular variability were closely associated with network connectors and the number of cognitive components, suggesting a potential contribution to information integration and flexible cognitive function. Collectively, our findings highlight individual modular variability and the notable dynamic characteristics in large-scale brain networks, which enhance our understanding of the neural substrates underlying individual differences in a variety of cognition and behaviors. Copyright © 2017 Elsevier Inc. All rights reserved.

[Psychotherapy of patients with brain lesions: an integrative model based on neuropsychological and psychodynamic perspectives].

PubMed

Ouss-Ryngaert, Lisa

2010-12-01

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

A Multi-Scale Integrated Approach to Representing Watershed Systems: Significance and Challenges

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Katopodes, N.

2013-12-01

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a

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

PubMed

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

2016-07-01

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

Chip-scale integrated optical interconnects: a key enabler for future high-performance computing

NASA Astrophysics Data System (ADS)

Haney, Michael; Nair, Rohit; Gu, Tian

2012-01-01

High Performance Computing (HPC) systems are putting ever-increasing demands on the throughput efficiency of their interconnection fabrics. In this paper, the limits of conventional metal trace-based inter-chip interconnect fabrics are examined in the context of state-of-the-art HPC systems, which currently operate near the 1 GFLOPS/W level. The analysis suggests that conventional metal trace interconnects will limit performance to approximately 6 GFLOPS/W in larger HPC systems that require many computer chips to be interconnected in parallel processing architectures. As the HPC communications bottlenecks push closer to the processing chips, integrated Optical Interconnect (OI) technology may provide the ultra-high bandwidths needed at the inter- and intra-chip levels. With inter-chip photonic link energies projected to be less than 1 pJ/bit, integrated OI is projected to enable HPC architecture scaling to the 50 GFLOPS/W level and beyond - providing a path to Peta-FLOPS-level HPC within a single rack, and potentially even Exa-FLOPSlevel HPC for large systems. A new hybrid integrated chip-scale OI approach is described and evaluated. The concept integrates a high-density polymer waveguide fabric directly on top of a multiple quantum well (MQW) modulator array that is area-bonded to the Silicon computing chip. Grayscale lithography is used to fabricate 5 μm x 5 μm polymer waveguides and associated novel small-footprint total internal reflection-based vertical input/output couplers directly onto a layer containing an array of GaAs MQW devices configured to be either absorption modulators or photodetectors. An external continuous wave optical "power supply" is coupled into the waveguide links. Contrast ratios were measured using a test rider chip in place of a Silicon processing chip. The results suggest that sub-pJ/b chip-scale communication is achievable with this concept. When integrated into high-density integrated optical interconnect fabrics, it could provide

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

PubMed

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

2006-01-01

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

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

PubMed

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

2015-03-01

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

LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

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

2014-01-01

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

Brain anatomical networks in early human brain development.

PubMed

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

2011-02-01

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

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

PubMed

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

2018-05-17

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

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

PubMed

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

2011-06-01

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

Brain noise is task dependent and region specific.

PubMed

Misić, Bratislav; Mills, Travis; Taylor, Margot J; McIntosh, Anthony R

2010-11-01

The emerging organization of anatomical and functional connections during human brain development is thought to facilitate global integration of information. Recent empirical and computational studies have shown that this enhanced capacity for information processing enables a diversified dynamic repertoire that manifests in neural activity as irregularity and noise. However, transient functional networks unfold over multiple time, scales and the embedding of a particular region depends not only on development, but also on the manner in which sensory and cognitive systems are engaged. Here we show that noise is a facet of neural activity that is also sensitive to the task context and is highly region specific. Children (6-16 yr) and adults (20-41 yr) performed a one-back face recognition task with inverted and upright faces. Neuromagnetic activity was estimated at several hundred sources in the brain by applying a beamforming technique to the magnetoencephalogram (MEG). During development, neural activity became more variable across the whole brain, with most robust increases in medial parietal regions, such as the precuneus and posterior cingulate cortex. For young children and adults, activity evoked by upright faces was more variable and noisy compared with inverted faces, and this effect was reliable only in the right fusiform gyrus. These results are consistent with the notion that upright faces engender a variety of integrative neural computations, such as the relations among facial features and their holistic constitution. This study shows that transient changes in functional integration modulated by task demand are evident in the variability of regional neural activity.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

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

2018-08-01

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

The Exercising Brain: Changes in Functional Connectivity Induced by an Integrated Multimodal Cognitive and Whole-Body Coordination Training

PubMed Central

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

2016-01-01

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

Plasticity of brain wave network interactions and evolution across physiologic states

PubMed Central

Liu, Kang K. L.; Bartsch, Ronny P.; Lin, Aijing; Mantegna, Rosario N.; Ivanov, Plamen Ch.

2015-01-01

Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of

Silencing microRNA-143 protects the integrity of the blood-brain barrier: implications for methamphetamine abuse

PubMed Central

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

2016-01-01

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

Multiple-scale neuroendocrine signals connect brain and pituitary hormone rhythms

PubMed Central

Romanò, Nicola; Guillou, Anne; Martin, Agnès O; Mollard, Patrice

2017-01-01

Small assemblies of hypothalamic “parvocellular” neurons release their neuroendocrine signals at the median eminence (ME) to control long-lasting pituitary hormone rhythms essential for homeostasis. How such rapid hypothalamic neurotransmission leads to slowly evolving hormonal signals remains unknown. Here, we show that the temporal organization of dopamine (DA) release events in freely behaving animals relies on a set of characteristic features that are adapted to the dynamic dopaminergic control of pituitary prolactin secretion, a key reproductive hormone. First, locally generated DA release signals are organized over more than four orders of magnitude (0.001 Hz–10 Hz). Second, these DA events are finely tuned within and between frequency domains as building blocks that recur over days to weeks. Third, an integration time window is detected across the ME and consists of high-frequency DA discharges that are coordinated within the minutes range. Thus, a hierarchical combination of time-scaled neuroendocrine signals displays local–global integration to connect brain–pituitary rhythms and pace hormone secretion. PMID:28193889

Do anesthetics harm the developing human brain? An integrative analysis of animal and human studies.

PubMed

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

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

The suppression of scale-free fMRI brain dynamics across three different sources of effort: aging, task novelty and task difficulty.

PubMed

Churchill, Nathan W; Spring, Robyn; Grady, Cheryl; Cimprich, Bernadine; Askren, Mary K; Reuter-Lorenz, Patricia A; Jung, Mi Sook; Peltier, Scott; Strother, Stephen C; Berman, Marc G

2016-08-08

There is growing evidence that fluctuations in brain activity may exhibit scale-free ("fractal") dynamics. Scale-free signals follow a spectral-power curve of the form P(f ) ∝ f(-β), where spectral power decreases in a power-law fashion with increasing frequency. In this study, we demonstrated that fractal scaling of BOLD fMRI signal is consistently suppressed for different sources of cognitive effort. Decreases in the Hurst exponent (H), which quantifies scale-free signal, was related to three different sources of cognitive effort/task engagement: 1) task difficulty, 2) task novelty, and 3) aging effects. These results were consistently observed across multiple datasets and task paradigms. We also demonstrated that estimates of H are robust across a range of time-window sizes. H was also compared to alternative metrics of BOLD variability (SDBOLD) and global connectivity (Gconn), with effort-related decreases in H producing similar decreases in SDBOLD and Gconn. These results indicate a potential global brain phenomenon that unites research from different fields and indicates that fractal scaling may be a highly sensitive metric for indexing cognitive effort/task engagement.

The suppression of scale-free fMRI brain dynamics across three different sources of effort: aging, task novelty and task difficulty

PubMed Central

Churchill, Nathan W.; Spring, Robyn; Grady, Cheryl; Cimprich, Bernadine; Askren, Mary K.; Reuter-Lorenz, Patricia A.; Jung, Mi Sook; Peltier, Scott; Strother, Stephen C.; Berman, Marc G.

2016-01-01

There is growing evidence that fluctuations in brain activity may exhibit scale-free (“fractal”) dynamics. Scale-free signals follow a spectral-power curve of the form P(f ) ∝ f−β, where spectral power decreases in a power-law fashion with increasing frequency. In this study, we demonstrated that fractal scaling of BOLD fMRI signal is consistently suppressed for different sources of cognitive effort. Decreases in the Hurst exponent (H), which quantifies scale-free signal, was related to three different sources of cognitive effort/task engagement: 1) task difficulty, 2) task novelty, and 3) aging effects. These results were consistently observed across multiple datasets and task paradigms. We also demonstrated that estimates of H are robust across a range of time-window sizes. H was also compared to alternative metrics of BOLD variability (SDBOLD) and global connectivity (Gconn), with effort-related decreases in H producing similar decreases in SDBOLD and Gconn. These results indicate a potential global brain phenomenon that unites research from different fields and indicates that fractal scaling may be a highly sensitive metric for indexing cognitive effort/task engagement. PMID:27498696

Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis.

PubMed

Goch, Caspar J; Stieltjes, Bram; Henze, Romy; Hering, Jan; Poustka, Luise; Meinzer, Hans-Peter; Maier-Hein, Klaus H

2014-05-01

Diagnosis of autism spectrum disorders (ASD) is difficult, as symptoms vary greatly and are difficult to quantify objectively. Recent work has focused on the assessment of non-invasive diffusion tensor imaging-based biomarkers that reflect the microstructural characteristics of neuronal pathways in the brain. While tractography-based approaches typically analyze specific structures of interest, a graph-based large-scale network analysis of the connectome can yield comprehensive measures of larger-scale architectural patterns in the brain. Commonly applied global network indices, however, do not provide any specificity with respect to functional areas or anatomical structures. Aim of this work was to assess the concept of network centrality as a tool to perform locally specific analysis without disregarding the global network architecture and compare it to other popular network indices. We create connectome networks from fiber tractographies and parcellations of the human brain and compute global network indices as well as local indices for Wernicke's Area, Broca's Area and the Motor Cortex. Our approach was evaluated on 18 children suffering from ASD and 18 typically developed controls using magnetic resonance imaging-based cortical parcellations in combination with diffusion tensor imaging tractography. We show that the network centrality of Wernicke's area is significantly (p<0.001) reduced in ASD, while the motor cortex, which was used as a control region, did not show significant alterations. This could reflect the reduced capacity for comprehension of language in ASD. The betweenness centrality could potentially be an important metric in the development of future diagnostic tools in the clinical context of ASD diagnosis. Our results further demonstrate the applicability of large-scale network analysis tools in the domain of region-specific analysis with a potential application in many different psychological disorders.

GIGGLE: a search engine for large-scale integrated genome analysis.

PubMed

Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

2018-02-01

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

Poincaré-Treshchev Mechanism in Multi-scale, Nearly Integrable Hamiltonian Systems

NASA Astrophysics Data System (ADS)

Xu, Lu; Li, Yong; Yi, Yingfei

2018-02-01

This paper is a continuation to our work (Xu et al. in Ann Henri Poincaré 18(1):53-83, 2017) concerning the persistence of lower-dimensional tori on resonant surfaces of a multi-scale, nearly integrable Hamiltonian system. This type of systems, being properly degenerate, arise naturally in planar and spatial lunar problems of celestial mechanics for which the persistence problem ties closely to the stability of the systems. For such a system, under certain non-degenerate conditions of Rüssmann type, the majority persistence of non-resonant tori and the existence of a nearly full measure set of Poincaré non-degenerate, lower-dimensional, quasi-periodic invariant tori on a resonant surface corresponding to the highest order of scale is proved in Han et al. (Ann Henri Poincaré 10(8):1419-1436, 2010) and Xu et al. (2017), respectively. In this work, we consider a resonant surface corresponding to any intermediate order of scale and show the existence of a nearly full measure set of Poincaré non-degenerate, lower-dimensional, quasi-periodic invariant tori on the resonant surface. The proof is based on a normal form reduction which consists of a finite step of KAM iterations in pushing the non-integrable perturbation to a sufficiently high order and the splitting of resonant tori on the resonant surface according to the Poincaré-Treshchev mechanism.

Development and psychometric properties of an informant assessment scale of theory of mind for adults with traumatic brain injury.

PubMed

Zhang, Dengke; Pang, Yanxia; Cai, Weixiong; Fazio, Rachel L; Ge, Jianrong; Su, Qiaorong; Xu, Shuiqin; Pan, Yinan; Chen, Sanmei; Zhang, Hongwei

2016-08-01

Impairment of theory of mind (ToM) is a common phenomenon following traumatic brain injury (TBI) that has clear effects on patients' social functioning. A growing body of research has focused on this area, and several methods have been developed to assess ToM deficiency. Although an informant assessment scale would be useful for examining individuals with TBI, very few studies have adopted this approach. The purpose of the present study was to develop an informant assessment scale of ToM for adults with traumatic brain injury (IASToM-aTBI) and to test its reliability and validity with 196 adults with TBI and 80 normal adults. A 44-item scale was developed following a literature review, interviews with patient informants, consultations with experts, item analysis, and exploratory factor analysis (EFA). The following three common factors were extracted: social interaction, understanding of beliefs, and understanding of emotions. The psychometric analyses indicate that the scale has good internal consistency reliability, split-half reliability, test-retest reliability, inter-rater reliability, structural validity, discriminate validity and criterion validity. These results provide preliminary evidence that supports the reliability and validity of the IASToM-aTBI as a ToM assessment tool for adults with TBI.

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

Consciousness, cognition and brain networks: New perspectives.

PubMed

Aldana, E M; Valverde, J L; Fábregas, N

2016-10-01

A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks. Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

Low-Activity Waste Pretreatment System Additional Engineering-Scale Integrated Test Report

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

Landon, Matt R.; Wilson, Robert A.

Washington River Protections Solutions, LLC’s (WRPS) Low Activity Waste Pretreatment System (LAWPS) Project provides for the early production of immobilized low-activity waste (ILAW) by feeding LAW directly from Tank Farms to the Waste Treatment and Immobilization Plant (WTP) LAW Facility, bypassing the WTP Pretreatment Facility. Prior to the transfer of feed to the WTP LAW Vitrification Facility, tank supernatant waste will be pretreated in the LAWPS to meet the WTP LAW waste acceptance criteria (WAC). Full-scale and engineering-scale testing of critical technology elements, as part of the technology maturation process, are components of the overall LAWPS Project. WRPS awarded themore » engineering-scale integrated testing scope to AECOM via WRPS Subcontract 58349. This report is deliverable MSR-008 of the subcontract.« less

Transforming Research and Clinical Knowledge in Traumatic Brain Injury

DTIC Science & Technology

2016-12-01

Szuflita, N., Orman, J., and Schwab, K. (2010). Advancing integrated research in psychological health and traumatic brain injury: common data ele- ments...Szuflita N, Orman J, et al. Advancing Integrated Research in Psychological Health and Traumatic Brain Injury: Common Data Elements. Arch Phys Med Rehabil...R, Gleason T, et al. Advancing integrated research in psychological health and traumatic brain injury: common data elements. Arch Phys Med Rehabil

Potentiated antibodies to mu-opiate receptors: effect on integrative activity of the brain.

PubMed

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

2003-01-01

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

Critical perspectives on causality and inference in brain networks: Allusions, illusions, solutions?. Comment on: "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

NASA Astrophysics Data System (ADS)

Diwadkar, Vaibhav A.

2015-12-01

The human brain is an impossibly difficult cartographic landscape to map out. Within it's convoluted and labyrinthine structure is folded a million years of phylogeny, somehow expressed in the ontogeny of the specific organism; an ontogeny that conceals idiosyncratic effects of countless genes, and then the (perhaps) countably infinite effects of processes of the organism's lifespan subsequently resulting in remarkable heterogeneity [1,2]. The physical brain itself is therefore a nearly un-decodable ;time machine; motivating more questions than frameworks for answering those questions: Why has evolution endowed it with the general structure that is possesses [3]; Is there regularity in macroscopic metrics of structure across species [4]; What are the most meaningful structural units in the brain: molecules, neurons, cortical columns or cortical maps [5]? Remarkably, understanding the intricacies of structure is perhaps not even the most difficult aspect of understanding the human brain. In fact, and as recently argued, a central issue lies in resolving the dialectic between structure and function: how does dynamic function arises from static (at least at the time scales at which human brain function is experimentally studied) brain structures [6]? In other words, if the mind is the brain ;in action;, how does it arise?

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

PubMed Central

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

2013-01-01

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

Whole brain diffeomorphic metric mapping via integration of sulcal and gyral curves, cortical surfaces, and images

PubMed Central

Du, Jia; Younes, Laurent; Qiu, Anqi

2011-01-01

This paper introduces a novel large deformation diffeomorphic metric mapping algorithm for whole brain registration where sulcal and gyral curves, cortical surfaces, and intensity images are simultaneously carried from one subject to another through a flow of diffeomorphisms. To the best of our knowledge, this is the first time that the diffeomorphic metric from one brain to another is derived in a shape space of intensity images and point sets (such as curves and surfaces) in a unified manner. We describe the Euler–Lagrange equation associated with this algorithm with respect to momentum, a linear transformation of the velocity vector field of the diffeomorphic flow. The numerical implementation for solving this variational problem, which involves large-scale kernel convolution in an irregular grid, is made feasible by introducing a class of computationally friendly kernels. We apply this algorithm to align magnetic resonance brain data. Our whole brain mapping results show that our algorithm outperforms the image-based LDDMM algorithm in terms of the mapping accuracy of gyral/sulcal curves, sulcal regions, and cortical and subcortical segmentation. Moreover, our algorithm provides better whole brain alignment than combined volumetric and surface registration (Postelnicu et al., 2009) and hierarchical attribute matching mechanism for elastic registration (HAMMER) (Shen and Davatzikos, 2002) in terms of cortical and subcortical volume segmentation. PMID:21281722

Practical considerations for transitioning early childhood interventions to scale: lessons from the Saving Brains portfolio.

PubMed

Radner, James M; Ferrer, Marvin J S; McMahon, Dominique; Shankar, Anuraj H; Silver, Karlee L

2018-05-01

Small pilot studies of young children have frequently shown promise, but very few have been successfully scaled to the regional or national levels. How can we ensure that these promising approaches move from a suite of pilots to full-scale implementation that can deliver sustainable impact for hundreds of millions of children? To elucidate concrete lessons learned and suggestions on accelerating the transition to impact at scale, we reviewed the Saving Brains portfolio to better understand three points: (1) the extent to which useful signals of impact could be extracted from data at the seed phase, (2) the ways in which innovators (project leaders) were approaching human resource challenges critical for scaling, and (3) the multisector diversity of the portfolio and the way innovators entered partnerships. The findings suggest key considerations for transitioning early childhood development interventions to scale and sustainability: strong entrepreneurial leadership, rigorous measurement and active use of data in support of adaptive learning, and champions acting at subnational levels. Together, these can enable flexible, iterative learning that can make the scaling process an opportunity to increase the level of benefit each child receives from an intervention. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of The New York Academy of Sciences.

Reduced hemispheric asymmetry of brain anatomical networks in attention deficit hyperactivity disorder.

PubMed

Li, Dandan; Li, Ting; Niu, Yan; Xiang, Jie; Cao, Rui; Liu, Bo; Zhang, Hui; Wang, Bin

2018-05-11

Despite many studies reporting a variety of alterations in brain networks in patients with attention deficit hyperactivity disorder (ADHD), alterations in hemispheric anatomical networks are still unclear. In this study, we investigated topology alterations in hemispheric white matter in patients with ADHD and the relationship between these alterations and clinical features of the illness. Weighted hemispheric brain anatomical networks were first constructed for each of 40 right-handed patients with ADHD and 53 matched normal controls. Then, graph theoretical approaches were utilized to compute hemispheric topological properties. The small-world property was preserved in the hemispheric network. Furthermore, a significant group-by-hemisphere interaction was revealed in global efficiency, local efficiency and characteristic path length, attributed to the significantly reduced hemispheric asymmetry of global and local integration in patients with ADHD compared with normal controls. Specifically, reduced asymmetric regional efficiency was found in three regions. Finally, we found that the abnormal asymmetry of hemispheric brain anatomical network topology and regional efficiency were both associated with clinical features (the Adult ADHD Self-Report Scale and Wechsler Adult Intelligence Scale) in patients. Our findings provide new insights into the lateralized nature of hemispheric dysconnectivity and highlight the potential for using brain network measures of hemispheric asymmetry as neural biomarkers for ADHD and its clinical features.

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

PubMed

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

2016-05-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2015-01-01

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