Neural Representation of Subjective Sexual Arousal in Men and Women.

PubMed

Parada, Mayte; Gérard, Marina; Larcher, Kevin; Dagher, Alain; Binik, Yitzchak M

2016-10-01

Studies investigating brain indices of sexual arousal have begun to elucidate the brain's role in processing subjective arousal; however, most research has focused on men, used discrete ratings of subjective arousal, and used stimuli too short to induce significant arousal in women. To examine brain regions modulated by changes in subjective sexual arousal (SSA) rating intensity in men and women. Two groups (20 men, 20 women) viewed movie clips (erotic or humorous) while continuously evaluating changes in their SSA using a Likert-like scale (0 = not aroused, 10 = most aroused) and answering discrete questions about liking the movies and wanting sexual stimulation. Brain activity was measured using functional magnetic resonance imaging. Blood oxygen level-dependent responses and continuous and discrete measurements of sexual arousal. Erotic movies induced significant SSA in men and women. No sex difference in mean SSA was found in response to the erotic movies on continuous or discrete measurements. Several brain regions were correlated with changes in SSA. Parametric modulation with rating intensity showed a specific group of regions within the parietal lobe that showed significant differences in activity among low, medium, and high SSA. Multiple regions were concordant with changes in SSA; however, a subset of regions in men and women was modulated by SSA intensity, a subset previously linked to attentional processes, monitoring of internal body representation, and processing of sensory information from the genitals. This study highlights that similar brain regions are activated during subjective assessment of sexual arousal in men and women. The data further highlight the fact that SSA is a complex phenomenon made up of multiple interoceptive and attentional processes. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Language, music, syntax and the brain.

PubMed

Patel, Aniruddh D

2003-07-01

The comparative study of music and language is drawing an increasing amount of research interest. Like language, music is a human universal involving perceptually discrete elements organized into hierarchically structured sequences. Music and language can thus serve as foils for each other in the study of brain mechanisms underlying complex sound processing, and comparative research can provide novel insights into the functional and neural architecture of both domains. This review focuses on syntax, using recent neuroimaging data and cognitive theory to propose a specific point of convergence between syntactic processing in language and music. This leads to testable predictions, including the prediction that that syntactic comprehension problems in Broca's aphasia are not selective to language but influence music perception as well.

The organizing actions of adolescent gonadal steroid hormones on brain and behavioral development.

PubMed

Schulz, Kalynn M; Sisk, Cheryl L

2016-11-01

Adolescence is a developmental period characterized by dramatic changes in cognition, risk-taking and social behavior. Although gonadal steroid hormones are well-known mediators of these behaviors in adulthood, the role gonadal steroid hormones play in shaping the adolescent brain and behavioral development has only come to light in recent years. Here we discuss the sex-specific impact of gonadal steroid hormones on the developing adolescent brain. Indeed, the effects of gonadal steroid hormones during adolescence on brain structure and behavioral outcomes differs markedly between the sexes. Research findings suggest that adolescence, like the perinatal period, is a sensitive period for the sex-specific effects of gonadal steroid hormones on brain and behavioral development. Furthermore, evidence from studies on male sexual behavior suggests that adolescence is part of a protracted postnatal sensitive period that begins perinatally and ends following adolescence. As such, the perinatal and peripubertal periods of brain and behavioral organization likely do not represent two discrete sensitive periods, but instead are the consequence of normative developmental timing of gonadal hormone secretions in males and females. Copyright © 2016 Elsevier Ltd. All rights reserved.

The organizing actions of adolescent gonadal steroid hormones on brain and behavioral development

PubMed Central

Schulz, Kalynn M.; Sisk, Cheryl L.

2016-01-01

Adolescence is a developmental period characterized by dramatic changes in cognition, risk-taking and social behavior. Although gonadal steroid hormones are well-known mediators of these behaviors in adulthood, the role gonadal steroid hormones play in shaping the adolescent brain and behavioral development has only come to light in recent years. Here we discuss the sex-specific impact of gonadal steroid hormones on the developing adolescent brain. Indeed, the effects of gonadal steroid hormones during adolescence on brain structure and behavioral outcomes differs markedly between the sexes. Research findings suggest that adolescence, like the perinatal period, is a sensitive period for the sex-specific effects of gonadal steroid hormones on brain and behavioral development. Furthermore, evidence from studies on male sexual behavior suggests that adolescence is part of a protracted postnatal sensitive period that begins perinatally and ends following adolescence. As such, the perinatal and peripubertal periods of brain and behavioral organization likely do not represent two discrete sensitive periods, but instead are the consequence of normative developmental timing of gonadal hormone secretions in males and females. PMID:27497718

Direct electrical stimulation as an input gate into brain functional networks: principles, advantages and limitations.

PubMed

Mandonnet, Emmanuel; Winkler, Peter A; Duffau, Hugues

2010-02-01

While the fundamental and clinical contribution of direct electrical stimulation (DES) of the brain is now well acknowledged, its advantages and limitations have not been re-evaluated for a long time. Here, we critically review exactly what DES can tell us about cerebral function. First, we show that DES is highly sensitive for detecting the cortical and axonal eloquent structures. Moreover, DES also provides a unique opportunity to study brain connectivity, since each area responsive to stimulation is in fact an input gate into a large-scale network rather than an isolated discrete functional site. DES, however, also has a limitation: its specificity is suboptimal. Indeed, DES may lead to interpretations that a structure is crucial because of the induction of a transient functional response when stimulated, whereas (1) this effect is caused by the backward spreading of the electro-stimulation along the network to an essential area and/or (2) the stimulated region can be functionally compensated owing to long-term brain plasticity mechanisms. In brief, although DES is still the gold standard for brain mapping, its combination with new methods such as perioperative neurofunctional imaging and biomathematical modeling is now mandatory, in order to clearly differentiate those networks that are actually indispensable to function from those that can be compensated.

Gray and white matter correlates of the Big Five personality traits.

PubMed

Privado, Jesús; Román, Francisco J; Saénz-Urturi, Carlota; Burgaleta, Miguel; Colom, Roberto

2017-05-04

Personality neuroscience defines the scientific study of the neurobiological basis of personality. This field assumes that individual differences in personality traits are related with structural and functional variations of the human brain. Gray and white matters are structural properties considered separately in previous research. Available findings in this regard are largely disparate. Here we analyze the relationships between gray matter (cortical thickness (CT), cortical surface area (CSA), and cortical volume) and integrity scores obtained after several white matter tracts connecting different brain regions, with individual differences in the personality traits comprised by the Five-Factor Model (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience). These psychological and biological data were obtained from young healthy women. The main findings showed statistically significant associations between occipital CSA variations and extraversion, as well as between parietal CT variations and neuroticism. Regarding white matter integrity, openness showed positive correlations with tracts connecting posterior and anterior brain regions. Therefore, variations in discrete gray matter clusters were associated with temperamental traits (extraversion and neuroticism), whereas long-distance structural connections were related with the dimension of personality that has been associated with high-level cognitive processes (openness). Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Brain Morphometry on Congenital Hand Deformities based on Teichmüller Space Theory.

PubMed

Peng, Hao; Wang, Xu; Duan, Ye; Frey, Scott H; Gu, Xianfeng

2015-01-01

Congenital Hand Deformities (CHD) are usually occurred between fourth and eighth week after the embryo is formed. Failure of the transformation from arm bud cells to upper limb can lead to an abnormal appearing/functioning upper extremity which is presented at birth. Some causes are linked to genetics while others are affected by the environment, and the rest have remained unknown. CHD patients develop prehension through the use of their hands, which affect the brain as time passes. In recent years, CHD have gain increasing attention and researches have been conducted on CHD, both surgically and psychologically. However, the impacts of CHD on brain structure are not well-understood so far. Here, we propose a novel approach to apply Teichmüller space theory and conformal welding method to study brain morphometry in CHD patients. Conformal welding signature reflects the geometric relations among different functional areas on the cortex surface, which is intrinsic to the Riemannian metric, invariant under conformal deformation, and encodes complete information of the functional area boundaries. The computational algorithm is based on discrete surface Ricci flow, which has theoretic guarantees for the existence and uniqueness of the solutions. In practice, discrete Ricci flow is equivalent to a convex optimization problem, therefore has high numerically stability. In this paper, we compute the signatures of contours on general 3D surfaces with surface Ricci flow method, which encodes both global and local surface contour information. Then we evaluated the signatures of pre-central and post-central gyrus on healthy control and CHD subjects for analyzing brain cortical morphometry. Preliminary experimental results from 3D MRI data of CHD/control data demonstrate the effectiveness of our method. The statistical comparison between left and right brain gives us a better understanding on brain morphometry of subjects with Congenital Hand Deformities, in particular, missing the distal part of the upper limb.

Discovering Event Structure in Continuous Narrative Perception and Memory.

PubMed

Baldassano, Christopher; Chen, Janice; Zadbood, Asieh; Pillow, Jonathan W; Hasson, Uri; Norman, Kenneth A

2017-08-02

During realistic, continuous perception, humans automatically segment experiences into discrete events. Using a novel model of cortical event dynamics, we investigate how cortical structures generate event representations during narrative perception and how these events are stored to and retrieved from memory. Our data-driven approach allows us to detect event boundaries as shifts between stable patterns of brain activity without relying on stimulus annotations and reveals a nested hierarchy from short events in sensory regions to long events in high-order areas (including angular gyrus and posterior medial cortex), which represent abstract, multimodal situation models. High-order event boundaries are coupled to increases in hippocampal activity, which predict pattern reinstatement during later free recall. These areas also show evidence of anticipatory reinstatement as subjects listen to a familiar narrative. Based on these results, we propose that brain activity is naturally structured into nested events, which form the basis of long-term memory representations. Copyright © 2017 Elsevier Inc. All rights reserved.

The graphical brain: Belief propagation and active inference

PubMed Central

Friston, Karl J.; Parr, Thomas; de Vries, Bert

2018-01-01

This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference—and what implications this has for context-sensitive connectivity at microscopic and macroscopic levels. In particular, we formulate neuronal processing as belief propagation under deep generative models. Crucially, these models can entertain both discrete and continuous states, leading to distinct schemes for belief updating that play out on the same (neuronal) architecture. Technically, we use Forney (normal) factor graphs to elucidate the requisite message passing in terms of its form and scheduling. To accommodate mixed generative models (of discrete and continuous states), one also has to consider link nodes or factors that enable discrete and continuous representations to talk to each other. When mapping the implicit computational architecture onto neuronal connectivity, several interesting features emerge. For example, Bayesian model averaging and comparison, which link discrete and continuous states, may be implemented in thalamocortical loops. These and other considerations speak to a computational connectome that is inherently state dependent and self-organizing in ways that yield to a principled (variational) account. We conclude with simulations of reading that illustrate the implicit neuronal message passing, with a special focus on how discrete (semantic) representations inform, and are informed by, continuous (visual) sampling of the sensorium. Author Summary This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference—and what implications this has for context-sensitive connectivity at microscopic and macroscopic levels. In particular, we formulate neuronal processing as belief propagation under deep generative models that can entertain both discrete and continuous states. This leads to distinct schemes for belief updating that play out on the same (neuronal) architecture. Technically, we use Forney (normal) factor graphs to characterize the requisite message passing, and link this formal characterization to canonical microcircuits and extrinsic connectivity in the brain. PMID:29417960

Altered brain structural connectivity in post-traumatic stress disorder: a diffusion tensor imaging tractography study.

PubMed

Long, Zhiliang; Duan, Xujun; Xie, Bing; Du, Handan; Li, Rong; Xu, Qiang; Wei, Luqing; Zhang, Shao-xiang; Wu, Yi; Gao, Qing; Chen, Huafu

2013-09-25

Post-traumatic stress disorder (PTSD) is characterized by dysfunction of several discrete brain regions such as medial prefrontal gyrus with hypoactivation and amygdala with hyperactivation. However, alterations of large-scale whole brain topological organization of structural networks remain unclear. Seventeen patients with PTSD in motor vehicle accident survivors and 15 normal controls were enrolled in our study. Large-scale structural connectivity network (SCN) was constructed using diffusion tensor tractography, followed by thresholding the mean factional anisotropy matrix of 90 brain regions. Graph theory analysis was then employed to investigate their aberrant topological properties. Both patient and control group showed small-world topology in their SCNs. However, patients with PTSD exhibited abnormal global properties characterized by significantly decreased characteristic shortest path length and normalized characteristic shortest path length. Furthermore, the patient group showed enhanced nodal centralities predominately in salience network including bilateral anterior cingulate and pallidum, and hippocampus/parahippocamus gyrus, and decreased nodal centralities mainly in medial orbital part of superior frontal gyrus. The main limitation of this study is the small sample of PTSD patients, which may lead to decrease the statistic power. Consequently, this study should be considered an exploratory analysis. These results are consistent with the notion that PTSD can be understood by investigating the dysfunction of large-scale, spatially distributed neural networks, and also provide structural evidences for further exploration of neurocircuitry models in PTSD. © 2013 Elsevier B.V. All rights reserved.

Psychoanalysis and the Brain – Why Did Freud Abandon Neuroscience?

PubMed Central

Northoff, Georg

2012-01-01

Sigmund Freud, the founder of psychoanalysis, was initially a neuroscientist but abandoned neuroscience completely after he made a last attempt to link both in his writing, “Project of a Scientific Psychology,” in 1895. The reasons for his subsequent disregard of the brain remain unclear though. I here argue that one central reason may be that the approach to the brain during his time was simply not appealing to Freud. More specifically, Freud was interested in revealing the psychological predispositions of psychodynamic processes. However, he was not so much focused on the actual psychological functions themselves which though were the prime focus of the neuroscience at his time and also in current Cognitive Neuroscience. Instead, he probably would have been more interested in the brain’s resting state and its constitution of a spatiotemporal structure. I here assume that the resting state activity constitutes a statistically based virtual structure extending and linking the different discrete points in time and space within the brain. That in turn may serve as template, schemata, or grid for all subsequent neural processing during stimulus-induced activity. As such the resting state’ spatiotemporal structure may serve as the neural predisposition of what Freud described as “psychological structure.” Hence, Freud and also current neuropsychoanalysis may want to focus more on neural predispositions, the necessary non-sufficient conditions, rather than the neural correlates, i.e., sufficient, conditions of psychodynamic processes. PMID:22485098

Brain organization and specialization in deep-sea chondrichthyans.

PubMed

Yopak, Kara E; Montgomery, John C

2008-01-01

Chondrichthyans occupy a basal place in vertebrate evolution and offer a relatively unexplored opportunity to study the evolution of vertebrate brains. This study examines the brain morphology of 22 species of deep-sea sharks and holocephalans, in relation to both phylogeny and ecology. Both relative brain size (expressed as residuals) and the relative development of the five major brain areas (telencephalon, diencephalon, mesencephalon, cerebellum, and medulla) were assessed. The cerebellar-like structures, which receive projections from the electroreceptive and lateral line organs, were also examined as a discrete part of the medulla. Although the species examined spanned three major chondrichthyan groupings (Squalomorphii, Galeomorphii, Holocephali), brain size and the relative development of the major brain areas did not track phylogenetic groupings. Rather, a hierarchical cluster analysis performed on the deep-sea sharks and holocephalans shows that these species all share the common characteristics of a relatively reduced telencephalon and smooth cerebellar corpus, as well as extreme relative enlargement of the medulla, specifically the cerebellar-like lobes. Although this study was not a functional analysis, it provides evidence that brain variation in deep-sea chondichthyans shows adaptive patterns in addition to underlying phylogenetic patterns, and that particular brain patterns might be interpreted as 'cerebrotypes'. (c) 2008 S. Karger AG, Basel

Analogue mouse pointer control via an online steady state visual evoked potential (SSVEP) brain-computer interface

NASA Astrophysics Data System (ADS)

Wilson, John J.; Palaniappan, Ramaswamy

2011-04-01

The steady state visual evoked protocol has recently become a popular paradigm in brain-computer interface (BCI) applications. Typically (regardless of function) these applications offer the user a binary selection of targets that perform correspondingly discrete actions. Such discrete control systems are appropriate for applications that are inherently isolated in nature, such as selecting numbers from a keypad to be dialled or letters from an alphabet to be spelled. However motivation exists for users to employ proportional control methods in intrinsically analogue tasks such as the movement of a mouse pointer. This paper introduces an online BCI in which control of a mouse pointer is directly proportional to a user's intent. Performance is measured over a series of pointer movement tasks and compared to the traditional discrete output approach. Analogue control allowed subjects to move the pointer faster to the cued target location compared to discrete output but suffers more undesired movements overall. Best performance is achieved when combining the threshold to movement of traditional discrete techniques with the range of movement offered by proportional control.

Safety of real-time convection-enhanced delivery of liposomes to primate brain: a long-term retrospective.

PubMed

Krauze, Michal T; Vandenberg, Scott R; Yamashita, Yoji; Saito, Ryuta; Forsayeth, John; Noble, Charles; Park, John; Bankiewicz, Krystof S

2008-04-01

Convection-enhanced delivery (CED) is gaining popularity in direct brain infusions. Our group has pioneered the use of liposomes loaded with the MRI contrast reagent as a means to track and quantitate CED in the primate brain through real-time MRI. When co-infused with therapeutic nanoparticles, these tracking liposomes provide us with unprecedented precision in the management of infusions into discrete brain regions. In order to translate real-time CED into clinical application, several important parameters must be defined. In this study, we have analyzed all our cumulative animal data to answer a number of questions as to whether real-time CED in primates depends on concentration of infusate, is reproducible, allows prediction of distribution in a given anatomic structure, and whether it has long term pathological consequences. Our retrospective analysis indicates that real-time CED is highly predictable; repeated procedures yielded identical results, and no long-term brain pathologies were found. We conclude that introduction of our technique to clinical application would enhance accuracy and patient safety when compared to current non-monitored delivery trials.

Antioxidant mediated response of Scoparia dulcis in noise-induced redox imbalance and immunohistochemical changes in rat brain.

PubMed

Wankhar, Wankupar; Srinivasan, Sakthivel; Rajan, Ravindran; Sheeladevi, Rathinasamy

2017-01-19

Noise has been regarded as an environmental/occupational stressor that causes damages to both auditory and non-auditory organs. Prolonged exposure to these mediators of stress has often resulted in detrimental effect, where oxidative/nitrosative stress plays a major role. Hence, it would be appropriate to examine the possible role of free radicals in brain discrete regions and the "antioxidants" mediated response of S. dulcis. Animals were subjected to noise stress for 15 days (100 dB/4 hours/day) and estimation of endogenous free radical and antioxidant activity were carried out on brain discrete regions (the cerebral cortex, cerebellum, brainstem, striatum, hippocampus and hypothalamus). The result showed that exposure to noise could alleviate endogenous free radical generation and altered antioxidant status in brain discrete regions when compared to that of the control groups. This alleviated free radical generation (H 2 O 2 and NO) is well supported by an upregulated protein expression on immunohistochemistry of both iNOS and nNOS in the cerebral cortex on exposure to noise stress. These findings suggest that increased free radical generation and altered anti-oxidative status can cause redox imbalance in the brain discrete regions. However, free radical scavenging activity of the plant was evident as the noise exposed group treated with S. dulcis[200 mg/(kg·b·w)] displayed a therapeutic effect by decreasing the free radical level and regulate the anti-oxidative status to that of control animals. Hence, it can be concluded that the efficacy of S. dulcis could be attributed to its free radical scavenging activity and anti-oxidative property.

Antioxidant mediated response of Scoparia dulcis in noise-induced redox imbalance and immunohistochemical changes in rat brain

PubMed Central

Wankhar, Wankupar; Srinivasan, Sakthivel; Rajan, Ravindran; Sheeladevi, Rathinasamy

2017-01-01

Noise has been regarded as an environmental/occupational stressor that causes damages to both auditory and non-auditory organs. Prolonged exposure to these mediators of stress has often resulted in detrimental effect, where oxidative/nitrosative stress plays a major role. Hence, it would be appropriate to examine the possible role of free radicals in brain discrete regions and the "antioxidants" mediated response of S. dulcis. Animals were subjected to noise stress for 15 days (100 dB/4 hours/day) and estimation of endogenous free radical and antioxidant activity were carried out on brain discrete regions (the cerebral cortex, cerebellum, brainstem, striatum, hippocampus and hypothalamus). The result showed that exposure to noise could alleviate endogenous free radical generation and altered antioxidant status in brain discrete regions when compared to that of the control groups. This alleviated free radical generation (H2O2 and NO) is well supported by an upregulated protein expression on immunohistochemistry of both iNOS and nNOS in the cerebral cortex on exposure to noise stress. These findings suggest that increased free radical generation and altered anti-oxidative status can cause redox imbalance in the brain discrete regions. However, free radical scavenging activity of the plant was evident as the noise exposed group treated with S. dulcis[200 mg/(kg·b·w)] displayed a therapeutic effect by decreasing the free radical level and regulate the anti-oxidative status to that of control animals. Hence, it can be concluded that the efficacy of S. dulcis could be attributed to its free radical scavenging activity and anti-oxidative property. PMID:28808196

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

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

What can volumes reveal about human brain evolution? A framework for bridging behavioral, histometric, and volumetric perspectives

PubMed Central

de Sousa, Alexandra A.; Proulx, Michael J.

2014-01-01

An overall relationship between brain size and cognitive ability exists across primates. Can more specific information about neural function be gleaned from cortical area volumes? Numerous studies have found significant relationships between brain structures and behaviors. However, few studies have speculated about brain structure-function relationships from the microanatomical to the macroanatomical level. Here we address this problem in comparative neuroanatomy, where the functional relevance of overall brain size and the sizes of cortical regions have been poorly understood, by considering comparative psychology, with measures of visual acuity and the perception of visual illusions. We outline a model where the macroscopic size (volume or surface area) of a cortical region (such as the primary visual cortex, V1) is related to the microstructure of discrete brain regions. The hypothesis developed here is that an absolutely larger V1 can process more information with greater fidelity due to having more neurons to represent a field of space. This is the first time that the necessary comparative neuroanatomical research at the microstructural level has been brought to bear on the issue. The evidence suggests that as the size of V1 increases: the number of neurons increases, the neuron density decreases, and the density of neuronal connections increases. Thus, we describe how information about gross neuromorphology, using V1 as a model for the study of other cortical areas, may permit interpretations of cortical function. PMID:25009469

The origin and evolution of chordate nervous systems

PubMed Central

Holland, Linda Z.

2015-01-01

In the past 40 years, comparisons of developmental gene expression and mechanisms of development (evodevo) joined comparative morphology as tools for reconstructing long-extinct ancestral forms. Unfortunately, both approaches typically give congruent answers only with closely related organisms. Chordate nervous systems are good examples. Classical studies alone left open whether the vertebrate brain was a new structure or evolved from the anterior end of an ancestral nerve cord like that of modern amphioxus. Evodevo plus electron microscopy showed that the amphioxus brain has a diencephalic forebrain, small midbrain, hindbrain and spinal cord with parts of the genetic mechanisms for the midbrain/hindbrain boundary, zona limitans intrathalamica and neural crest. Evodevo also showed how extra genes resulting from whole-genome duplications in vertebrates facilitated evolution of new structures like neural crest. Understanding how the chordate central nervous system (CNS) evolved from that of the ancestral deuterostome has been truly challenging. The majority view is that this ancestor had a CNS with a brain that gave rise to the chordate CNS and, with loss of a discrete brain, to one of the two hemichordate nerve cords. The minority view is that this ancestor had no nerve cord; those in chordates and hemichordates evolved independently. New techniques such as phylostratigraphy may help resolve this conundrum. PMID:26554041

Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.

PubMed

Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E

2017-05-01

Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.

The relationship of impulsivity and cortical thickness in depressed and non-depressed adolescents.

PubMed

Fradkin, Yuli; Khadka, Sabin; Bessette, Katie L; Stevens, Michael C

2017-10-01

Major Depressive Disorder (MDD) is recognized to be heterogeneous in terms of brain structure abnormality findings across studies, which might reflect previously unstudied traits that confer variability to neuroimaging measurements. The purpose of this study was to examine the relationships between different types of trait impulsivity and MDD diagnosis on adolescent brain structure. We predicted that adolescents with depression who were high on trait impulsivity would have more abnormal cortical structure than depressed patients or non-MDD who were low on impulsivity. We recruited 58 subjects, including 29 adolescents (ages 12-19) with a primary DSM-IV diagnosis of MDD and a history of suicide attempt and 29 demographically-matched healthy control participants. Our GLM-based analyses sought to describe differences in the linear relationships between cortical thickness and impulsivity trait levels. As hypothesized, we found significant moderation effects in rostral middle frontal gyrus and right paracentral lobule cortical thickness for different subscales of the Barratt Impulsiveness Scale. However, although these brain-behavior relationships differed between diagnostic study groups, they were not simple additive effects as we had predicted. For the middle frontal gyrus, non-MDD participants showed a strong positive association between cortical thickness and BIS-11 Motor scores, while MDD-diagnosed participants showed a negative association. For Non-Planning Impulsiveness, paracentral lobule cortical thickness was observed with greater impulsivity in MDD, but no association was found for controls. In conclusion, the findings confirm that dimensions of impulsivity have discrete neural correlates, and show that relationships between impulsivity and brain structure are expressed differently in adolescents with MDD compared to non-MDD.

Deep Brain Stimulation Frequency—A Divining Rod for New and Novel Concepts of Nervous System Function and Therapy

PubMed Central

Montgomery, Erwin B.; He, Huang

2016-01-01

The efficacy of Deep Brain Stimulation (DBS) for an expanding array of neurological and psychiatric disorders demonstrates directly that DBS affects the basic electroneurophysiological mechanisms of the brain. The increasing array of active electrode configurations, stimulation currents, pulse widths, frequencies, and pulse patterns provides valuable tools to probe electroneurophysiological mechanisms. The extension of basic electroneurophysiological and anatomical concepts using sophisticated computational modeling and simulation has provided relatively straightforward explanations of all the DBS parameters except frequency. This article summarizes current thought about frequency and relevant observations. Current methodological and conceptual errors are critically examined in the hope that future work will not replicate these errors. One possible alternative theory is presented to provide a contrast to many current theories. DBS, conceptually, is a noisy discrete oscillator interacting with the basal ganglia–thalamic–cortical system of multiple re-entrant, discrete oscillators. Implications for positive and negative resonance, stochastic resonance and coherence, noisy synchronization, and holographic memory (related to movement generation) are presented. The time course of DBS neuronal responses demonstrates evolution of the DBS response consistent with the dynamics of re-entrant mechanisms. Finally, computational modeling demonstrates identical dynamics as seen by neuronal activities recorded from human and nonhuman primates, illustrating the differences of discrete from continuous harmonic oscillators and the power of conceptualizing the nervous system as composed on interacting discrete nonlinear oscillators. PMID:27548234

Registering Cortical Surfaces Based on Whole-Brain Structural Connectivity and Continuous Connectivity Analysis

PubMed Central

Gutman, Boris; Leonardo, Cassandra; Jahanshad, Neda; Hibar, Derrek; Eschen-burg, Kristian; Nir, Talia; Villalon, Julio; Thompson, Paul

2014-01-01

We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains’ continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer’s patients and controls. Our measures show significant differences between the two groups. PMID:25320795

On the nature and evolution of the neural bases of human language

NASA Technical Reports Server (NTRS)

Lieberman, Philip

2002-01-01

The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on the brains of human beings and other species provides insight into the evolution of the brain bases of human language. The neural substrate that regulated motor control in the common ancestor of apes and humans most likely was modified to enhance cognitive and linguistic ability. Speech communication played a central role in this process. However, the process that ultimately resulted in the human brain may have started when our earliest hominid ancestors began to walk.

How Does the Sparse Memory “Engram” Neurons Encode the Memory of a Spatial–Temporal Event?

PubMed Central

Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan

2016-01-01

Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns. PMID:27601979

How Does the Sparse Memory "Engram" Neurons Encode the Memory of a Spatial-Temporal Event?

PubMed

Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan

2016-01-01

Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns.

Network structure of brain atrophy in de novo Parkinson's disease

PubMed Central

Zeighami, Yashar; Ulla, Miguel; Iturria-Medina, Yasser; Dadar, Mahsa; Zhang, Yu; Larcher, Kevin Michel-Herve; Fonov, Vladimir; Evans, Alan C; Collins, D Louis; Dagher, Alain

2015-01-01

We mapped the distribution of atrophy in Parkinson's disease (PD) using magnetic resonance imaging (MRI) and clinical data from 232 PD patients and 117 controls from the Parkinson's Progression Markers Initiative. Deformation-based morphometry and independent component analysis identified PD-specific atrophy in the midbrain, basal ganglia, basal forebrain, medial temporal lobe, and discrete cortical regions. The degree of atrophy reflected clinical measures of disease severity. The spatial pattern of atrophy demonstrated overlap with intrinsic networks present in healthy brain, as derived from functional MRI. Moreover, the degree of atrophy in each brain region reflected its functional and anatomical proximity to a presumed disease epicenter in the substantia nigra, compatible with a trans-neuronal spread of the disease. These results support a network-spread mechanism in PD. Finally, the atrophy pattern in PD was also seen in healthy aging, where it also correlated with the loss of striatal dopaminergic innervation. DOI: http://dx.doi.org/10.7554/eLife.08440.001 PMID:26344547

Tracking the fear memory engram: discrete populations of neurons within amygdala, hypothalamus, and lateral septum are specifically activated by auditory fear conditioning

PubMed Central

Wilson, Yvette M.; Gunnersen, Jenny M.; Murphy, Mark

2015-01-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used fos-tau-lacZ (FTL) transgenic mice to identify discrete populations of neurons in amygdala and hypothalamus, which were specifically activated by fear conditioning to a context. Here we have examined neuronal activation due to fear conditioning to a more specific auditory cue. Discrete populations of learning-specific neurons were identified in only a small number of locations in the brain, including those previously found to be activated in amygdala and hypothalamus by context fear conditioning. These populations, each containing only a relatively small number of neurons, may be directly involved in fear learning and memory. PMID:26179231

Cocaine-Induced Structural Plasticity in Input Regions to Distinct Cell Types in Nucleus Accumbens.

PubMed

Barrientos, Cindy; Knowland, Daniel; Wu, Mingche M J; Lilascharoen, Varoth; Huang, Kee Wui; Malenka, Robert C; Lim, Byung Kook

2018-05-09

The nucleus accumbens (NAc) is a brain region implicated in pathological motivated behaviors such as drug addiction and is composed predominantly of two discrete populations of neurons, dopamine receptor-1- and dopamine receptor-2-expressing medium spiny neurons (D1-MSNs and D2-MSNs, respectively). It is unclear whether these populations receive inputs from different brain areas and whether input regions to these cell types undergo distinct structural adaptations in response to the administration of addictive drugs such as cocaine. Using a modified rabies virus-mediated tracing method, we created a comprehensive brain-wide monosynaptic input map to NAc D1- and D2-MSNs. Next, we analyzed nearly 2000 dendrites and 125,000 spines of neurons across four input regions (the prelimbic cortex, medial orbitofrontal cortex, basolateral amygdala, and ventral hippocampus) at four separate time points during cocaine administration and withdrawal to examine changes in spine density in response to repeated intraperitoneal cocaine injection in mice. D1- and D2-MSNs display overall similar input profiles, with the exception that D1-MSNs receive significantly more input from the medial orbitofrontal cortex. We found that neurons in distinct brain areas projecting to D1- and D2-MSNs display different adaptations in dendritic spine density at different stages of cocaine administration and withdrawal. While NAc D1- and D2-MSNs receive input from similar brain structures, cocaine-induced spine density changes in input regions are quite distinct and dynamic. While previous studies have focused on input-specific postsynaptic changes within NAc MSNs in response to cocaine, these findings emphasize the dramatic changes that occur in the afferent input regions as well. Published by Elsevier Inc.

Origins of serotonin innervation of forebrain structures

NASA Technical Reports Server (NTRS)

Kellar, K. J.; Brown, P. A.; Madrid, J.; Bernstein, M.; Vernikos-Danellis, J.; Mehler, W. R.

1977-01-01

The tryptophan hydroxylase activity and high-affinity uptake of (3H) serotonin ((3H)5-HT) were measured in five discrete brain regions of rats following lesions of the dorsal or median raphe nuclei. Dorsal raphe lesions reduced enzyme and uptake activity in the striatum only. Median raphe lesions reduced activities in the hippocampus, septal area, frontal cortex, and, to a lesser extent, in the hypothalamus. These data are consistent with the suggestion that the dorsal and median raphe nuclei are the origins of two separate ascending serotonergic systems - one innervating striatal structures and the other mesolimbic structures, predominantly. In addition, the data suggest that measurements of high-affinity uptake of (3H)5-HT may be a more reliable index of innervation than either 5-HT content or tryptophan hydroxylase activity.

What makes a word so attractive? Disclosing the urge to read while bisecting.

PubMed

Girelli, Luisa; Previtali, Paola; Arduino, Lisa S

2018-04-22

Expert readers have been repeatedly reported to misperceive the centre of visual stimuli, shifting systematically to the left the bisection of any lines (pseudoneglect) while showing a cross-over effect while bisecting different types of orthographic strings (Arduino et al., 2010, Neuropsychologia, 48, 2140). This difference has been attributed to asymmetrical allocation of attention that visuo-verbal material receives when lexical access occurs (e.g., Fischer, 2004, Cognitive Brain Research, 4, 163). The aim of this study was to further examine which visual features guide recognition of potentially orthographic materials. To disentangle the role of orthography, heterogeneity, and visuo-perceptual discreteness, we presented Italian unimpaired adults with four experiments exploiting the bisection paradigm. The results showed that a cross-over effect emerges in most discrete strings, especially when their internal structure, that is being composed of heterogeneous elements, is suggestive of orthographically relevant material. Interestingly, the cross-over effect systematically characterized the processing of letter strings (Experiment 2) and words (Experiments 3 and 4), whether visually discrete or not. Overall, this pattern of results suggests that neither discreteness nor heterogeneity per se are responsible for activating visual scanning mechanisms implied in text exploration, although both contribute to increasing the chance of a visual stimulus undergoing a perceptual analysis dedicated to pre-lexical processing. © 2018 The British Psychological Society.

Permanent alterations in catecholamine concentrations in discrete areas of brain in the offspring of rats treated with methylamphetamine and chlorpromazine

PubMed Central

Tonge, Sally R.

1973-01-01

Methylamphetamine hydrochloride (80 mg/l.) and/or chlorpromazine hydrochloride (200 mg/l.) have been administered in the drinking water of female Wistar rats during pregnancy and suckling. The offspring were weaned at 21 days and thereafter received no drugs. Nine months later, male offspring were killed and noradrenaline and normetanephrine concentrations were determined in eight discrete areas of the brains: neocortex, hippocampus, striatum, thalamus, hypothalamus, corpora quadrigemina, pons/medulla, and amygdala region. Both drugs appeared to have permanently altered catecholamine concentrations in several areas of the brain. There was evidence of antagonism between the effects of the two drugs in the hippocampus, striatum, thalamus, and corpora quadrigemina, where the individual drugs produced altered noradrenaline concentrations but a combination of the two had no effect. PMID:4722052

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

2008-04-01

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

Efficacy Evaluation of Different Wavelet Feature Extraction Methods on Brain MRI Tumor Detection

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel; Kubat, Miroslav

2014-03-01

Automated Magnetic Resonance Imaging brain tumor detection and segmentation is a challenging task. Among different available methods, feature-based methods are very dominant. While many feature extraction techniques have been employed, it is still not quite clear which of feature extraction methods should be preferred. To help improve the situation, we present the results of a study in which we evaluate the efficiency of using different wavelet transform features extraction methods in brain MRI abnormality detection. Applying T1-weighted brain image, Discrete Wavelet Transform (DWT), Discrete Wavelet Packet Transform (DWPT), Dual Tree Complex Wavelet Transform (DTCWT), and Complex Morlet Wavelet Transform (CMWT) methods are applied to construct the feature pool. Three various classifiers as Support Vector Machine, K Nearest Neighborhood, and Sparse Representation-Based Classifier are applied and compared for classifying the selected features. The results show that DTCWT and CMWT features classified with SVM, result in the highest classification accuracy, proving of capability of wavelet transform features to be informative in this application.

Mapping common aphasia assessments to underlying cognitive processes and their neural substrates

PubMed Central

Lacey, Elizabeth H.; Skipper-Kallal, LM; Xing, S; Fama, ME; Turkeltaub, PE

2017-01-01

Background Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. Objective To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Methods 25 behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high resolution MRI was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. Results The principal components analysis yielded four dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. Conclusions An extensive clinical aphasia assessment identifies four independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual’s specific pattern of deficits and preserved abilities. PMID:28135902

On the cyclic nature of perception in vision versus audition

PubMed Central

VanRullen, Rufin; Zoefel, Benedikt; Ilhan, Barkin

2014-01-01

Does our perceptual awareness consist of a continuous stream, or a discrete sequence of perceptual cycles, possibly associated with the rhythmic structure of brain activity? This has been a long-standing question in neuroscience. We review recent psychophysical and electrophysiological studies indicating that part of our visual awareness proceeds in approximately 7–13 Hz cycles rather than continuously. On the other hand, experimental attempts at applying similar tools to demonstrate the discreteness of auditory awareness have been largely unsuccessful. We argue and demonstrate experimentally that visual and auditory perception are not equally affected by temporal subsampling of their respective input streams: video sequences remain intelligible at sampling rates of two to three frames per second, whereas audio inputs lose their fine temporal structure, and thus all significance, below 20–30 samples per second. This does not mean, however, that our auditory perception must proceed continuously. Instead, we propose that audition could still involve perceptual cycles, but the periodic sampling should happen only after the stage of auditory feature extraction. In addition, although visual perceptual cycles can follow one another at a spontaneous pace largely independent of the visual input, auditory cycles may need to sample the input stream more flexibly, by adapting to the temporal structure of the auditory inputs. PMID:24639585

Neuroscience is awaiting for a breakthrough: an essay bridging the concepts of Descartes, Einstein, Heisenberg, Hebb and Hayek with the explanatory formulations in this special issue.

PubMed

Başar, Erol; Karakaş, Sirel

2006-05-01

The paper presents gedankenmodels which, based on the theories and models in the present special issue, describe the conditions for a breakthrough in brain sciences and neuroscience. The new model is based on contemporary findings which show that the brain and its cognitive processes show super-synchronization. Accordingly, understanding the brain/body-mind complex is possible only when these three are considered as a wholistic entity and not as discrete structures or functions. Such a breakthrough and the related perspectives to the brain/body-mind complex will involve a transition from the mechanistic Cartesian system to a nebulous Cartesian system, one that is basically characterized by parallel computing and is further parallel to quantum mechanics. This integrated outlook on the brain/body-mind, or dynamic functionality, will make the treatment of also the meta-cognitive processes and the greater part of the iceberg, the unconscious, possible. All this will be possible only through the adoption of a multidisciplinary approach that will bring together the knowledge and the technology of the four P's which consist of physics, physiology, psychology and philosophy. The genetic approach to the functional dynamics of the brain/body-mind, where the oscillatory responses were found to be laws of brain activity, is presented in this volume as one of the most recent perspectives of neuroscience.

What songbirds teach us about learning

NASA Astrophysics Data System (ADS)

Brainard, Michael S.; Doupe, Allison J.

2002-05-01

Bird fanciers have known for centuries that songbirds learn their songs. This learning has striking parallels to speech acquisition: like humans, birds must hear the sounds of adults during a sensitive period, and must hear their own voice while learning to vocalize. With the discovery and investigation of discrete brain structures required for singing, songbirds are now providing insights into neural mechanisms of learning. Aided by a wealth of behavioural observations and species diversity, studies in songbirds are addressing such basic issues in neuroscience as perceptual and sensorimotor learning, developmental regulation of plasticity, and the control and function of adult neurogenesis.

Functional Connectivity Magnetic Resonance Imaging Classification of Autism

ERIC Educational Resources Information Center

Anderson, Jeffrey S.; Nielsen, Jared A.; Froehlich, Alyson L.; DuBray, Molly B.; Druzgal, T. Jason; Cariello, Annahir N.; Cooperrider, Jason R.; Zielinski, Brandon A.; Ravichandran, Caitlin; Fletcher, P. Thomas; Alexander, Andrew L.; Bigler, Erin D.; Lange, Nicholas; Lainhart, Janet E.

2011-01-01

Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear…

Multi-object model-based multi-atlas segmentation for rodent brains using dense discrete correspondences

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Kim, Sun Hyung; Styner, Martin

2016-03-01

The delineation of rodent brain structures is challenging due to low-contrast multiple cortical and subcortical organs that are closely interfacing to each other. Atlas-based segmentation has been widely employed due to its ability to delineate multiple organs at the same time via image registration. The use of multiple atlases and subsequent label fusion techniques has further improved the robustness and accuracy of atlas-based segmentation. However, the accuracy of atlas-based segmentation is still prone to registration errors; for example, the segmentation of in vivo MR images can be less accurate and robust against image artifacts than the segmentation of post mortem images. In order to improve the accuracy and robustness of atlas-based segmentation, we propose a multi-object, model-based, multi-atlas segmentation method. We first establish spatial correspondences across atlases using a set of dense pseudo-landmark particles. We build a multi-object point distribution model using those particles in order to capture inter- and intra- subject variation among brain structures. The segmentation is obtained by fitting the model into a subject image, followed by label fusion process. Our result shows that the proposed method resulted in greater accuracy than comparable segmentation methods, including a widely used ANTs registration tool.

Quantifying Discretization Effects on Brain Trauma Simulations

DTIC Science & Technology

2016-01-01

arbitrarily formed meshes can propagate error when resolving interactions among the skull , cerebrospinal fluid, and brain. We compared Lagrangian, pure...embedded methods from top to bottom. ......3 Fig. 2 Loading node-set for Eulerian rotational problem. The dark shaded area around the skull is the area to...and top inner edges of the skull . The example shown is a Lagrangian rotational model. The red and green materials represent the brain and skull

Altered Brain Microstate Dynamics in Adolescents with Narcolepsy

PubMed Central

Drissi, Natasha M.; Szakács, Attila; Witt, Suzanne T.; Wretman, Anna; Ulander, Martin; Ståhlbrandt, Henriettae; Darin, Niklas; Hallböök, Tove; Landtblom, Anne-Marie; Engström, Maria

2016-01-01

Narcolepsy is a chronic sleep disorder caused by a loss of hypocretin-1 producing neurons in the hypothalamus. Previous neuroimaging studies have investigated brain function in narcolepsy during rest using positron emission tomography (PET) and single photon emission computed tomography (SPECT). In addition to hypothalamic and thalamic dysfunction they showed aberrant prefrontal perfusion and glucose metabolism in narcolepsy. Given these findings in brain structure and metabolism in narcolepsy, we anticipated that changes in functional magnetic resonance imaging (fMRI) resting state network (RSN) dynamics might also be apparent in patients with narcolepsy. The objective of this study was to investigate and describe brain microstate activity in adolescents with narcolepsy and correlate these to RSNs using simultaneous fMRI and electroencephalography (EEG). Sixteen adolescents (ages 13–20) with a confirmed diagnosis of narcolepsy were recruited and compared to age-matched healthy controls. Simultaneous EEG and fMRI data were collected during 10 min of wakeful rest. EEG data were analyzed for microstates, which are discrete epochs of stable global brain states obtained from topographical EEG analysis. Functional MRI data were analyzed for RSNs. Data showed that narcolepsy patients were less likely than controls to spend time in a microstate which we found to be related to the default mode network and may suggest a disruption of this network that is disease specific. We concluded that adolescents with narcolepsy have altered resting state brain dynamics. PMID:27536225

Tracking the fear memory engram: discrete populations of neurons within amygdala, hypothalamus, and lateral septum are specifically activated by auditory fear conditioning.

PubMed

Butler, Christopher W; Wilson, Yvette M; Gunnersen, Jenny M; Murphy, Mark

2015-08-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used fos-tau-lacZ (FTL) transgenic mice to identify discrete populations of neurons in amygdala and hypothalamus, which were specifically activated by fear conditioning to a context. Here we have examined neuronal activation due to fear conditioning to a more specific auditory cue. Discrete populations of learning-specific neurons were identified in only a small number of locations in the brain, including those previously found to be activated in amygdala and hypothalamus by context fear conditioning. These populations, each containing only a relatively small number of neurons, may be directly involved in fear learning and memory. © 2015 Butler et al.; Published by Cold Spring Harbor Laboratory Press.

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John; Lui, Su

2017-12-05

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta­-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular ­gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia. 2017 Joule Inc., or its licensors

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2018-03-01

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2017-12-15

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.

Brain Embodiment of Syntax and Grammar: Discrete Combinatorial Mechanisms Spelt Out in Neuronal Circuits

ERIC Educational Resources Information Center

Pulvermuller, Friedemann

2010-01-01

Neuroscience has greatly improved our understanding of the brain basis of abstract lexical and semantic processes. The neuronal devices underlying words and concepts are distributed neuronal assemblies reaching into sensory and motor systems of the cortex and, at the cognitive level, information binding in such widely dispersed circuits is…

Neural Basis of Interpersonal Traits in Neurodegenerative Diseases

PubMed Central

Sollberger, Marc; Stanley, Christine M.; Wilson, Stephen M.; Gyurak, Anett; Beckman, Victoria; Growdon, Matthew; Jang, Jung; Weiner, Michael W.; Miller, Bruce L.; Rankin, Katherine P.

2009-01-01

Several functional and structural imaging studies have investigated the neural basis of personality in healthy adults, but human lesions studies are scarce. Personality changes are a common symptom in patients with neurodegenerative diseases like frontotemporal dementia (FTD) and semantic dementia (SD), allowing a unique window into the neural basis of personality. In this study, we used the Interpersonal Adjective Scales to investigate the structural basis of eight interpersonal traits (dominance, arrogance, coldness, introversion, submissiveness, ingenuousness, warmth, and extraversion) in 257 subjects: 214 patients with neurodegenerative diseases such as FTD, SD, progressive non-fluent aphasia, Alzheimer’s disease, amnestic mild cognitive impairment, corticobasal degeneration, and progressive supranuclear palsy and 43 healthy elderly people. Measures of interpersonal traits were correlated with regional atrophy pattern using voxel-based morphometry (VBM) analysis of structural MR images. Interpersonal traits mapped onto distinct brain regions depending on the degree to which they involved agency and affiliation. Interpersonal traits high in agency related to left dorsolateral prefrontal and left lateral frontopolar regions, whereas interpersonal traits high in affiliation related to right ventromedial prefrontal and right anteromedial temporal regions. Consistent with the existing literature on neural networks underlying social cognition, these results indicate that brain regions related to externally-focused, executive control-related processes underlie agentic interpersonal traits such as dominance, whereas brain regions related to internally-focused, emotion- and reward-related processes underlie affiliative interpersonal traits such as warmth. In addition, these findings indicate that interpersonal traits are subserved by complex neural networks rather than discrete anatomic areas. PMID:19540253

Multiscale Path Metrics for the Analysis of Discrete Geometric Structures

DTIC Science & Technology

2017-11-30

Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release

Differences between high-affinity forskolin binding sites in dopamine-riche and other regions of rat brain

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

Poat, J.A.; Cripps, H.E.; Iversen, L.L.

1988-05-01

Forskolin labelled with (/sup 3/H) bound to high- and low-affinity sites in the rat brain. The high-affinity site was discretely located, with highest densities in the striatum, nucleus accumbens, olfactory tubercule, substantia nigra, hippocampus, and the molecular layers of the cerebellum. This site did not correlate well with the distribution of adenylate cyclase. The high-affinity striatal binding site may be associated with a stimulatory guanine nucleotide-binding protein. Thus, the number of sites was increased by the addition of Mg/sup 2 +/ and guanylyl imidodiphosphate. Cholera toxin stereotaxically injected into rat striatum increased the number of binding sites, and no furthermore » increase was noted following the subsequent addition of guanyl nucleotide. High-affinity forskolin binding sites in non-dopamine-rich brain areas (hippocampus and cerebullum) were modulated in a qualitatively different manner by guanyl nucleotides. In these areas the number of binding sites was significantly reduced by the addition of guanyl nucleotide. These results suggest that forskolin may have a potential role in identifying different functional/structural guanine nucleotide-binding proteins.« less

A weighted communicability measure applied to complex brain networks

PubMed Central

Crofts, Jonathan J.; Higham, Desmond J.

2009-01-01

Recent advances in experimental neuroscience allow non-invasive studies of the white matter tracts in the human central nervous system, thus making available cutting-edge brain anatomical data describing these global connectivity patterns. Through magnetic resonance imaging, this non-invasive technique is able to infer a snapshot of the cortical network within the living human brain. Here, we report on the initial success of a new weighted network communicability measure in distinguishing local and global differences between diseased patients and controls. This approach builds on recent advances in network science, where an underlying connectivity structure is used as a means to measure the ease with which information can flow between nodes. One advantage of our method is that it deals directly with the real-valued connectivity data, thereby avoiding the need to discretize the corresponding adjacency matrix, i.e. to round weights up to 1 or down to 0, depending upon some threshold value. Experimental results indicate that the new approach is able to extract biologically relevant features that are not immediately apparent from the raw connectivity data. PMID:19141429

Optogenetic fMRI and electrophysiological identification of region-specific connectivity between the cerebellar cortex and forebrain.

PubMed

Choe, Katrina Y; Sanchez, Carlos F; Harris, Neil G; Otis, Thomas S; Mathews, Paul J

2018-06-01

Complex animal behavior is produced by dynamic interactions between discrete regions of the brain. As such, defining functional connections between brain regions is critical in gaining a full understanding of how the brain generates behavior. Evidence suggests that discrete regions of the cerebellar cortex functionally project to the forebrain, mediating long-range communication potentially important in motor and non-motor behaviors. However, the connectivity map remains largely incomplete owing to the challenge of driving both reliable and selective output from the cerebellar cortex, as well as the need for methods to detect region specific activation across the entire forebrain. Here we utilize a paired optogenetic and fMRI (ofMRI) approach to elucidate the downstream forebrain regions modulated by activating a region of the cerebellum that induces stereotypical, ipsilateral forelimb movements. We demonstrate with ofMRI, that activating this forelimb motor region of the cerebellar cortex results in functional activation of a variety of forebrain and midbrain areas of the brain, including the hippocampus and primary motor, retrosplenial and anterior cingulate cortices. We further validate these findings using optogenetic stimulation paired with multi-electrode array recordings and post-hoc staining for molecular markers of activated neurons (i.e. c-Fos). Together, these findings demonstrate that a single discrete region of the cerebellar cortex is capable of influencing motor output and the activity of a number of downstream forebrain as well as midbrain regions thought to be involved in different aspects of behavior. Copyright © 2018 Elsevier Inc. All rights reserved.

Combining Classical and Molecular Approaches Elaborates on the Complexity of Mechanisms Underpinning Anterior Regeneration

PubMed Central

Evans, Deborah J.; Owlarn, Suthira; Tejada Romero, Belen; Chen, Chen; Aboobaker, A. Aziz

2011-01-01

The current model of planarian anterior regeneration evokes the establishment of low levels of Wnt signalling at anterior wounds, promoting anterior polarity and subsequent elaboration of anterior fate through the action of the TALE class homeodomain PREP. The classical observation that decapitations positioned anteriorly will regenerate heads more rapidly than posteriorly positioned decapitations was among the first to lead to the proposal of gradients along an anteroposterior (AP) axis in a developmental context. An explicit understanding of this phenomenon is not included in the current model of anterior regeneration. This raises the question what the underlying molecular and cellular basis of this temporal gradient is, whether it can be explained by current models and whether understanding the gradient will shed light on regenerative events. Differences in anterior regeneration rate are established very early after amputation and this gradient is dependent on the activity of Hedgehog (Hh) signalling. Animals induced to produce two tails by either Smed-APC-1(RNAi) or Smed-ptc(RNAi) lose anterior fate but form previously described ectopic anterior brain structures. Later these animals form peri-pharyngeal brain structures, which in Smed-ptc(RNAi) grow out of the body establishing a new A/P axis. Combining double amputation and hydroxyurea treatment with RNAi experiments indicates that early ectopic brain structures are formed by uncommitted stem cells that have progressed through S-phase of the cell cycle at the time of amputation. Our results elaborate on the current simplistic model of both AP axis and brain regeneration. We find evidence of a gradient of hedgehog signalling that promotes posterior fate and temporarily inhibits anterior regeneration. Our data supports a model for anterior brain regeneration with distinct early and later phases of regeneration. Together these insights start to delineate the interplay between discrete existing, new, and then later homeostatic signals in AP axis regeneration. PMID:22125640

Combining classical and molecular approaches elaborates on the complexity of mechanisms underpinning anterior regeneration.

PubMed

Evans, Deborah J; Owlarn, Suthira; Tejada Romero, Belen; Chen, Chen; Aboobaker, A Aziz

2011-01-01

The current model of planarian anterior regeneration evokes the establishment of low levels of Wnt signalling at anterior wounds, promoting anterior polarity and subsequent elaboration of anterior fate through the action of the TALE class homeodomain PREP. The classical observation that decapitations positioned anteriorly will regenerate heads more rapidly than posteriorly positioned decapitations was among the first to lead to the proposal of gradients along an anteroposterior (AP) axis in a developmental context. An explicit understanding of this phenomenon is not included in the current model of anterior regeneration. This raises the question what the underlying molecular and cellular basis of this temporal gradient is, whether it can be explained by current models and whether understanding the gradient will shed light on regenerative events. Differences in anterior regeneration rate are established very early after amputation and this gradient is dependent on the activity of Hedgehog (Hh) signalling. Animals induced to produce two tails by either Smed-APC-1(RNAi) or Smed-ptc(RNAi) lose anterior fate but form previously described ectopic anterior brain structures. Later these animals form peri-pharyngeal brain structures, which in Smed-ptc(RNAi) grow out of the body establishing a new A/P axis. Combining double amputation and hydroxyurea treatment with RNAi experiments indicates that early ectopic brain structures are formed by uncommitted stem cells that have progressed through S-phase of the cell cycle at the time of amputation. Our results elaborate on the current simplistic model of both AP axis and brain regeneration. We find evidence of a gradient of hedgehog signalling that promotes posterior fate and temporarily inhibits anterior regeneration. Our data supports a model for anterior brain regeneration with distinct early and later phases of regeneration. Together these insights start to delineate the interplay between discrete existing, new, and then later homeostatic signals in AP axis regeneration.

Multimodal fluorescence microscopy of prion strain specific PrP deposits stained by thiophene-based amyloid ligands.

PubMed

Magnusson, Karin; Simon, Rozalyn; Sjölander, Daniel; Sigurdson, Christina J; Hammarström, Per; Nilsson, K Peter R

2014-01-01

The disease-associated prion protein (PrP) forms aggregates which vary in structural conformation yet share an identical primary sequence. These variations in PrP conformation are believed to manifest in prion strains exhibiting distinctly different periods of disease incubation as well as regionally specific aggregate deposition within the brain. The anionic luminescent conjugated polythiophene (LCP), polythiophene acetic acid (PTAA) has previously been used to distinguish PrP deposits associated with distinct mouse adapted strains via distinct fluorescence emission profiles from the dye. Here, we employed PTAA and 3 structurally related chemically defined luminescent conjugated oligothiophenes (LCOs) to stain brain tissue sections from mice inoculated with 2 distinct prion strains. Our results showed that in addition to emission spectra, excitation, and fluorescence lifetime imaging microscopy (FLIM) can fruitfully be assessed for optical distinction of PrP deposits associated with distinct prion strains. Our findings support the theory that alterations in LCP/LCO fluorescence are due to distinct conformational restriction of the thiophene backbone upon interaction with PrP aggregates associated with distinct prion strains. We foresee that LCP and LCO staining in combination with multimodal fluorescence microscopy might aid in detecting structural differences among discrete protein aggregates and in linking protein conformational features with disease phenotypes for a variety of neurodegenerative proteinopathies.

Multimodal fluorescence microscopy of prion strain specific PrP deposits stained by thiophene-based amyloid ligands

PubMed Central

Magnusson, Karin; Simon, Rozalyn; Sjölander, Daniel; Sigurdson, Christina J; Hammarström, Per; Nilsson, K Peter R

2014-01-01

The disease-associated prion protein (PrP) forms aggregates which vary in structural conformation yet share an identical primary sequence. These variations in PrP conformation are believed to manifest in prion strains exhibiting distinctly different periods of disease incubation as well as regionally specific aggregate deposition within the brain. The anionic luminescent conjugated polythiophene (LCP), polythiophene acetic acid (PTAA) has previously been used to distinguish PrP deposits associated with distinct mouse adapted strains via distinct fluorescence emission profiles from the dye. Here, we employed PTAA and 3 structurally related chemically defined luminescent conjugated oligothiophenes (LCOs) to stain brain tissue sections from mice inoculated with 2 distinct prion strains. Our results showed that in addition to emission spectra, excitation, and fluorescence lifetime imaging microscopy (FLIM) can fruitfully be assessed for optical distinction of PrP deposits associated with distinct prion strains. Our findings support the theory that alterations in LCP/LCO fluorescence are due to distinct conformational restriction of the thiophene backbone upon interaction with PrP aggregates associated with distinct prion strains. We foresee that LCP and LCO staining in combination with multimodal fluorescence microscopy might aid in detecting structural differences among discrete protein aggregates and in linking protein conformational features with disease phenotypes for a variety of neurodegenerative proteinopathies. PMID:25495506

Space-Time Discrete KPZ Equation

NASA Astrophysics Data System (ADS)

Cannizzaro, G.; Matetski, K.

2018-03-01

We study a general family of space-time discretizations of the KPZ equation and show that they converge to its solution. The approach we follow makes use of basic elements of the theory of regularity structures (Hairer in Invent Math 198(2):269-504, 2014) as well as its discrete counterpart (Hairer and Matetski in Discretizations of rough stochastic PDEs, 2015. arXiv:1511.06937). Since the discretization is in both space and time and we allow non-standard discretization for the product, the methods mentioned above have to be suitably modified in order to accommodate the structure of the models under study.

Discrete-continuous duality of protein structure space.

PubMed

Sadreyev, Ruslan I; Kim, Bong-Hyun; Grishin, Nick V

2009-06-01

Recently, the nature of protein structure space has been widely discussed in the literature. The traditional discrete view of protein universe as a set of separate folds has been criticized in the light of growing evidence that almost any arrangement of secondary structures is possible and the whole protein space can be traversed through a path of similar structures. Here we argue that the discrete and continuous descriptions are not mutually exclusive, but complementary: the space is largely discrete in evolutionary sense, but continuous geometrically when purely structural similarities are quantified. Evolutionary connections are mainly confined to separate structural prototypes corresponding to folds as islands of structural stability, with few remaining traceable links between the islands. However, for a geometric similarity measure, it is usually possible to find a reasonable cutoff that yields paths connecting any two structures through intermediates.

Statistical physics approaches to Alzheimer's disease

NASA Astrophysics Data System (ADS)

Peng, Shouyong

Alzheimer's disease (AD) is the most common cause of late life dementia. In the brain of an AD patient, neurons are lost and spatial neuronal organizations (microcolumns) are disrupted. An adequate quantitative analysis of microcolumns requires that we automate the neuron recognition stage in the analysis of microscopic images of human brain tissue. We propose a recognition method based on statistical physics. Specifically, Monte Carlo simulations of an inhomogeneous Potts model are applied for image segmentation. Unlike most traditional methods, this method improves the recognition of overlapped neurons, and thus improves the overall recognition percentage. Although the exact causes of AD are unknown, as experimental advances have revealed the molecular origin of AD, they have continued to support the amyloid cascade hypothesis, which states that early stages of aggregation of amyloid beta (Abeta) peptides lead to neurodegeneration and death. X-ray diffraction studies reveal the common cross-beta structural features of the final stable aggregates-amyloid fibrils. Solid-state NMR studies also reveal structural features for some well-ordered fibrils. But currently there is no feasible experimental technique that can reveal the exact structure or the precise dynamics of assembly and thus help us understand the aggregation mechanism. Computer simulation offers a way to understand the aggregation mechanism on the molecular level. Because traditional all-atom continuous molecular dynamics simulations are not fast enough to investigate the whole aggregation process, we apply coarse-grained models and discrete molecular dynamics methods to increase the simulation speed. First we use a coarse-grained two-bead (two beads per amino acid) model. Simulations show that peptides can aggregate into multilayer beta-sheet structures, which agree with X-ray diffraction experiments. To better represent the secondary structure transition happening during aggregation, we refine the model to four beads per amino acid. Typical essential interactions, such as backbone hydrogen bond, hydrophobic and electrostatic interactions, are incorporated into our model. We study the aggregation of Abeta16-22, a peptide that can aggregate into a well-ordered fibrillar structure in experiments. Our results show that randomly-oriented monomers can aggregate into fibrillar subunits, which agree not only with X-ray diffraction experiments but also with solid-state NMR studies. Our findings demonstrate that coarse-grained models and discrete molecular dynamics simulations can help researchers understand the aggregation mechanism of amyloid peptides.

Discrete capacity limits and neuroanatomical correlates of visual short-term memory for objects and spatial locations.

PubMed

Konstantinou, Nikos; Constantinidou, Fofi; Kanai, Ryota

2017-02-01

Working memory is responsible for keeping information in mind when it is no longer in view, linking perception with higher cognitive functions. Despite such crucial role, short-term maintenance of visual information is severely limited. Research suggests that capacity limits in visual short-term memory (VSTM) are correlated with sustained activity in distinct brain areas. Here, we investigated whether variability in the structure of the brain is reflected in individual differences of behavioral capacity estimates for spatial and object VSTM. Behavioral capacity estimates were calculated separately for spatial and object information using a novel adaptive staircase procedure and were found to be unrelated, supporting domain-specific VSTM capacity limits. Voxel-based morphometry (VBM) analyses revealed dissociable neuroanatomical correlates of spatial versus object VSTM. Interindividual variability in spatial VSTM was reflected in the gray matter density of the inferior parietal lobule. In contrast, object VSTM was reflected in the gray matter density of the left insula. These dissociable findings highlight the importance of considering domain-specific estimates of VSTM capacity and point to the crucial brain regions that limit VSTM capacity for different types of visual information. Hum Brain Mapp 38:767-778, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neurobiological actions of cysteamine

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

Brown, M.; Fisher, L.; Mason, R.T.

1985-06-01

Somatostatin (SS)-related peptides act within discrete brain regions to inhibit adrenal epinephrine (E) secretion, to prevent hypothermia, and to produce hyperthermia. Depletion of brain concentrations of these SS-related peptides using cysteamine (CSH) or central administration of an SS receptor antagonist increases adrenal E secretion and impairs thermoregulation. These actions of CSH and the SS receptor antagonist are reversed by administration of SS into the central nervous system. These results support the hypothesis that endogenous brain SS-related peptides are involved in the regulation of adrenal E secretion and thermoregulation.

Regularized two-step brain activity reconstruction from spatiotemporal EEG data

NASA Astrophysics Data System (ADS)

Alecu, Teodor I.; Voloshynovskiy, Sviatoslav; Pun, Thierry

2004-10-01

We are aiming at using EEG source localization in the framework of a Brain Computer Interface project. We propose here a new reconstruction procedure, targeting source (or equivalently mental task) differentiation. EEG data can be thought of as a collection of time continuous streams from sparse locations. The measured electric potential on one electrode is the result of the superposition of synchronized synaptic activity from sources in all the brain volume. Consequently, the EEG inverse problem is a highly underdetermined (and ill-posed) problem. Moreover, each source contribution is linear with respect to its amplitude but non-linear with respect to its localization and orientation. In order to overcome these drawbacks we propose a novel two-step inversion procedure. The solution is based on a double scale division of the solution space. The first step uses a coarse discretization and has the sole purpose of globally identifying the active regions, via a sparse approximation algorithm. The second step is applied only on the retained regions and makes use of a fine discretization of the space, aiming at detailing the brain activity. The local configuration of sources is recovered using an iterative stochastic estimator with adaptive joint minimum energy and directional consistency constraints.

Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy.

PubMed

Yang, Guang; Nawaz, Tahir; Barrick, Thomas R; Howe, Franklyn A; Slabaugh, Greg

2015-12-01

Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

Retrieving quasi-phase-matching structure with discrete layer-peeling method.

PubMed

Zhang, Q W; Zeng, X L; Wang, M; Wang, T Y; Chen, X F

2012-07-02

An approach to reconstruct a quasi-phase-matching grating by using a discrete layer-peeling algorithm is presented. Experimentally measured output spectra of Šolc-type filters, based on uniform and chirped QPM structures, are used in the discrete layer-peeling algorithm. The reconstructed QPM structures are in agreement with the exact structures used in the experiment and the method is verified to be accurate and efficient in quality inspection on quasi-phase-matching grating.

On the role of the SMA in the discrete sequence production task: a TMS study. Transcranial Magnetic Stimulation.

PubMed

Verwey, Willem B; Lammens, Robin; van Honk, Jack

2002-01-01

Participants practiced two discrete six-key sequences for a total of 420 trials. The 1 x 6 sequence had a unique order of key presses while the 2 x 3 sequence involved repetition of a three-key segment. Both sequences showed a long interkey interval halfway the sequence indicating hierarchical sequence control in that not only the 2 x 3 but also the 1 x 6 sequence was executed as two successive motor chunks. Besides, the second part of both sequences was executed faster than the first part. This supports the earlier notion of a motor processor executing the elements of familiar motor chunks and a cognitive processor triggering either these motor chunks or individual sequence elements. Low-frequency, off-line transcranial magnetic stimulation (TMS) of the supplementary motor area (SMA) counteracted normal improvement with practice of key presses at all sequence positions. Together, these results are in line with the notion that with moderate practice, the SMA executes short sequence fragments that are concatenated by other brain structures.

Discrete classification technique applied to TV advertisements liking recognition system based on low-cost EEG headsets.

PubMed

Soria Morillo, Luis M; Alvarez-Garcia, Juan A; Gonzalez-Abril, Luis; Ortega Ramírez, Juan A

2016-07-15

In this paper a new approach is applied to the area of marketing research. The aim of this paper is to recognize how brain activity responds during the visualization of short video advertisements using discrete classification techniques. By means of low cost electroencephalography devices (EEG), the activation level of some brain regions have been studied while the ads are shown to users. We may wonder about how useful is the use of neuroscience knowledge in marketing, or what could provide neuroscience to marketing sector, or why this approach can improve the accuracy and the final user acceptance compared to other works. By using discrete techniques over EEG frequency bands of a generated dataset, C4.5, ANN and the new recognition system based on Ameva, a discretization algorithm, is applied to obtain the score given by subjects to each TV ad. The proposed technique allows to reach more than 75 % of accuracy, which is an excellent result taking into account the typology of EEG sensors used in this work. Furthermore, the time consumption of the algorithm proposed is reduced up to 30 % compared to other techniques presented in this paper. This bring about a battery lifetime improvement on the devices where the algorithm is running, extending the experience in the ubiquitous context where the new approach has been tested.

Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics.

PubMed

Harris, Kenneth D; Hochgerner, Hannah; Skene, Nathan G; Magno, Lorenza; Katona, Linda; Bengtsson Gonzales, Carolina; Somogyi, Peter; Kessaris, Nicoletta; Linnarsson, Sten; Hjerling-Leffler, Jens

2018-06-18

Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.

Generalized fictitious methods for fluid-structure interactions: Analysis and simulations

NASA Astrophysics Data System (ADS)

Yu, Yue; Baek, Hyoungsu; Karniadakis, George Em

2013-07-01

We present a new fictitious pressure method for fluid-structure interaction (FSI) problems in incompressible flow by generalizing the fictitious mass and damping methods we published previously in [1]. The fictitious pressure method involves modification of the fluid solver whereas the fictitious mass and damping methods modify the structure solver. We analyze all fictitious methods for simplified problems and obtain explicit expressions for the optimal reduction factor (convergence rate index) at the FSI interface [2]. This analysis also demonstrates an apparent similarity of fictitious methods to the FSI approach based on Robin boundary conditions, which have been found to be very effective in FSI problems. We implement all methods, including the semi-implicit Robin based coupling method, in the context of spectral element discretization, which is more sensitive to temporal instabilities than low-order methods. However, the methods we present here are simple and general, and hence applicable to FSI based on any other spatial discretization. In numerical tests, we verify the selection of optimal values for the fictitious parameters for simplified problems and for vortex-induced vibrations (VIV) even at zero mass ratio ("for-ever-resonance"). We also develop an empirical a posteriori analysis for complex geometries and apply it to 3D patient-specific flexible brain arteries with aneurysms for very large deformations. We demonstrate that the fictitious pressure method enhances stability and convergence, and is comparable or better in most cases to the Robin approach or the other fictitious methods.

Role of stochastic processes in maintaining discrete strain structure in antigenically diverse pathogen populations.

PubMed

Buckee, Caroline O; Recker, Mario; Watkins, Eleanor R; Gupta, Sunetra

2011-09-13

Many highly diverse pathogen populations appear to exist stably as discrete antigenic types despite evidence of genetic exchange. It has been shown that this may arise as a consequence of immune selection on pathogen populations, causing them to segregate permanently into discrete nonoverlapping subsets of antigenic variants to minimize competition for available hosts. However, discrete antigenic strain structure tends to break down under conditions where there are unequal numbers of allelic variants at each locus. Here, we show that the inclusion of stochastic processes can lead to the stable recovery of discrete strain structure through loss of certain alleles. This explains how pathogen populations may continue to behave as independently transmitted strains despite inevitable asymmetries in allelic diversity of major antigens. We present evidence for this type of structuring across global meningococcal isolates in three diverse antigens that are currently being developed as vaccine components.

76 FR 74655 - Damage Tolerance and Fatigue Evaluation of Composite Rotorcraft Structures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-01

... and discrete flaws, and impact or other accidental damage (including the discrete source of the... discrete manufacturing defects or accidental damage, is avoided throughout the operational life or... and discrete flaws, and impact or other accidental damage (including the discrete source of the...

A general population-genetic model for the production by population structure of spurious genotype-phenotype associations in discrete, admixed or spatially distributed populations.

PubMed

Rosenberg, Noah A; Nordborg, Magnus

2006-07-01

In linkage disequilibrium mapping of genetic variants causally associated with phenotypes, spurious associations can potentially be generated by any of a variety of types of population structure. However, mathematical theory of the production of spurious associations has largely been restricted to population structure models that involve the sampling of individuals from a collection of discrete subpopulations. Here, we introduce a general model of spurious association in structured populations, appropriate whether the population structure involves discrete groups, admixture among such groups, or continuous variation across space. Under the assumptions of the model, we find that a single common principle--applicable to both the discrete and admixed settings as well as to spatial populations--gives a necessary and sufficient condition for the occurrence of spurious associations. Using a mathematical connection between the discrete and admixed cases, we show that in admixed populations, spurious associations are less severe than in corresponding mixtures of discrete subpopulations, especially when the variance of admixture across individuals is small. This observation, together with the results of simulations that examine the relative influences of various model parameters, has important implications for the design and analysis of genetic association studies in structured populations.

A discrete polar Stockwell transform for enhanced characterization of tissue structure using MRI.

PubMed

Pridham, Glen; Steenwijk, Martijn D; Geurts, Jeroen J G; Zhang, Yunyan

2018-05-02

The purpose of this study was to present an effective algorithm for computing the discrete polar Stockwell transform (PST), investigate its unique multiscale and multi-orientation features, and explore potentially new applications including denoising and tissue segmentation. We investigated PST responses using both synthetic and MR images. Moreover, we compared the features of PST with both Gabor and Morlet wavelet transforms, and compared the PST with two wavelet approaches for denoising using MRI. Using a synthetic image, we also tested the edge effect of PST through signal-padding. Then, we constructed a partially supervised classifier using radial, marginal PST spectra of T2-weighted MRI, acquired from postmortem brains with multiple sclerosis. The classification involved three histology-verified tissue types: normal appearing white matter (NAWM), lesion, or other, along with 5-fold cross-validation. The PST generated a series of images with varying orientations or rotation-invariant scales. Radial frequencies highlighted image structures of different size, and angular frequencies enhanced structures by orientation. Signal-padding helped suppress boundary artifacts but required attention to incidental artifacts. In comparison, the Gabor transform produced more redundant images and the wavelet spectra appeared less spatially smooth than the PST. In addition, the PST demonstrated lower root-mean-square errors than other transforms in denoising and achieved a 93% accuracy for NAWM pixels (296/317), and 88% accuracy for lesion pixels (165/188) in MRI segmentation. The PST is a unique local spectral density-assessing tool which is sensitive to both structure orientations and scales. This may facilitate multiple new applications including advanced characterization of tissue structure in standard MRI. © 2018 International Society for Magnetic Resonance in Medicine.

The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

ERIC Educational Resources Information Center

Bauer, Daniel J.; Curran, Patrick J.

2004-01-01

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

A homogenization-based quasi-discrete method for the fracture of heterogeneous materials

NASA Astrophysics Data System (ADS)

Berke, P. Z.; Peerlings, R. H. J.; Massart, T. J.; Geers, M. G. D.

2014-05-01

The understanding and the prediction of the failure behaviour of materials with pronounced microstructural effects is of crucial importance. This paper presents a novel computational methodology for the handling of fracture on the basis of the microscale behaviour. The basic principles presented here allow the incorporation of an adaptive discretization scheme of the structure as a function of the evolution of strain localization in the underlying microstructure. The proposed quasi-discrete methodology bridges two scales: the scale of the material microstructure, modelled with a continuum type description; and the structural scale, where a discrete description of the material is adopted. The damaging material at the structural scale is divided into unit volumes, called cells, which are represented as a discrete network of points. The scale transition is inspired by computational homogenization techniques; however it does not rely on classical averaging theorems. The structural discrete equilibrium problem is formulated in terms of the underlying fine scale computations. Particular boundary conditions are developed on the scale of the material microstructure to address damage localization problems. The performance of this quasi-discrete method with the enhanced boundary conditions is assessed using different computational test cases. The predictions of the quasi-discrete scheme agree well with reference solutions obtained through direct numerical simulations, both in terms of crack patterns and load versus displacement responses.

Late-onset dietary restriction compensates for age-related increase in oxidative stress and alterations of HSP 70 and synapsin 1 protein levels in male Wistar rats.

PubMed

Sharma, Sandeep; Singh, Rumani; Kaur, Manpreet; Kaur, Gurcharan

2010-04-01

Numerous reports implicate increased oxidative stress in the functional and structural changes occurring in the brain and other organs as a part of the normal aging process. Dietary restriction (DR) has long been shown to be life-prolonging intervention in several species. This study was aimed to assess the potential efficacy of late-onset short term DR when initiated in 21 months old male wistar rats for 3 months on the antioxidant defense system and lipid peroxidation, cellular stress response protein HSP 70 and synaptic marker protein synapsin 1 in discrete brain regions such as cortex, hypothalamus, and hippocampus as well as liver, kidney and heart from 24 month old rats. Age-associated decline in activities of superoxide dismutase, catalase, glutathione peroxidase, glutathione, and elevated levels of lipid peroxidation was observed in brain and peripheral organ as well as increased expression of HSP 70 and reduction in synapsin 1 was observed in brain studied. Late-onset short term DR was effective in partially restoring the antioxidant status and in decreasing lipid peroxidation level as well as enhancing the expression of HSP 70 and synapsin 1 in aged rats. Late onset short term DR also prevented age-related neurodegeneration as revealed by Fluoro-Jade B staining in hippocampus and cortex regions of rat brain. Thus our current results suggest that DR initiated even in old age has the potential to improve age related decline in body functions.

Discrete Structure-Point Testing: Problems and Alternatives. TESL Reporter, Vol. 9, No. 4.

ERIC Educational Resources Information Center

Aitken, Kenneth G.

This paper presents some reasons for reconsidering the use of discrete structure-point tests of language proficiency, and suggests an alternative basis for designing proficiency tests. Discrete point tests are one of the primary tools of the audio-lingual method of teaching a foreign language and are based on certain assumptions, including the…

Lineage-associated tracts defining the anatomy of the Drosophila first instar larval brain

PubMed Central

Hartenstein, Volker; Younossi-Hartenstein, Amelia; Lovick, Jennifer; Kong, Angel; Omoto, Jaison; Ngo, Kathy; Viktorin, Gudrun

2015-01-01

Fixed lineages derived from unique, genetically specified neuroblasts form the anatomical building blocks of the Drosophila brain. Neurons belonging to the same lineage project their axons in a common tract, which is labeled by neuronal markers. In this paper, we present a detailed atlas of the lineage-associated tracts forming the brain of the early Drosophila larva, based on the use of global markers (anti-Neuroglian, anti-Neurotactin, Inscuteable-Gal4>UAS-chRFP-Tub) and lineage-specific reporters. We describe 68 discrete fiber bundles that contain axons of one lineage or pairs/small sets of adjacent lineages. Bundles enter the neuropil at invariant locations, the lineage tract entry portals. Within the neuropil, these fiber bundles form larger fascicles that can be classified, by their main orientation, into longitudinal, transverse, and vertical (ascending/descending) fascicles. We present 3D digital models of lineage tract entry portals and neuropil fascicles, set into relationship to commonly used, easily recognizable reference structures such as the mushroom body, the antennal lobe, the optic lobe, and the Fasciclin II-positive fiber bundles that connect the brain and ventral nerve cord. Correspondences and differences between early larval tract anatomy and the previously described late larval and adult lineage patterns are highlighted. Our L1 neuro-anatomical atlas of lineages constitutes an essential step towards following morphologically defined lineages to the neuroblasts of the early embryo, which will ultimately make it possible to link the structure and connectivity of a lineage to the expression of genes in the particular neuroblast that gives rise to that lineage. Furthermore, the L1 atlas will be important for a host of ongoing work that attempts to reconstruct neuronal connectivity at the level of resolution of single neurons and their synapses. PMID:26141956

Lineage-associated tracts defining the anatomy of the Drosophila first instar larval brain.

PubMed

Hartenstein, Volker; Younossi-Hartenstein, Amelia; Lovick, Jennifer K; Kong, Angel; Omoto, Jaison J; Ngo, Kathy T; Viktorin, Gudrun

2015-10-01

Fixed lineages derived from unique, genetically specified neuroblasts form the anatomical building blocks of the Drosophila brain. Neurons belonging to the same lineage project their axons in a common tract, which is labeled by neuronal markers. In this paper, we present a detailed atlas of the lineage-associated tracts forming the brain of the early Drosophila larva, based on the use of global markers (anti-Neuroglian, anti-Neurotactin, inscuteable-Gal4>UAS-chRFP-Tub) and lineage-specific reporters. We describe 68 discrete fiber bundles that contain axons of one lineage or pairs/small sets of adjacent lineages. Bundles enter the neuropil at invariant locations, the lineage tract entry portals. Within the neuropil, these fiber bundles form larger fascicles that can be classified, by their main orientation, into longitudinal, transverse, and vertical (ascending/descending) fascicles. We present 3D digital models of lineage tract entry portals and neuropil fascicles, set into relationship to commonly used, easily recognizable reference structures such as the mushroom body, the antennal lobe, the optic lobe, and the Fasciclin II-positive fiber bundles that connect the brain and ventral nerve cord. Correspondences and differences between early larval tract anatomy and the previously described late larval and adult lineage patterns are highlighted. Our L1 neuro-anatomical atlas of lineages constitutes an essential step towards following morphologically defined lineages to the neuroblasts of the early embryo, which will ultimately make it possible to link the structure and connectivity of a lineage to the expression of genes in the particular neuroblast that gives rise to that lineage. Furthermore, the L1 atlas will be important for a host of ongoing work that attempts to reconstruct neuronal connectivity at the level of resolution of single neurons and their synapses. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluation of the antagonism of nicotine by mecamylamine and pempidine in the brain

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

Martin, T.J.

1989-01-01

Antagonists have been crucial in the characterization of nicotine's pharmacology. Initial evidence for the existence of central nicotinic receptors was based on the fact that nicotine produced a number of behavioral effects that were antagonized by ganglionic blockers that crossed the blood-brain barrier, such as mecamylamine and pempidine. These compounds are thought to be noncompetitive antagonists due to the fact that they do not compete for agonist binding to brain homogenate in vitro. However, pharmacological evidence in support of noncompetitive antagonism is lacking. Dose-response curves for nicotine were determined in the presence of various doses of pempidine for depression ofmore » spontaneous activity and antinociception in mice. Pempidine was found to shift the dose response curves for these effects of nicotine in a manner consistent with noncompetitive antagonism. A number of mecamylamine analogs were investigated for antagonism of these central effects of nicotine as well. These studies revealed that the N-, 2-, and 3-methyls were crucial for optimal efficacy and potency and suggests that these compounds possess a specific mechanism of action, possibly involving a receptor. Furthermore, the structure-activity relationships for the mecamylamine analogs were found to be different than that previously reported for the agonists, suggesting that they do not act at the same site. The binding of ({sup 3} H)-L-nicotine and ({sup 3}H)-pempidine was studied in vitro to mouse brain homogentate and in situ to rat brain slices. The in situ binding of ({sup 3}H)-L-nicotine to rat brain slices was quantitated autoradiographically to discrete brain areas in the presence and absence of 1, 10 and 100 {mu}M nicotine and pempidine. Pempidine did not effectively displace ({sup 3}H)-L-nicotine binding.« less

Discrete structure of an RNA folding intermediate revealed by cryo-electron microscopy.

PubMed

Baird, Nathan J; Ludtke, Steven J; Khant, Htet; Chiu, Wah; Pan, Tao; Sosnick, Tobin R

2010-11-24

RNA folding occurs via a series of transitions between metastable intermediate states. It is unknown whether folding intermediates are discrete structures folding along defined pathways or heterogeneous ensembles folding along broad landscapes. We use cryo-electron microscopy and single-particle image reconstruction to determine the structure of the major folding intermediate of the specificity domain of a ribonuclease P ribozyme. Our results support the existence of a discrete conformation for this folding intermediate.

Decrease in level of APG-2, a member of the heat shock protein 110 family, in murine brain following systemic administration of kainic acid.

PubMed

Ogita, K; Takagi, R; Oyama, N; Okuda, H; Ito, F; Okui, M; Shimizu, N; Yoneda, Y

2001-09-01

APG-2 belongs to the heat shock protein 110 family. Although kainic acid (KA)-induced seizures are known to elicit expression of inducible heat shock protein 70 (HSP70) in the brain, no investigation has been carried out on the APG-2 level after excitatory amino acid-induced seizures. By means of an immunoblot assay, we determined the levels of HSP70 and APG-2 in discrete brain structures of mice after a single intraperitoneal injection of KA or N-methyl-D-aspartic acid (NMDA). APG-2 level was significantly decreased in frontal cortex, hippocampus, and striatum three days after the administration of KA, while HSP70 level was increased in these regions following the administration. In any of these regions, APG-2 levels were returned to the control levels 10 days after the administration. However, no significant changes were observed in levels of both HSP70 and APG-2 in hypothalamus, midbrain, medulla-pons, and cerebellum of the mice. By contrast, NMDA administration did not significantly affect both levels in any of the regions examined. These findings indicate that the transient decrease in APG-2 expression is one of the intracellular events elicited by signals peculiar to KA, but not by those peculiar to NMDA, in telencephalon of murine brain.

28 CFR 31.102 - State agency structure.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Applicants § 31.102 State agency structure. The State agency may be a discrete unit of State government or a... 28 Judicial Administration 1 2014-07-01 2014-07-01 false State agency structure. 31.102 Section 31... unit of State government. Details of organization and structure are matters of State discretion...

28 CFR 31.102 - State agency structure.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Applicants § 31.102 State agency structure. The State agency may be a discrete unit of State government or a... 28 Judicial Administration 1 2013-07-01 2013-07-01 false State agency structure. 31.102 Section 31... unit of State government. Details of organization and structure are matters of State discretion...

28 CFR 31.102 - State agency structure.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Applicants § 31.102 State agency structure. The State agency may be a discrete unit of State government or a... 28 Judicial Administration 1 2012-07-01 2012-07-01 false State agency structure. 31.102 Section 31... unit of State government. Details of organization and structure are matters of State discretion...

28 CFR 31.102 - State agency structure.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Applicants § 31.102 State agency structure. The State agency may be a discrete unit of State government or a... 28 Judicial Administration 1 2011-07-01 2011-07-01 false State agency structure. 31.102 Section 31... unit of State government. Details of organization and structure are matters of State discretion...

28 CFR 31.102 - State agency structure.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Applicants § 31.102 State agency structure. The State agency may be a discrete unit of State government or a... 28 Judicial Administration 1 2010-07-01 2010-07-01 false State agency structure. 31.102 Section 31... unit of State government. Details of organization and structure are matters of State discretion...

Discrete structures in continuum descriptions of defective crystals

PubMed Central

2016-01-01

I discuss various mathematical constructions that combine together to provide a natural setting for discrete and continuum geometric models of defective crystals. In particular, I provide a quite general list of ‘plastic strain variables’, which quantifies inelastic behaviour, and exhibit rigorous connections between discrete and continuous mathematical structures associated with crystalline materials that have a correspondingly general constitutive specification. PMID:27002070

Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

NASA Astrophysics Data System (ADS)

Sharma, Gaurav; Friedenberg, David A.; Annetta, Nicholas; Glenn, Bradley; Bockbrader, Marcie; Majstorovic, Connor; Domas, Stephanie; Mysiw, W. Jerry; Rezai, Ali; Bouton, Chad

2016-09-01

Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.

Norepinephrine content in discrete brain areas and neurohypophysial vasopressin in rats after a 9-d spaceflight (SLS-1)

NASA Technical Reports Server (NTRS)

Fareh, Jeannette; Cottet-Emard, Jean-Marie; Pequignot, Jean-Marc; Jahns, Gary; Meylor, John; Viso, Michel; Vassaux, Didier; Gauquelin, Guillemette; Gharib, Claude

1993-01-01

The norepinephrine (NE) content in discrete brain areas and the vasopressin content in the neurohypophysial system were assessed in rats after a 9-d spaceflight and after a recovery period. The NE content in the locus coeruleus decreased significantly in spaceflight rats, but showed no difference between control and flight animals after a 9-d recovery. These findings were probably due to an acute stress undergone during landing. The NE content was unchanged in the A2 and A5 cell groups. In rats flown aboard SLS-1, the vasopressin content was increased in the posterior pituitary, and was significantly decreased in the hypothalamus. We conclude that the NE depletion in the locus coeruleus and the alteration in vasopressin release were consistent with an acute stress, likely occurring during and/or after landing. These changes tend to mask the actual neuroendocrine modifications caused by microgravity.

Volition and eye movements.

PubMed

Nachev, Parashkev; Husain, Masud; Kennard, Christopher

2008-01-01

Although the conceptual distinction between voluntary and automatic acts seems intuitively obvious, its neural basis remains opaque. Assigning volition--or some paraphrase such as action selection--to discrete parts of the brain arguably tells us nothing about what volition actually is in neural terms. Equally, exploring the relative sensitivity of discrete brain areas to manipulations of action choice, including its asymptote--free choice--would only be informative if voluntary processes could thereby be reliably isolated. Unfortunately, such manipulations are subject to ineliminable confounds, such as the complexity of the underlying condition-action associations. Here we propose an adaptation of a classic oculomotor task--saccadic choice with asynchronous targets--where the processes engaged in free choice manifest as interference in the performance of an automatic task, thereby circumventing the difficulties in parameterising volition. We suggest that this task may be useful in probing deficits in voluntary action in pathological states.

Sheet Probability Index (SPI): Characterizing the geometrical organization of the white matter with diffusion MRI

PubMed Central

Tax, Chantal M.W.; Haije, Tom Dela; Fuster, Andrea; Westin, Carl-Fredrik; Viergever, Max A.; Florack, Luc; Leemans, Alexander

2017-01-01

The question whether our brain pathways adhere to a geometric grid structure has been a popular topic of debate in the diffusion imaging and neuroscience society. Wedeen et al. (2012a b) proposed that the brain’s white matter is organized like parallel sheets of interwoven pathways. Catani et al. (2012) concluded that this grid pattern is most likely an artifact, resulting from methodological biases that cause the tractography pathways to cross in orthogonal angles. To date, ambiguities in the mathematical conditions for a sheet structure to exist (e.g. its relation to orthogonal angles) combined with the lack of extensive quantitative evidence have prevented wide acceptance of the hypothesis. In this work, we formalize the relevant terminology and recapitulate the condition for a sheet structure to exist. Note that this condition is not related to the presence or absence of orthogonal crossing fibers, and that sheet structure is defined formally as a surface formed by two sets of interwoven pathways intersecting at arbitrary angles within the surface. To quantify the existence of sheet structure, we present a novel framework to compute the sheet probability index (SPI), which reflects the presence of sheet structure in discrete orientation data (e.g. fiber peaks derived from diffusion MRI). With simulation experiments we investigate the effect of spatial resolution, curvature of the fiber pathways, and measurement noise on the ability to detect sheet structure. In real diffusion MRI data experiments we can identify various regions where the data supports sheet structure (high SPI values), but also areas where the data does not support sheet structure (low SPI values) or where no reliable conclusion can be drawn. Several areas with high SPI values were found to be consistent across subjects, across multiple data sets obtained with different scanners, resolutions, and degrees of diffusion weighting, and across various modeling techniques. Under the strong assumption that the diffusion MRI peaks reflect true axons, our results would therefore indicate that pathways do not form sheet structures at every crossing fiber region but instead at well-defined locations in the brain. With this framework, sheet structure location, extent, and orientation could potentially serve as new structural features of brain tissue. The proposed method can be extended to quantify sheet structure in directional data obtained with techniques other than diffusion MRI, which is essential for further validation. PMID:27456538

RINGMesh: A programming library for developing mesh-based geomodeling applications

NASA Astrophysics Data System (ADS)

Pellerin, Jeanne; Botella, Arnaud; Bonneau, François; Mazuyer, Antoine; Chauvin, Benjamin; Lévy, Bruno; Caumon, Guillaume

2017-07-01

RINGMesh is a C++ open-source programming library for manipulating discretized geological models. It is designed to ease the development of applications and workflows that use discretized 3D models. It is neither a geomodeler, nor a meshing software. RINGMesh implements functionalities to read discretized surface-based or volumetric structural models and to check their validity. The models can be then exported in various file formats. RINGMesh provides data structures to represent geological structural models, either defined by their discretized boundary surfaces, and/or by discretized volumes. A programming interface allows to develop of new geomodeling methods, and to plug in external software. The goal of RINGMesh is to help researchers to focus on the implementation of their specific method rather than on tedious tasks common to many applications. The documented code is open-source and distributed under the modified BSD license. It is available at https://www.ring-team.org/index.php/software/ringmesh.

Regulation of cellular plasticity and resilience by mood stabilizers: the role of AMPA receptor trafficking

PubMed Central

Du, Jing; Quiroz, Jorge A.; Gray, Neil A.; Szabo, Steve T.; Zarate Jr, Carlos A.; Manji, Husseini K.

2004-01-01

There is increasing evidence from a variety of sources that severe mood disorders are associated with regional reductions in brain volume, as well as reductions in the number, size, and density of glia and neurons in discrete brain areas. Although the precise pathophysiology underlying these morphometric changes remains to be fully elucidated, the data suggest that severe mood disorders are associated with impairments of structural plasticity and cellular resilience. In this context, it is noteworthy that a growing body of data suggests that the glutamaiergic system (which is known to play a major role in neuronal plasticity and cellular resilience) may be involved in the pathophysiology and treatment of mood disorders. Glutamate α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) GluR1 receptor trafficking plays a critical role in regulating various forms of neural plasticity. It is thus noteworthy that recent studies have shown that structurally dissimilar mood stabilizers lithium and valproate regulate GluR1 receptor subunit trafficking and localization at synapses. These studies suggest that regulation of glutamatergically mediated synaptic plasticity may play a role in the treatment of mood disorders, and raises the possibility that agents more directly affecting synaptic GluR1 represent novel therapies for these devastating illnesses. PMID:22034247

Aging Neural Progenitor Cells Have Decreased Mitochondrial Content and Lower Oxidative Metabolism*

PubMed Central

Stoll, Elizabeth A.; Cheung, Willy; Mikheev, Andrei M.; Sweet, Ian R.; Bielas, Jason H.; Zhang, Jing; Rostomily, Robert C.; Horner, Philip J.

2011-01-01

Although neurogenesis occurs in discrete areas of the adult mammalian brain, neural progenitor cells (NPCs) produce fewer new neurons with age. To characterize the molecular changes that occur during aging, we performed a proteomic comparison between primary-cultured NPCs from the young adult and aged mouse forebrain. This analysis yielded changes in proteins necessary for cellular metabolism. Mitochondrial quantity and oxygen consumption rates decrease with aging, although mitochondrial DNA in aged NPCs does not have increased mutation rates. In addition, aged cells are resistant to the mitochondrial inhibitor rotenone and proliferate in response to lowered oxygen conditions. These results demonstrate that aging NPCs display an altered metabolic phenotype, characterized by a coordinated shift in protein expression, subcellular structure, and metabolic physiology. PMID:21900249

Nonparametric weighted stochastic block models

NASA Astrophysics Data System (ADS)

Peixoto, Tiago P.

2018-01-01

We present a Bayesian formulation of weighted stochastic block models that can be used to infer the large-scale modular structure of weighted networks, including their hierarchical organization. Our method is nonparametric, and thus does not require the prior knowledge of the number of groups or other dimensions of the model, which are instead inferred from data. We give a comprehensive treatment of different kinds of edge weights (i.e., continuous or discrete, signed or unsigned, bounded or unbounded), as well as arbitrary weight transformations, and describe an unsupervised model selection approach to choose the best network description. We illustrate the application of our method to a variety of empirical weighted networks, such as global migrations, voting patterns in congress, and neural connections in the human brain.

Discrete structures in continuum descriptions of defective crystals.

PubMed

Parry, G P

2016-04-28

I discuss various mathematical constructions that combine together to provide a natural setting for discrete and continuum geometric models of defective crystals. In particular, I provide a quite general list of 'plastic strain variables', which quantifies inelastic behaviour, and exhibit rigorous connections between discrete and continuous mathematical structures associated with crystalline materials that have a correspondingly general constitutive specification. © 2016 The Author(s).

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

PubMed Central

Prerau, Michael J.; Brown, Ritchie E.; Bianchi, Matt T.; Ellenbogen, Jeffrey M.; Purdon, Patrick L.

2016-01-01

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible—elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications. PMID:27927806

Graph Frequency Analysis of Brain Signals

PubMed Central

Huang, Weiyu; Goldsberry, Leah; Wymbs, Nicholas F.; Grafton, Scott T.; Bassett, Danielle S.; Ribeiro, Alejandro

2016-01-01

This paper presents methods to analyze functional brain networks and signals from graph spectral perspectives. The notion of frequency and filters traditionally defined for signals supported on regular domains such as discrete time and image grids has been recently generalized to irregular graph domains, and defines brain graph frequencies associated with different levels of spatial smoothness across the brain regions. Brain network frequency also enables the decomposition of brain signals into pieces corresponding to smooth or rapid variations. We relate graph frequency with principal component analysis when the networks of interest denote functional connectivity. The methods are utilized to analyze brain networks and signals as subjects master a simple motor skill. We observe that brain signals corresponding to different graph frequencies exhibit different levels of adaptability throughout learning. Further, we notice a strong association between graph spectral properties of brain networks and the level of exposure to tasks performed, and recognize the most contributing and important frequency signatures at different levels of task familiarity. PMID:28439325

Discrete-continuous variable structural synthesis using dual methods

NASA Technical Reports Server (NTRS)

Schmit, L. A.; Fleury, C.

1980-01-01

Approximation concepts and dual methods are extended to solve structural synthesis problems involving a mix of discrete and continuous sizing type of design variables. Pure discrete and pure continuous variable problems can be handled as special cases. The basic mathematical programming statement of the structural synthesis problem is converted into a sequence of explicit approximate primal problems of separable form. These problems are solved by constructing continuous explicit dual functions, which are maximized subject to simple nonnegativity constraints on the dual variables. A newly devised gradient projection type of algorithm called DUAL 1, which includes special features for handling dual function gradient discontinuities that arise from the discrete primal variables, is used to find the solution of each dual problem. Computational implementation is accomplished by incorporating the DUAL 1 algorithm into the ACCESS 3 program as a new optimizer option. The power of the method set forth is demonstrated by presenting numerical results for several example problems, including a pure discrete variable treatment of a metallic swept wing and a mixed discrete-continuous variable solution for a thin delta wing with fiber composite skins.

Integrable structure in discrete shell membrane theory

PubMed Central

Schief, W. K.

2014-01-01

We present natural discrete analogues of two integrable classes of shell membranes. By construction, these discrete shell membranes are in equilibrium with respect to suitably chosen internal stresses and external forces. The integrability of the underlying equilibrium equations is proved by relating the geometry of the discrete shell membranes to discrete O surface theory. We establish connections with generalized barycentric coordinates and nine-point centres and identify a discrete version of the classical Gauss equation of surface theory. PMID:24808755

Integrable structure in discrete shell membrane theory.

PubMed

Schief, W K

2014-05-08

We present natural discrete analogues of two integrable classes of shell membranes. By construction, these discrete shell membranes are in equilibrium with respect to suitably chosen internal stresses and external forces. The integrability of the underlying equilibrium equations is proved by relating the geometry of the discrete shell membranes to discrete O surface theory. We establish connections with generalized barycentric coordinates and nine-point centres and identify a discrete version of the classical Gauss equation of surface theory.

Hybrid ICA-Bayesian network approach reveals distinct effective connectivity differences in schizophrenia.

PubMed

Kim, D; Burge, J; Lane, T; Pearlson, G D; Kiehl, K A; Calhoun, V D

2008-10-01

We utilized a discrete dynamic Bayesian network (dDBN) approach (Burge, J., Lane, T., Link, H., Qiu, S., Clark, V.P., 2007. Discrete dynamic Bayesian network analysis of fMRI data. Hum Brain Mapp.) to determine differences in brain regions between patients with schizophrenia and healthy controls on a measure of effective connectivity, termed the approximate conditional likelihood score (ACL) (Burge, J., Lane, T., 2005. Learning Class-Discriminative Dynamic Bayesian Networks. Proceedings of the International Conference on Machine Learning, Bonn, Germany, pp. 97-104.). The ACL score represents a class-discriminative measure of effective connectivity by measuring the relative likelihood of the correlation between brain regions in one group versus another. The algorithm is capable of finding non-linear relationships between brain regions because it uses discrete rather than continuous values and attempts to model temporal relationships with a first-order Markov and stationary assumption constraint (Papoulis, A., 1991. Probability, random variables, and stochastic processes. McGraw-Hill, New York.). Since Bayesian networks are overly sensitive to noisy data, we introduced an independent component analysis (ICA) filtering approach that attempted to reduce the noise found in fMRI data by unmixing the raw datasets into a set of independent spatial component maps. Components that represented noise were removed and the remaining components reconstructed into the dimensions of the original fMRI datasets. We applied the dDBN algorithm to a group of 35 patients with schizophrenia and 35 matched healthy controls using an ICA filtered and unfiltered approach. We determined that filtering the data significantly improved the magnitude of the ACL score. Patients showed the greatest ACL scores in several regions, most markedly the cerebellar vermis and hemispheres. Our findings suggest that schizophrenia patients exhibit weaker connectivity than healthy controls in multiple regions, including bilateral temporal, frontal, and cerebellar regions during an auditory paradigm.

An assisted navigation training framework based on judgment theory using sparse and discrete human-machine interfaces.

PubMed

Lopes, Ana C; Nunes, Urbano

2009-01-01

This paper aims to present a new framework to train people with severe motor disabilities steering an assisted mobile robot (AMR), such as a powered wheelchair. Users with high level of motor disabilities are not able to use standard HMIs, which provide a continuous command signal (e. g. standard joystick). For this reason HMIs providing a small set of simple commands, which are sparse and discrete in time must be used (e. g. scanning interface, or brain computer interface), making very difficult to steer the AMR. In this sense, the assisted navigation training framework (ANTF) is designed to train users driving the AMR, in indoor structured environments, using this type of HMIs. Additionally it provides user characterization on steering the robot, which will later be used to adapt the AMR navigation system to human competence steering the AMR. A rule-based lens (RBL) model is used to characterize users on driving the AMR. Individual judgment performance choosing the best manoeuvres is modeled using a genetic-based policy capturing (GBPC) technique characterized to infer non-compensatory judgment strategies from human decision data. Three user models, at three different learning stages, using the RBL paradigm, are presented.

Fluoride toxicity and status of serum thyroid hormones, brain histopathology, and learning memory in rats: a multigenerational assessment.

PubMed

Basha, Piler Mahaboob; Rai, Puja; Begum, Shabana

2011-12-01

High-fluoride (100 and 200 ppm) water was administered to rats orally to study the fluoride-induced changes on the thyroid hormone status, the histopathology of discrete brain regions, the acetylcholine esterase activity, and the learning and memory abilities in multigeneration rats. Significant decrease in the serum-free thyroxine (FT4) and free triiodothyronine (FT3) levels and decrease in acetylcholine esterase activity in fluoride-treated group were observed. Presence of eosinophilic Purkinje cells, degenerating neurons, decreased granular cells, and vacuolations were noted in discrete brain regions of the fluoride-treated group. In the T-maze experiments, the fluoride-treated group showed poor acquisition and retention and higher latency when compared with the control. The alterations were more profound in the third generation when compared with the first- and second-generation fluoride-treated group. Changes in the thyroid hormone levels in the present study might have imbalanced the oxidant/antioxidant system, which further led to a reduction in learning memory ability. Hence, presence of generational or cumulative effects of fluoride on the development of the offspring when it is ingested continuously through multiple generations is evident from the present study.

Nonsomatotopic organization of the higher motor centers in octopus.

PubMed

Zullo, Letizia; Sumbre, German; Agnisola, Claudio; Flash, Tamar; Hochner, Binyamin

2009-10-13

Hyperredundant limbs with a virtually unlimited number of degrees of freedom (DOFs) pose a challenge for both biological and computational systems of motor control. In the flexible arms of the octopus, simplification strategies have evolved to reduce the number of controlled DOFs. Motor control in the octopus nervous system is hierarchically organized. A relatively small central brain integrates a huge amount of visual and tactile information from the large optic lobes and the peripheral nervous system of the arms and issues commands to lower motor centers controlling the elaborated neuromuscular system of the arms. This unique organization raises new questions on the organization of the octopus brain and whether and how it represents the rich movement repertoire. We developed a method of brain microstimulation in freely behaving animals and stimulated the higher motor centers-the basal lobes-thus inducing discrete and complex sets of movements. As stimulation strength increased, complex movements were recruited from basic components shared by different types of movement. We found no stimulation site where movements of a single arm or body part could be elicited. Discrete and complex components have no central topographical organization but are distributed over wide regions.

Predicting Outcome after Pediatric Traumatic Brain Injury by Early Magnetic Resonance Imaging Lesion Location and Volume

PubMed Central

Smitherman, Emily; Hernandez, Ana; Stavinoha, Peter L.; Huang, Rong; Kernie, Steven G.; Diaz-Arrastia, Ramon

2016-01-01

Abstract Brain lesions after traumatic brain injury (TBI) are heterogeneous, rendering outcome prognostication difficult. The aim of this study is to investigate whether early magnetic resonance imaging (MRI) of lesion location and lesion volume within discrete brain anatomical zones can accurately predict long-term neurological outcome in children post-TBI. Fluid-attenuated inversion recovery (FLAIR) MRI hyperintense lesions in 63 children obtained 6.2±5.6 days postinjury were correlated with the Glasgow Outcome Scale Extended-Pediatrics (GOS-E Peds) score at 13.5±8.6 months. FLAIR lesion volume was expressed as hyperintensity lesion volume index (HLVI)=(hyperintensity lesion volume / whole brain volume)×100 measured within three brain zones: zone A (cortical structures); zone B (basal ganglia, corpus callosum, internal capsule, and thalamus); and zone C (brainstem). HLVI-total and HLVI-zone C predicted good and poor outcome groups (p<0.05). GOS-E Peds correlated with HLVI-total (r=0.39; p=0.002) and HLVI in all three zones: zone A (r=0.31; p<0.02); zone B (r=0.35; p=0.004); and zone C (r=0.37; p=0.003). In adolescents ages 13–17 years, HLVI-total correlated best with outcome (r=0.5; p=0.007), whereas in younger children under the age of 13, HLVI-zone B correlated best (r=0.52; p=0.001). Compared to patients with lesions in zone A alone or in zones A and B, patients with lesions in all three zones had a significantly higher odds ratio (4.38; 95% confidence interval, 1.19–16.0) for developing an unfavorable outcome. PMID:25808802

Advanced biomaterial strategies to transplant preformed micro-tissue engineered neural networks into the brain

NASA Astrophysics Data System (ADS)

Harris, J. P.; Struzyna, L. A.; Murphy, P. L.; Adewole, D. O.; Kuo, E.; Cullen, D. K.

2016-02-01

Objective. Connectome disruption is a hallmark of many neurological diseases and trauma with no current strategies to restore lost long-distance axonal pathways in the brain. We are creating transplantable micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of embedded neurons and long axonal tracts to integrate with the nervous system to physically reconstitute lost axonal pathways. Approach. We advanced micro-tissue engineering techniques to generate micro-TENNs consisting of discrete populations of mature primary cerebral cortical neurons spanned by long axonal fascicles encased in miniature hydrogel micro-columns. Further, we improved the biomaterial encasement scheme by adding a thin layer of low viscosity carboxymethylcellulose (CMC) to enable needle-less insertion and rapid softening for mechanical similarity with brain tissue. Main results. The engineered architecture of cortical micro-TENNs facilitated robust neuronal viability and axonal cytoarchitecture to at least 22 days in vitro. Micro-TENNs displayed discrete neuronal populations spanned by long axonal fasciculation throughout the core, thus mimicking the general systems-level anatomy of gray matter—white matter in the brain. Additionally, micro-columns with thin CMC-coating upon mild dehydration were able to withstand a force of 893 ± 457 mN before buckling, whereas a solid agarose cylinder of similar dimensions was predicted to withstand less than 150 μN of force. This thin CMC coating increased the stiffness by three orders of magnitude, enabling needle-less insertion into brain while significantly reducing the footprint of previous needle-based delivery methods to minimize insertion trauma. Significance. Our novel micro-TENNs are the first strategy designed for minimally invasive implantation to facilitate nervous system repair by simultaneously providing neuronal replacement and physical reconstruction of long-distance axon pathways in the brain. The micro-TENN approach may offer the ability to treat several disorders that disrupt the connectome, including Parkinson’s disease, traumatic brain injury, stroke, and brain tumor excision.

Advanced biomaterial strategies to transplant preformed micro-tissue engineered neural networks into the brain

PubMed Central

Harris, J P; Struzyna, L A; Murphy, P L; Adewole, D O; Kuo, E; Cullen, D K

2017-01-01

Objective Connectome disruption is a hallmark of many neurological diseases and trauma with no current strategies to restore lost long-distance axonal pathways in the brain. We are creating transplantable micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of embedded neurons and long axonal tracts to integrate with the nervous system to physically reconstitute lost axonal pathways. Approach We advanced micro-tissue engineering techniques to generate micro-TENNs consisting of discrete populations of mature primary cerebral cortical neurons spanned by long axonal fascicles encased in miniature hydrogel micro-columns. Further, we improved the biomaterial encasement scheme by adding a thin layer of low viscosity carboxymethylcellulose (CMC) to enable needle-less insertion and rapid softening for mechanical similarity with brain tissue. Main results The engineered architecture of cortical micro-TENNs facilitated robust neuronal viability and axonal cytoarchitecture to at least 22 days in vitro. Micro-TENNs displayed discrete neuronal populations spanned by long axonal fasciculation throughout the core, thus mimicking the general systems-level anatomy of gray matter—white matter in the brain. Additionally, micro columns with thin CMC-coating upon mild dehydration were able to withstand a force of 893 ± 457 mN before buckling, whereas a solid agarose cylinder of similar dimensions was predicted to withstand less than 150 μN of force. This thin CMC coating increased the stiffness by three orders of magnitude, enabling needle-less insertion into brain while significantly reducing the footprint of previous needle-based delivery methods to minimize insertion trauma. Significance Our novel micro-TENNs are the first strategy designed for minimally invasive implantation to facilitate nervous system repair by simultaneously providing neuronal replacement and physical reconstruction of long-distance axon pathways in the brain. The micro-TENN approach may offer the ability to treat several disorders that disrupt the connectome, including Parkinson’s disease, traumatic brain injury, stroke, and brain tumor excision PMID:26760138

Developmental and Regional Patterns of GAP-43 Immunoreactivity in a Metamorphosing Brain

PubMed Central

Simmons, Andrea Megela; Tanyu, Leslie H.; Horowitz, Seth S.; Chapman, Judith A.; Brown, Rebecca A.

2012-01-01

Growth-associated protein-43 is typically expressed at high levels in the nervous system during development. In adult animals, its expression is lower, but still observable in brain areas showing structural or functional plasticity. We examined patterns of GAP-43 immunoreactivity in the brain of the bullfrog, an animal whose nervous system undergoes considerable reorganization across metamorphic development and retains a strong capacity for plasticity in adulthood. Immunolabeling was mostly diffuse in hatchling tadpoles, but became progressively more discrete as larval development proceeded. In many brain areas, intensity of immunolabel peaked at metamorphic climax, the time of final transition from aquatic to semi-terrestrial life. Changes in intensity of GAP-43 expression in the medial vestibular nucleus, superior olivary nucleus, and torus semicircularis appeared correlated with stage-dependent functional changes in processing auditory stimuli. Immunolabeling in the Purkinje cell layer of the cerebellum and in the cerebellar nucleus was detectable at most developmental time points. Heavy immunolabel was present from early larval stages through the end of climax in the thalamus (ventromedial, anterior, posterior, central nuclei). Immunolabel in the tadpole telencephalon was observed around the lateral ventricles, and in the medial septum and ventral striatum. In postmetamorphic animals, immunoreactivity was confined mainly to the ventricular zones and immediately adjacent cell layers. GAP-43 expression was present in olfactory, auditory and optic cranial nerves throughout larval and postmetamorphic life. The continued expression of GAP-43 in brain nuclei and in cranial nerves throughout development and into adulthood reflects the high regenerative potential of the bullfrog’s central nervous system. PMID:18431052

A New Ghost Cell/Level Set Method for Moving Boundary Problems: Application to Tumor Growth

PubMed Central

Macklin, Paul

2011-01-01

In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics—an effect observed in real tumor growth. PMID:21331304

Discrete shaped strain sensors for intelligent structures

NASA Technical Reports Server (NTRS)

Andersson, Mark S.; Crawley, Edward F.

1992-01-01

Design of discrete, highly distributed sensor systems for intelligent structures has been studied. Data obtained indicate that discrete strain-averaging sensors satisfy the functional requirements for distributed sensing of intelligent structures. Bartlett and Gauss-Hanning sensors, in particular, provide good wavenumber characteristics while meeting the functional requirements. They are characterized by good rolloff rates and positive Fourier transforms for all wavenumbers. For the numerical integration schemes, Simpson's rule is considered to be very simple to implement and consistently provides accurate results for five sensors or more. It is shown that a sensor system that satisfies the functional requirements can be applied to a structure that supports mode shapes with purely sinusoidal curvature.

Functional connectivity dynamics: modeling the switching behavior of the resting state.

PubMed

Hansen, Enrique C A; Battaglia, Demian; Spiegler, Andreas; Deco, Gustavo; Jirsa, Viktor K

2015-01-15

Functional connectivity (FC) sheds light on the interactions between different brain regions. Besides basic research, it is clinically relevant for applications in Alzheimer's disease, schizophrenia, presurgical planning, epilepsy, and traumatic brain injury. Simulations of whole-brain mean-field computational models with realistic connectivity determined by tractography studies enable us to reproduce with accuracy aspects of average FC in the resting state. Most computational studies, however, did not address the prominent non-stationarity in resting state FC, which may result in large intra- and inter-subject variability and thus preclude an accurate individual predictability. Here we show that this non-stationarity reveals a rich structure, characterized by rapid transitions switching between a few discrete FC states. We also show that computational models optimized to fit time-averaged FC do not reproduce these spontaneous state transitions and, thus, are not qualitatively superior to simplified linear stochastic models, which account for the effects of structure alone. We then demonstrate that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks. Because of the noise-driven exploration of this repertoire, the dynamics of FC qualitatively change now and display non-stationary switching similar to empirical resting state recordings (Functional Connectivity Dynamics (FCD)). Thus FCD bear promise to serve as a better biomarker of resting state neural activity and of its pathologic alterations. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Appearance of the canine meninges in subtraction magnetic resonance images.

PubMed

Lamb, Christopher R; Lam, Richard; Keenihan, Erin K; Frean, Stephen

2014-01-01

The canine meninges are not visible as discrete structures in noncontrast magnetic resonance (MR) images, and are incompletely visualized in T1-weighted, postgadolinium images, reportedly appearing as short, thin curvilinear segments with minimal enhancement. Subtraction imaging facilitates detection of enhancement of tissues, hence may increase the conspicuity of meninges. The aim of the present study was to describe qualitatively the appearance of canine meninges in subtraction MR images obtained using a dynamic technique. Images were reviewed of 10 consecutive dogs that had dynamic pre- and postgadolinium T1W imaging of the brain that was interpreted as normal, and had normal cerebrospinal fluid. Image-anatomic correlation was facilitated by dissection and histologic examination of two canine cadavers. Meningeal enhancement was relatively inconspicuous in postgadolinium T1-weighted images, but was clearly visible in subtraction images of all dogs. Enhancement was visible as faint, small-rounded foci compatible with vessels seen end on within the sulci, a series of larger rounded foci compatible with vessels of variable caliber on the dorsal aspect of the cerebral cortex, and a continuous thin zone of moderate enhancement around the brain. Superimposition of color-encoded subtraction images on pregadolinium T1- and T2-weighted images facilitated localization of the origin of enhancement, which appeared to be predominantly dural, with relatively few leptomeningeal structures visible. Dynamic subtraction MR imaging should be considered for inclusion in clinical brain MR protocols because of the possibility that its use may increase sensitivity for lesions affecting the meninges. © 2014 American College of Veterinary Radiology.

A microPET comparison of the effects of etifoxine and diazepam on [(11)C]flumazenil uptake in rat brains.

PubMed

Bouillot, Caroline; Bonnefoi, Frédéric; Liger, François; Zimmer, Luc

2016-01-26

Using positron emission tomography (PET), the present study assessed the binding of [(11)C]flumazenil to GABA-A receptors in anesthetized rats following a single intravenous injection of an active dose of either etifoxine (25mg/kg) or diazepam (1mg/kg), which are both anxiolytic drugs. [(11)C]flumazenil binding was measured in five discrete brain structures, namely the caudate putamen, hippocampus, cerebellum, occipital cortex and parietal cortex. As expected, diazepam injection produced a significant decrease in [(11)C]flumazenil binding, which was interpreted as benzodiazepine GABA-A receptor occupancy, whereas etifoxine increased the binding of [(11)C]flumazenil. This first use of in vivo imaging after etifoxine administration revealed the activated binding pattern of [(11)C]flumazenil and highlighted the pharmacological differences between etifoxine and benzodiazepines. Using the same [(11)C]flumazenil radiotracer, PET neuroimaging could be applied to larger animals and, ultimately, to human subjects, thus providing new perspectives for better defining the molecular pharmacology of etifoxine. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

PubMed Central

Jones, Michael N.

2017-01-01

A central goal of cognitive neuroscience is to decode human brain activity—that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive—that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model—Generalized Correspondence Latent Dirichlet Allocation—that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text—enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity. PMID:29059185

Protein structure-structure alignment with discrete Fréchet distance.

PubMed

Jiang, Minghui; Xu, Ying; Zhu, Binhai

2008-02-01

Matching two geometric objects in two-dimensional (2D) and three-dimensional (3D) spaces is a central problem in computer vision, pattern recognition, and protein structure prediction. In particular, the problem of aligning two polygonal chains under translation and rotation to minimize their distance has been studied using various distance measures. It is well known that the Hausdorff distance is useful for matching two point sets, and that the Fréchet distance is a superior measure for matching two polygonal chains. The discrete Fréchet distance closely approximates the (continuous) Fréchet distance, and is a natural measure for the geometric similarity of the folded 3D structures of biomolecules such as proteins. In this paper, we present new algorithms for matching two polygonal chains in two dimensions to minimize their discrete Fréchet distance under translation and rotation, and an effective heuristic for matching two polygonal chains in three dimensions. We also describe our empirical results on the application of the discrete Fréchet distance to protein structure-structure alignment.

Modafinil Reverses Phencyclidine-Induced Deficits in Cognitive Flexibility, Cerebral Metabolism, and Functional Brain Connectivity

PubMed Central

Dawson, Neil; Thompson, Rhiannon J.; McVie, Allan; Thomson, David M.; Morris, Brian J.; Pratt, Judith A.

2012-01-01

Objective: In the present study, we employ mathematical modeling (partial least squares regression, PLSR) to elucidate the functional connectivity signatures of discrete brain regions in order to identify the functional networks subserving PCP-induced disruption of distinct cognitive functions and their restoration by the procognitive drug modafinil. Methods: We examine the functional connectivity signatures of discrete brain regions that show overt alterations in metabolism, as measured by semiquantitative 2-deoxyglucose autoradiography, in an animal model (subchronic phencyclidine [PCP] treatment), which shows cognitive inflexibility with relevance to the cognitive deficits seen in schizophrenia. Results: We identify the specific components of functional connectivity that contribute to the rescue of this cognitive inflexibility and to the restoration of overt cerebral metabolism by modafinil. We demonstrate that modafinil reversed both the PCP-induced deficit in the ability to switch attentional set and the PCP-induced hypometabolism in the prefrontal (anterior prelimbic) and retrosplenial cortices. Furthermore, modafinil selectively enhanced metabolism in the medial prelimbic cortex. The functional connectivity signatures of these regions identified a unifying functional subsystem underlying the influence of modafinil on cerebral metabolism and cognitive flexibility that included the nucleus accumbens core and locus coeruleus. In addition, these functional connectivity signatures identified coupling events specific to each brain region, which relate to known anatomical connectivity. Conclusions: These data support clinical evidence that modafinil may alleviate cognitive deficits in schizophrenia and also demonstrate the benefit of applying PLSR modeling to characterize functional brain networks in translational models relevant to central nervous system dysfunction. PMID:20810469

Dendrites are dispensable for basic motoneuron function but essential for fine tuning of behavior.

PubMed

Ryglewski, Stefanie; Kadas, Dimitrios; Hutchinson, Katie; Schuetzler, Natalie; Vonhoff, Fernando; Duch, Carsten

2014-12-16

Dendrites are highly complex 3D structures that define neuronal morphology and connectivity and are the predominant sites for synaptic input. Defects in dendritic structure are highly consistent correlates of brain diseases. However, the precise consequences of dendritic structure defects for neuronal function and behavioral performance remain unknown. Here we probe dendritic function by using genetic tools to selectively abolish dendrites in identified Drosophila wing motoneurons without affecting other neuronal properties. We find that these motoneuron dendrites are unexpectedly dispensable for synaptic targeting, qualitatively normal neuronal activity patterns during behavior, and basic behavioral performance. However, significant performance deficits in sophisticated motor behaviors, such as flight altitude control and switching between discrete courtship song elements, scale with the degree of dendritic defect. To our knowledge, our observations provide the first direct evidence that complex dendrite architecture is critically required for fine-tuning and adaptability within robust, evolutionarily constrained behavioral programs that are vital for mating success and survival. We speculate that the observed scaling of performance deficits with the degree of structural defect is consistent with gradual increases in intellectual disability during continuously advancing structural deficiencies in progressive neurological disorders.

Digital Material Assembly by Passive Means and Modular Isotropic Lattice Extruder System

NASA Technical Reports Server (NTRS)

Gershenfeld, Neil (Inventor); Carney, Matthew Eli (Inventor); Jenett, Benjamin (Inventor)

2017-01-01

A set of machines and related systems build structures by the additive assembly of discrete parts. These digital material assemblies constrain the constituent parts to a discrete set of possible positions and orientations. In doing so, the structures exhibit many of the properties inherent in digital communication such as error correction, fault tolerance and allow the assembly of precise structures with comparatively imprecise tools. Assembly of discrete cellular lattices by a Modular Isotropic Lattice Extruder System (MILES) is implemented by pulling strings of lattice elements through a forming die that enforces geometry constraints that lock the elements into a rigid structure that can then be pushed against and extruded out of the die as an assembled, loadbearing structure.

Evolvable Neuronal Paths: A Novel Basis for Information and Search in the Brain

PubMed Central

Fernando, Chrisantha; Vasas, Vera; Szathmáry, Eörs; Husbands, Phil

2011-01-01

We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques) which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard ‘genetic’ informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA) is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain. PMID:21887266

Global loss of acetylcholinesterase activity with mitochondrial complexes inhibition and inflammation in brain of hypercholesterolemic mice.

PubMed

Paul, Rajib; Borah, Anupom

2017-12-20

There exists an intricate relationship between hypercholesterolemia (elevated plasma cholesterol) and brain functions. The present study aims to understand the impact of hypercholesterolemia on pathological consequences in mouse brain. A chronic mouse model of hypercholesterolemia was induced by giving high-cholesterol diet for 12 weeks. The hypercholesterolemic mice developed cognitive impairment as evident from object recognition memory test. Cholesterol accumulation was observed in four discrete brain regions, such as cortex, striatum, hippocampus and substantia nigra along with significantly damaged blood-brain barrier by hypercholesterolemia. The crucial finding is the loss of acetylcholinesterase activity with mitochondrial dysfunction globally in the brain of hypercholesterolemic mice, which is related to the levels of cholesterol. Moreover, the levels of hydroxyl radical were elevated in the regions of brain where the activity of mitochondrial complexes was found to be reduced. Intriguingly, elevations of inflammatory stress markers in the cholesterol-rich brain regions were observed. As cognitive impairment, diminished brain acetylcholinesterase activity, mitochondrial dysfunctions, and inflammation are the prima facie pathologies of neurodegenerative diseases, the findings impose hypercholesterolemia as potential risk factor towards brain dysfunction.

Algebraic perturbation theory for dense liquids with discrete potentials

NASA Astrophysics Data System (ADS)

Adib, Artur B.

2007-06-01

A simple theory for the leading-order correction g1(r) to the structure of a hard-sphere liquid with discrete (e.g., square-well) potential perturbations is proposed. The theory makes use of a general approximation that effectively eliminates four-particle correlations from g1(r) with good accuracy at high densities. For the particular case of discrete perturbations, the remaining three-particle correlations can be modeled with a simple volume-exclusion argument, resulting in an algebraic and surprisingly accurate expression for g1(r) . The structure of a discrete “core-softened” model for liquids with anomalous thermodynamic properties is reproduced as an application.

Sentient Structures: Optimising Sensor Layouts for Direct Measurement of Discrete Variables

DTIC Science & Technology

2008-11-01

1 Sentient Structures Optimising Sensor Layouts for Direct Measurement of Discrete Variables Report to US Air Force...TITLE AND SUBTITLE Sentient Structures 5a. CONTRACT NUMBER FA48690714045 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Donald Price...optimal sensor placements is an important requirement for the development of sentient structures. An optimal sensor layout is attained when a limited

Fermion Systems in Discrete Space-Time Exemplifying the Spontaneous Generation of a Causal Structure

NASA Astrophysics Data System (ADS)

Diethert, A.; Finster, F.; Schiefeneder, D.

As toy models for space-time at the Planck scale, we consider examples of fermion systems in discrete space-time which are composed of one or two particles defined on two up to nine space-time points. We study the self-organization of the particles as described by a variational principle both analytically and numerically. We find an effect of spontaneous symmetry breaking which leads to the emergence of a discrete causal structure.

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

PubMed Central

Sharma, Gaurav; Friedenberg, David A.; Annetta, Nicholas; Glenn, Bradley; Bockbrader, Marcie; Majstorovic, Connor; Domas, Stephanie; Mysiw, W. Jerry; Rezai, Ali; Bouton, Chad

2016-01-01

Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis. PMID:27658585

Nonlinear Light Dynamics in Multi-Core Structures

DTIC Science & Technology

2017-02-27

be generated in continuous- discrete optical media such as multi-core optical fiber or waveguide arrays; localisation dynamics in a continuous... discrete nonlinear system. Detailed theoretical analysis is presented of the existence and stability of the discrete -continuous light bullets using a very...and pulse compression using wave collapse (self-focusing) energy localisation dynamics in a continuous- discrete nonlinear system, as implemented in a

Distinguishing discrete and gradient category structure in language: Insights from verb-particle constructions.

PubMed

Brehm, Laurel; Goldrick, Matthew

2017-10-01

The current work uses memory errors to examine the mental representation of verb-particle constructions (VPCs; e.g., make up the story, cut up the meat). Some evidence suggests that VPCs are represented by a cline in which the relationship between the VPC and its component elements ranges from highly transparent (cut up) to highly idiosyncratic (make up). Other evidence supports a multiple class representation, characterizing VPCs as belonging to discretely separated classes differing in semantic and syntactic structure. We outline a novel paradigm to investigate the representation of VPCs in which we elicit illusory conjunctions, or memory errors sensitive to syntactic structure. We then use a novel application of piecewise regression to demonstrate that the resulting error pattern follows a cline rather than discrete classes. A preregistered replication verifies these findings, and a final preregistered study verifies that these errors reflect syntactic structure. This provides evidence for gradient rather than discrete representations across levels of representation in language processing. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A perspective on the complexity of dietary fiber structures and their potential effect on the gut microbiota.

PubMed

Hamaker, Bruce R; Tuncil, Yunus E

2014-11-25

Even though there are many factors that determine the human colon microbiota composition, diet is an important one because most microorganisms in the colon obtain energy for their growth by degrading complex dietary compounds, particularly dietary fibers. While fiber carbohydrates that escape digestion in the upper gastrointestinal tract are recognized to have a range of structures, the vastness in number of chemical structures from the perspective of the bacteria is not well appreciated. In this article, we introduce the concept of "discrete structure" that is defined as a unique chemical structure, often within a fiber molecule, which aligns with encoded gene clusters in bacterial genomes. The multitude of discrete structures originates from the array of different fiber types coupled with structural variations within types due to genotype and growing environment, anatomical parts of the grain or plant, discrete regions within polymers, and size of oligosaccharides and small polysaccharides. These thousands of discrete structures conceivably could be used to favor bacteria in the competitive colon environment. A global framework needs to be developed to better understand how dietary fibers can be used to obtain predicted changes in microbiota composition for improved health. This will require a multi-disciplinary effort that includes biological scientists, clinicians, and carbohydrate specialists. Copyright © 2014 Elsevier Ltd. All rights reserved.

Changes in Acetylcholine Extracellular Levels during Cognitive Processes

ERIC Educational Resources Information Center

Pepeu, Giancarlo; Giovannini, Maria Grazia

2004-01-01

Measuring the changes in neurotransmitter extracellular levels in discrete brain areas is considered a tool for identifying the neuronal systems involved in specific behavioral responses or cognitive processes. Acetylcholine (ACh) is the first neurotransmitter whose diffusion from the central nervous system was investigated and whose extracellular…

Imitating expressions: emotion-specific neural substrates in facial mimicry.

PubMed

Lee, Tien-Wen; Josephs, Oliver; Dolan, Raymond J; Critchley, Hugo D

2006-09-01

Intentionally adopting a discrete emotional facial expression can modulate the subjective feelings corresponding to that emotion; however, the underlying neural mechanism is poorly understood. We therefore used functional brain imaging (functional magnetic resonance imaging) to examine brain activity during intentional mimicry of emotional and non-emotional facial expressions and relate regional responses to the magnitude of expression-induced facial movement. Eighteen healthy subjects were scanned while imitating video clips depicting three emotional (sad, angry, happy), and two 'ingestive' (chewing and licking) facial expressions. Simultaneously, facial movement was monitored from displacement of fiducial markers (highly reflective dots) on each subject's face. Imitating emotional expressions enhanced activity within right inferior prefrontal cortex. This pattern was absent during passive viewing conditions. Moreover, the magnitude of facial movement during emotion-imitation predicted responses within right insula and motor/premotor cortices. Enhanced activity in ventromedial prefrontal cortex and frontal pole was observed during imitation of anger, in ventromedial prefrontal and rostral anterior cingulate during imitation of sadness and in striatal, amygdala and occipitotemporal during imitation of happiness. Our findings suggest a central role for right inferior frontal gyrus in the intentional imitation of emotional expressions. Further, by entering metrics for facial muscular change into analysis of brain imaging data, we highlight shared and discrete neural substrates supporting affective, action and social consequences of somatomotor emotional expression.

Multiresolution MR elastography using nonlinear inversion

PubMed Central

McGarry, M. D. J.; Van Houten, E. E. W.; Johnson, C. L.; Georgiadis, J. G.; Sutton, B. P.; Weaver, J. B.; Paulsen, K. D.

2012-01-01

Purpose: Nonlinear inversion (NLI) in MR elastography requires discretization of the displacement field for a finite element (FE) solution of the “forward problem”, and discretization of the unknown mechanical property field for the iterative solution of the “inverse problem”. The resolution requirements for these two discretizations are different: the forward problem requires sufficient resolution of the displacement FE mesh to ensure convergence, whereas lowering the mechanical property resolution in the inverse problem stabilizes the mechanical property estimates in the presence of measurement noise. Previous NLI implementations use the same FE mesh to support the displacement and property fields, requiring a trade-off between the competing resolution requirements. Methods: This work implements and evaluates multiresolution FE meshes for NLI elastography, allowing independent discretizations of the displacements and each mechanical property parameter to be estimated. The displacement resolution can then be selected to ensure mesh convergence, and the resolution of the property meshes can be independently manipulated to control the stability of the inversion. Results: Phantom experiments indicate that eight nodes per wavelength (NPW) are sufficient for accurate mechanical property recovery, whereas mechanical property estimation from 50 Hz in vivo brain data stabilizes once the displacement resolution reaches 1.7 mm (approximately 19 NPW). Viscoelastic mechanical property estimates of in vivo brain tissue show that subsampling the loss modulus while holding the storage modulus resolution constant does not substantially alter the storage modulus images. Controlling the ratio of the number of measurements to unknown mechanical properties by subsampling the mechanical property distributions (relative to the data resolution) improves the repeatability of the property estimates, at a cost of modestly decreased spatial resolution. Conclusions: Multiresolution NLI elastography provides a more flexible framework for mechanical property estimation compared to previous single mesh implementations. PMID:23039674

Optimization and quantization in gradient symbol systems: a framework for integrating the continuous and the discrete in cognition.

PubMed

Smolensky, Paul; Goldrick, Matthew; Mathis, Donald

2014-08-01

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed Symbol Systems, have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization-Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. Copyright © 2013 Cognitive Science Society, Inc.

Identification of brain nuclei implicated in cocaine-primed reinstatement of conditioned place preference: a behaviour dissociable from sensitization.

PubMed

Brown, Robyn Mary; Short, Jennifer Lynn; Lawrence, Andrew John

2010-12-29

Relapse prevention represents the primary therapeutic challenge in the treatment of drug addiction. As with humans, drug-seeking behaviour can be precipitated in laboratory animals by exposure to a small dose of the drug (prime). The aim of this study was to identify brain nuclei implicated in the cocaine-primed reinstatement of a conditioned place preference (CPP). Thus, a group of mice were conditioned to cocaine, had this place preference extinguished and were then tested for primed reinstatement of the original place preference. There was no correlation between the extent of drug-seeking upon reinstatement and the extent of behavioural sensitization, the extent of original CPP or the extinction profile of mice, suggesting a dissociation of these components of addictive behaviour with a drug-primed reinstatement. Expression of the protein product of the neuronal activity marker c-fos was assessed in a number of brain regions of mice that exhibited reinstatement (R mice) versus those which did not (NR mice). Reinstatement generally conferred greater Fos expression in cortical and limbic structures previously implicated in drug-seeking behaviour, though a number of regions not typically associated with drug-seeking were also activated. In addition, positive correlations were found between neural activation of a number of brain regions and reinstatement behaviour. The most significant result was the activation of the lateral habenula and its positive correlation with reinstatement behaviour. The findings of this study question the relationship between primed reinstatement of a previously extinguished place preference for cocaine and behavioural sensitization. They also implicate activation patterns of discrete brain nuclei as differentiators between reinstating and non-reinstating mice.

Transcriptional Landscape of the Prenatal Human Brain

PubMed Central

Miller, Jeremy A.; Ding, Song-Lin; Sunkin, Susan M.; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L.; Aiona, Kaylynn; Arnold, James M.; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A.; Dee, Nick; Dolbeare, Tim A.; Facer, Benjamin A. C.; Feng, David; Fliss, Tim P.; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W.; Gu, Guangyu; Howard, Robert E.; Jochim, Jayson M.; Kuan, Chihchau L.; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A.; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick F.; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D.; Parry, Sheana E.; Player, Allison Stevens; Pletikos, Mihovil; Reding, Melissa; Royall, Joshua J.; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V.; Shen, Elaine H.; Sjoquist, Nathan; Slaughterbeck, Clifford R.; Smith, Michael; Sodt, Andy J.; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B.; Geschwind, Daniel H.; Glass, Ian A.; Hawrylycz, Michael J.; Hevner, Robert F.; Huang, Hao; Jones, Allan R.; Knowles, James A.; Levitt, Pat; Phillips, John W.; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G.; Lein, Ed S.

2014-01-01

Summary The anatomical and functional architecture of the human brain is largely determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and postmitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and human-expanded outer subventricular zones. Both germinal and postmitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in frontal lobe. Finally, many neurodevelopmental disorder and human evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development. PMID:24695229

Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy

PubMed Central

Holmes, Holly E.; Powell, Nick M.; Ma, Da; Ismail, Ozama; Harrison, Ian F.; Wells, Jack A.; Colgan, Niall; O'Callaghan, James M.; Johnson, Ross A.; Murray, Tracey K.; Ahmed, Zeshan; Heggenes, Morten; Fisher, Alice; Cardoso, M. Jorge; Modat, Marc; O'Neill, Michael J.; Collins, Emily C.; Fisher, Elizabeth M. C.; Ourselin, Sébastien; Lythgoe, Mark F.

2017-01-01

With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our “in-skull” preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes. PMID:28408879

Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy.

PubMed

Holmes, Holly E; Powell, Nick M; Ma, Da; Ismail, Ozama; Harrison, Ian F; Wells, Jack A; Colgan, Niall; O'Callaghan, James M; Johnson, Ross A; Murray, Tracey K; Ahmed, Zeshan; Heggenes, Morten; Fisher, Alice; Cardoso, M Jorge; Modat, Marc; O'Neill, Michael J; Collins, Emily C; Fisher, Elizabeth M C; Ourselin, Sébastien; Lythgoe, Mark F

2017-01-01

With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our "in-skull" preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.

Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data

NASA Astrophysics Data System (ADS)

Deng, Xinyi

2016-08-01

A common interest of scientists in many fields is to understand the relationship between the dynamics of a physical system and the occurrences of discrete events within such physical system. Seismologists study the connection between mechanical vibrations of the Earth and the occurrences of earthquakes so that future earthquakes can be better predicted. Astrophysicists study the association between the oscillating energy of celestial regions and the emission of photons to learn the Universe's various objects and their interactions. Neuroscientists study the link between behavior and the millisecond-timescale spike patterns of neurons to understand higher brain functions. Such relationships can often be formulated within the framework of state-space models with point process observations. The basic idea is that the dynamics of the physical systems are driven by the dynamics of some stochastic state variables and the discrete events we observe in an interval are noisy observations with distributions determined by the state variables. This thesis proposes several new methodological developments that advance the framework of state-space models with point process observations at the intersection of statistics and neuroscience. In particular, we develop new methods 1) to characterize the rhythmic spiking activity using history-dependent structure, 2) to model population spike activity using marked point process models, 3) to allow for real-time decision making, and 4) to take into account the need for dimensionality reduction for high-dimensional state and observation processes. We applied these methods to a novel problem of tracking rhythmic dynamics in the spiking of neurons in the subthalamic nucleus of Parkinson's patients with the goal of optimizing placement of deep brain stimulation electrodes. We developed a decoding algorithm that can make decision in real-time (for example, to stimulate the neurons or not) based on various sources of information present in population spiking data. Lastly, we proposed a general three-step paradigm that allows us to relate behavioral outcomes of various tasks to simultaneously recorded neural activity across multiple brain areas, which is a step towards closed-loop therapies for psychological diseases using real-time neural stimulation. These methods are suitable for real-time implementation for content-based feedback experiments.

The neuroinflammatory phenotype in a mouse model of Gulf War Illness is unrelated to brain regional levels of acetylcholine as measured by quantitative HILIC-UPLC-MS/MS.

PubMed

Miller, Julie V; LeBouf, Ryan F; Kelly, Kimberly A; Michalovicz, Lindsay T; Ranpara, Anand; Locker, Alicia R; Miller, Diane B; O'Callaghan, James P

2018-05-28

Many veterans of the 1991 Persian Gulf War (GW) returned with a chronic multisymptom illness that has been termed Gulf War Illness (GWI). Previous GWI studies have suggested that exposure to acetylcholinesterase inhibitors (AChEIs) in theater, such as sarin and/or pesticides, may have contributed to the symptomatology of GWI. Additionally, concomitant high physiological stress experienced during the war may have contributed to the initiation of the GWI phenotype. While inhibition of AChE leading to accumulation of acetylcholine (ACh) will activate the cholinergic anti-inflammatory pathway, the signature symptomatology of GWI has been shown to be associated with neuroinflammation. To investigate the relationship between ACh and neuroinflammation in discrete brain regions, we used our previously established mouse model of GWI, which combines an exposure to a high physiological stress mimic, corticosterone (CORT), with GW-relevant AChEIs. The AChEIs used in this study were diisopropyl fluorophosphate (DFP), chlorpyrifos oxon (CPO), and physostigmine (PHY). After AChEI exposure, ACh concentrations for cortex (CTX), hippocampus (HIP), and striatum (STR) were determined using hydrophilic interaction liquid chromatography (HILIC) with ultra-performance liquid chromatography (UPLC)-tandem-mass spectrometry (MS/MS). CORT pretreatment ameliorated the DFP-induced ACh increase in HIP and STR, but not CTX. CORT pretreatment did not significantly alter ACh levels for CPO and PHY. Further analysis of STR neuroinflammatory biomarkers revealed an exacerbated CORT+AChEI response, which does not correspond to measured brain ACh. By utilizing this new analytical method for discrete brain region analysis of ACh, this work suggests the exacerbated neuroinflammatory effects in our mouse model of GWI are not driven by the accumulation of brain region-specific ACh.

Golgi: Interactive Online Brain Mapping

PubMed Central

Brown, Ramsay A.; Swanson, Larry W.

2015-01-01

Golgi (http://www.usegolgi.com) is a prototype interactive brain map of the rat brain that helps researchers intuitively interact with neuroanatomy, connectomics, and cellular and chemical architecture. The flood of “-omic” data urges new ways to help researchers connect discrete findings to the larger context of the nervous system. Here we explore Golgi’s underlying reasoning and techniques and how our design decisions balance the constraints of building both a scientifically useful and usable tool. We demonstrate how Golgi can enhance connectomic literature searches with a case study investigating a thalamocortical circuit involving the Nucleus Accumbens and we explore Golgi’s potential and future directions for growth in systems neuroscience and connectomics. PMID:26635596

Episodic reinstatement in the medial temporal lobe.

PubMed

Staresina, Bernhard P; Henson, Richard N A; Kriegeskorte, Nikolaus; Alink, Arjen

2012-12-12

The essence of episodic memory is our ability to reexperience past events in great detail, even in the absence of external stimulus cues. Does the phenomenological reinstatement of past experiences go along with reinstating unique neural representations in the brain? And if so, how is this accomplished by the medial temporal lobe (MTL), a brain region intimately linked to episodic memory? Computational models suggest that such reinstatement (also termed "pattern completion") in cortical regions is mediated by the hippocampus, a key region of the MTL. Although recent functional magnetic resonance imaging studies demonstrated reinstatement of coarse item properties like stimulus category or task context across different brain regions, it has not yet been shown whether reinstatement can be observed at the level of individual, discrete events-arguably the defining feature of episodic memory-nor whether MTL structures like the hippocampus support this "true episodic" reinstatement. Here we show that neural activity patterns for unique word-scene combinations encountered during encoding are reinstated in human parahippocampal cortex (PhC) during retrieval. Critically, this reinstatement occurs when word-scene combinations are successfully recollected (even though the original scene is not visually presented) and does not encompass other stimulus domains (such as word-color associations). Finally, the degree of PhC reinstatement across retrieval events correlated with hippocampal activity, consistent with a role of the hippocampus in coordinating pattern completion in cortical regions.

Continuum modeling of the mechanical and thermal behavior of discrete large structures

NASA Technical Reports Server (NTRS)

Nayfeh, A. H.; Hefzy, M. S.

1980-01-01

In the present paper we introduce a rather straightforward construction procedure in order to derive continuum equivalence of discrete truss-like repetitive structures. Once the actual structure is specified, the construction procedure can be outlined by the following three steps: (a) all sets of parallel members are identified, (b) unidirectional 'effective continuum' properties are derived for each of these sets and (c) orthogonal transformations are finally used to determine the contribution of each set to the 'overall effective continuum' properties of the structure. Here the properties includes mechanical (stiffnesses), thermal (coefficients of thermal expansions) and material densities. Once expanded descriptions of the steps (b) and (c) are done, the construction procedure will be applied to a wide variety of discrete structures and the results will be compared with those of other existing methods.

Fermion systems in discrete space-time

NASA Astrophysics Data System (ADS)

Finster, Felix

2007-05-01

Fermion systems in discrete space-time are introduced as a model for physics on the Planck scale. We set up a variational principle which describes a non-local interaction of all fermions. This variational principle is symmetric under permutations of the discrete space-time points. We explain how for minimizers of the variational principle, the fermions spontaneously break this permutation symmetry and induce on space-time a discrete causal structure.

A discrete control model of PLANT

NASA Technical Reports Server (NTRS)

Mitchell, C. M.

1985-01-01

A model of the PLANT system using the discrete control modeling techniques developed by Miller is described. Discrete control models attempt to represent in a mathematical form how a human operator might decompose a complex system into simpler parts and how the control actions and system configuration are coordinated so that acceptable overall system performance is achieved. Basic questions include knowledge representation, information flow, and decision making in complex systems. The structure of the model is a general hierarchical/heterarchical scheme which structurally accounts for coordination and dynamic focus of attention. Mathematically, the discrete control model is defined in terms of a network of finite state systems. Specifically, the discrete control model accounts for how specific control actions are selected from information about the controlled system, the environment, and the context of the situation. The objective is to provide a plausible and empirically testable accounting and, if possible, explanation of control behavior.

A framework for longitudinal data analysis via shape regression

NASA Astrophysics Data System (ADS)

Fishbaugh, James; Durrleman, Stanley; Piven, Joseph; Gerig, Guido

2012-02-01

Traditional longitudinal analysis begins by extracting desired clinical measurements, such as volume or head circumference, from discrete imaging data. Typically, the continuous evolution of a scalar measurement is estimated by choosing a 1D regression model, such as kernel regression or fitting a polynomial of fixed degree. This type of analysis not only leads to separate models for each measurement, but there is no clear anatomical or biological interpretation to aid in the selection of the appropriate paradigm. In this paper, we propose a consistent framework for the analysis of longitudinal data by estimating the continuous evolution of shape over time as twice differentiable flows of deformations. In contrast to 1D regression models, one model is chosen to realistically capture the growth of anatomical structures. From the continuous evolution of shape, we can simply extract any clinical measurements of interest. We demonstrate on real anatomical surfaces that volume extracted from a continuous shape evolution is consistent with a 1D regression performed on the discrete measurements. We further show how the visualization of shape progression can aid in the search for significant measurements. Finally, we present an example on a shape complex of the brain (left hemisphere, right hemisphere, cerebellum) that demonstrates a potential clinical application for our framework.

Gauge properties of the guiding center variational symplectic integrator

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

Squire, J.; Tang, W. M.; Qin, H.

Variational symplectic algorithms have recently been developed for carrying out long-time simulation of charged particles in magnetic fields [H. Qin and X. Guan, Phys. Rev. Lett. 100, 035006 (2008); H. Qin, X. Guan, and W. Tang, Phys. Plasmas (2009); J. Li, H. Qin, Z. Pu, L. Xie, and S. Fu, Phys. Plasmas 18, 052902 (2011)]. As a direct consequence of their derivation from a discrete variational principle, these algorithms have very good long-time energy conservation, as well as exactly preserving discrete momenta. We present stability results for these algorithms, focusing on understanding how explicit variational integrators can be designed formore » this type of system. It is found that for explicit algorithms, an instability arises because the discrete symplectic structure does not become the continuous structure in the t{yields}0 limit. We examine how a generalized gauge transformation can be used to put the Lagrangian in the 'antisymmetric discretization gauge,' in which the discrete symplectic structure has the correct form, thus eliminating the numerical instability. Finally, it is noted that the variational guiding center algorithms are not electromagnetically gauge invariant. By designing a model discrete Lagrangian, we show that the algorithms are approximately gauge invariant as long as A and {phi} are relatively smooth. A gauge invariant discrete Lagrangian is very important in a variational particle-in-cell algorithm where it ensures current continuity and preservation of Gauss's law [J. Squire, H. Qin, and W. Tang (to be published)].« less

[Comparative rheoencephalographic and convective radiation encephalic thermometric studies].

PubMed

Vaĭsfel'd, D N; Korobov, S A; Petrov, A P

1996-01-01

It is for the first time that thermoassimetry of heart flows of brain right and left hemispheres presenting as predominance of radiative-convective heat radiation from the left has been revealed, the thermoassimetry gradient being rostral-caudal. Disclosed in cerebral hemispheres was complimentarity of energetic processes: the right hemisphere secures the background energy state, the left one functions in ensuring the discrete adaptive thermoenergy reactions. The thermoassimetry revealed may be the basis of other functional asymmetries of the brain. There was no parallelism between the studied parameters of circulation and heat flow.

From motor cortex to visual cortex: the application of noninvasive brain stimulation to amblyopia.

PubMed

Thompson, Benjamin; Mansouri, Behzad; Koski, Lisa; Hess, Robert F

2012-04-01

Noninvasive brain stimulation is a technique for inducing changes in the excitability of discrete neural populations in the human brain. A current model of the underlying pathological processes contributing to the loss of motor function after stroke has motivated a number of research groups to investigate the potential therapeutic application of brain stimulation to stroke rehabilitation. The loss of motor function is modeled as resulting from a combination of reduced excitability in the lesioned motor cortex and an increased inhibitory drive from the nonlesioned hemisphere over the lesioned hemisphere. This combination of impaired neural function and pathological suppression resonates with current views on the cause of the visual impairment in amblyopia. Here, we discuss how the rationale for using noninvasive brain stimulation in stroke rehabilitation can be applied to amblyopia, review a proof-of-principle study demonstrating that brain stimulation can temporarily improve amblyopic eye function, and propose future research avenues. Copyright © 2010 Wiley Periodicals, Inc.

Is conscious perception a series of discrete temporal frames?

PubMed

White, Peter A

2018-04-01

This paper reviews proposals that conscious perception consists, in whole or part, of successive discrete temporal frames on the sub-second time scale, each frame containing information registered as simultaneous or static. Although the idea of discrete frames in conscious perception cannot be regarded as falsified, there are many problems. Evidence does not consistently support any proposed duration or range of durations for frames. EEG waveforms provide evidence of periodicity in brain activity, but not necessarily in conscious perception. Temporal properties of perceptual processes are flexible in response to competing processing demands, which is hard to reconcile with the relative inflexibility of regular frames. There are also problems concerning the definition of frames, the need for informational connections between frames, the means by which boundaries between frames are established, and the apparent requirement for a storage buffer for information awaiting entry to the next frame. Copyright © 2018 Elsevier Inc. All rights reserved.

Discrete cloud structure on Neptune

NASA Technical Reports Server (NTRS)

Hammel, H. B.

1989-01-01

Recent CCD imaging data for the discrete cloud structure of Neptune shows that while cloud features at CH4-band wavelengths are manifest in the southern hemisphere, they have not been encountered in the northern hemisphere since 1986. A literature search has shown the reflected CH4-band light from the planet to have come from a single discrete feature at least twice in the last 10 years. Disk-integrated photometry derived from the imaging has demonstrated that a bright cloud feature was responsible for the observed 8900 A diurnal variation in 1986 and 1987.

Discrete and continuous dynamics modeling of a mass moving on a flexible structure

NASA Technical Reports Server (NTRS)

Herman, Deborah Ann

1992-01-01

A general discrete methodology for modeling the dynamics of a mass that moves on the surface of a flexible structure is developed. This problem was motivated by the Space Station/Mobile Transporter system. A model reduction approach is developed to make the methodology applicable to large structural systems. To validate the discrete methodology, continuous formulations are also developed. Three different systems are examined: (1) simply-supported beam, (2) free-free beam, and (3) free-free beam with two points of contact between the mass and the flexible beam. In addition to validating the methodology, parametric studies were performed to examine how the system's physical properties affect its dynamics.

Discrete Self-Similarity in Interfacial Hydrodynamics and the Formation of Iterated Structures.

PubMed

Dallaston, Michael C; Fontelos, Marco A; Tseluiko, Dmitri; Kalliadasis, Serafim

2018-01-19

The formation of iterated structures, such as satellite and subsatellite drops, filaments, and bubbles, is a common feature in interfacial hydrodynamics. Here we undertake a computational and theoretical study of their origin in the case of thin films of viscous fluids that are destabilized by long-range molecular or other forces. We demonstrate that iterated structures appear as a consequence of discrete self-similarity, where certain patterns repeat themselves, subject to rescaling, periodically in a logarithmic time scale. The result is an infinite sequence of ridges and filaments with similarity properties. The character of these discretely self-similar solutions as the result of a Hopf bifurcation from ordinarily self-similar solutions is also described.

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 correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.

Evolution of the Mauthner axon cap.

PubMed

Bierman, Hilary S; Zottoli, Steven J; Hale, Melina E

2009-01-01

Studies of vertebrate brain evolution have focused primarily on patterns of gene expression or changes in size and organization of major brain regions. The Mauthner cell, an important reticulospinal neuron that functions in the startle response of many species, provides an opportunity for evolutionary comparisons at the cellular level. Despite broad interspecific similarities in Mauthner cell morphology, the motor patterns and startle behaviors it initiates vary markedly. Response diversity has been hypothesized to result, in part, from differences in the structure and function of the Mauthner cell-associated axon cap. We used light microscopy techniques to compare axon cap morphology across a wide range of species, including all four extant basal actinopterygian orders, representatives of a variety of teleost lineages and lungfishes, and we combined our data with published descriptions of axon cap structure. The 'composite' axon cap, observed in teleosts, is an organized conglomeration of glia and fibers of inhibitory and excitatory interneurons. Lungfish, amphibian tadpoles and several basal actinopterygian fishes have 'simple' axon caps that appear to lack glia and include few fibers. Several other basal actinopterygian fishes have 'simple-dense' caps that include greater numbers of fibers than simple caps, but lack the additional elements and organization of composite caps. Phylogenetic mapping shows that through evolution there are discrete transitions in axon cap morphology occurring at the base of gnathostomes, within basal actinopterygians, and at the base of the teleost radiation. Comparing axon cap evolution to the evolution of startle behavior and motor pattern provides insight into the relationship between Mauthner cell-associated structures and their functions in behavior. Copyright 2009 S. Karger AG, Basel.

On the Full-Discrete Extended Generalised q-Difference Toda System

NASA Astrophysics Data System (ADS)

Li, Chuanzhong; Meng, Anni

2017-08-01

In this paper, we construct a full-discrete integrable difference equation which is a full-discretisation of the generalised q-Toda equation. Meanwhile its soliton solutions are constructed to show its integrable property. Further the Lax pairs of an extended generalised full-discrete q-Toda hierarchy are also constructed. To show the integrability, the bi-Hamiltonian structure and tau symmetry of the extended full-discrete generalised q-Toda hierarchy are given.

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

Xiao, Jianyuan; Liu, Jian; He, Yang

Explicit high-order non-canonical symplectic particle-in-cell algorithms for classical particle-field systems governed by the Vlasov-Maxwell equations are developed. The algorithms conserve a discrete non-canonical symplectic structure derived from the Lagrangian of the particle-field system, which is naturally discrete in particles. The electromagnetic field is spatially discretized using the method of discrete exterior calculus with high-order interpolating differential forms for a cubic grid. The resulting time-domain Lagrangian assumes a non-canonical symplectic structure. It is also gauge invariant and conserves charge. The system is then solved using a structure-preserving splitting method discovered by He et al. [preprint http://arxiv.org/abs/arXiv:1505.06076 (2015)], which produces five exactlymore » soluble sub-systems, and high-order structure-preserving algorithms follow by combinations. The explicit, high-order, and conservative nature of the algorithms is especially suitable for long-term simulations of particle-field systems with extremely large number of degrees of freedom on massively parallel supercomputers. The algorithms have been tested and verified by the two physics problems, i.e., the nonlinear Landau damping and the electron Bernstein wave.« less

Protein local structure alignment under the discrete Fréchet distance.

PubMed

Zhu, Binhai

2007-12-01

Protein structure alignment is a fundamental problem in computational and structural biology. While there has been lots of experimental/heuristic methods and empirical results, very few results are known regarding the algorithmic/complexity aspects of the problem, especially on protein local structure alignment. A well-known measure to characterize the similarity of two polygonal chains is the famous Fréchet distance, and with the application of protein-related research, a related discrete Fréchet distance has been used recently. In this paper, following the recent work of Jiang et al. we investigate the protein local structural alignment problem using bounded discrete Fréchet distance. Given m proteins (or protein backbones, which are 3D polygonal chains), each of length O(n), our main results are summarized as follows: * If the number of proteins, m, is not part of the input, then the problem is NP-complete; moreover, under bounded discrete Fréchet distance it is NP-hard to approximate the maximum size common local structure within a factor of n(1-epsilon). These results hold both when all the proteins are static and when translation/rotation are allowed. * If the number of proteins, m, is a constant, then there is a polynomial time solution for the problem.

Optimization and Quantization in Gradient Symbol Systems: A Framework for Integrating the Continuous and the Discrete in Cognition

ERIC Educational Resources Information Center

Smolensky, Paul; Goldrick, Matthew; Mathis, Donald

2014-01-01

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The…

On the Importance of Both Dimensional and Discrete Models of Emotion.

PubMed

Harmon-Jones, Eddie; Harmon-Jones, Cindy; Summerell, Elizabeth

2017-09-29

We review research on the structure and functions of emotions that has benefitted from a serious consideration of both discrete and dimensional perspectives on emotion. To illustrate this point, we review research that demonstrates: (1) how affective valence within discrete emotions differs as a function of individuals and situations, and how these differences relate to various functions; (2) that anger (and other emotional states) should be considered as a discrete emotion but there are dimensions around and within anger; (3) that similarities exist between approach-related positive and negative discrete emotions and they have unique motivational functions; (4) that discrete emotions and broad dimensions of emotions both have unique functions; and (5) evidence that a "new" discrete emotion with discrete functions exists within a broader emotion family. We hope that this consideration of both discrete and dimensional perspectives on emotion will assist in understanding the functions of emotions.

On the Importance of Both Dimensional and Discrete Models of Emotion

PubMed Central

Harmon-Jones, Eddie

2017-01-01

We review research on the structure and functions of emotions that has benefitted from a serious consideration of both discrete and dimensional perspectives on emotion. To illustrate this point, we review research that demonstrates: (1) how affective valence within discrete emotions differs as a function of individuals and situations, and how these differences relate to various functions; (2) that anger (and other emotional states) should be considered as a discrete emotion but there are dimensions around and within anger; (3) that similarities exist between approach-related positive and negative discrete emotions and they have unique motivational functions; (4) that discrete emotions and broad dimensions of emotions both have unique functions; and (5) evidence that a “new” discrete emotion with discrete functions exists within a broader emotion family. We hope that this consideration of both discrete and dimensional perspectives on emotion will assist in understanding the functions of emotions. PMID:28961185

A Novel Signal Modeling Approach for Classification of Seizure and Seizure-Free EEG Signals.

PubMed

Gupta, Anubha; Singh, Pushpendra; Karlekar, Mandar

2018-05-01

This paper presents a signal modeling-based new methodology of automatic seizure detection in EEG signals. The proposed method consists of three stages. First, a multirate filterbank structure is proposed that is constructed using the basis vectors of discrete cosine transform. The proposed filterbank decomposes EEG signals into its respective brain rhythms: delta, theta, alpha, beta, and gamma. Second, these brain rhythms are statistically modeled with the class of self-similar Gaussian random processes, namely, fractional Brownian motion and fractional Gaussian noises. The statistics of these processes are modeled using a single parameter called the Hurst exponent. In the last stage, the value of Hurst exponent and autoregressive moving average parameters are used as features to design a binary support vector machine classifier to classify pre-ictal, inter-ictal (epileptic with seizure free interval), and ictal (seizure) EEG segments. The performance of the classifier is assessed via extensive analysis on two widely used data set and is observed to provide good accuracy on both the data set. Thus, this paper proposes a novel signal model for EEG data that best captures the attributes of these signals and hence, allows to boost the classification accuracy of seizure and seizure-free epochs.

Discrete RNA libraries from pseudo-torsional space

PubMed Central

Humphris-Narayanan, Elisabeth

2012-01-01

The discovery that RNA molecules can fold into complex structures and carry out diverse cellular roles has led to interest in developing tools for modeling RNA tertiary structure. While significant progress has been made in establishing that the RNA backbone is rotameric, few libraries of discrete conformations specifically for use in RNA modeling have been validated. Here, we present six libraries of discrete RNA conformations based on a simplified pseudo-torsional notation of the RNA backbone, comparable to phi and psi in the protein backbone. We evaluate the ability of each library to represent single nucleotide backbone conformations and we show how individual library fragments can be assembled into dinucleotides that are consistent with established RNA backbone descriptors spanning from sugar to sugar. We then use each library to build all-atom models of 20 test folds and we show how the composition of a fragment library can limit model quality. Despite the limitations inherent in using discretized libraries, we find that several hundred discrete fragments can rebuild RNA folds up to 174 nucleotides in length with atomic-level accuracy (<1.5Å RMSD). We anticipate the libraries presented here could easily be incorporated into RNA structural modeling, analysis, or refinement tools. PMID:22425640

A discourse on sensitivity analysis for discretely-modeled structures

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Haftka, Raphael T.

1991-01-01

A descriptive review is presented of the most recent methods for performing sensitivity analysis of the structural behavior of discretely-modeled systems. The methods are generally but not exclusively aimed at finite element modeled structures. Topics included are: selections of finite difference step sizes; special consideration for finite difference sensitivity of iteratively-solved response problems; first and second derivatives of static structural response; sensitivity of stresses; nonlinear static response sensitivity; eigenvalue and eigenvector sensitivities for both distinct and repeated eigenvalues; and sensitivity of transient response for both linear and nonlinear structural response.

Hybrid finite difference/finite element immersed boundary method.

PubMed

E Griffith, Boyce; Luo, Xiaoyu

2017-12-01

The immersed boundary method is an approach to fluid-structure interaction that uses a Lagrangian description of the structural deformations, stresses, and forces along with an Eulerian description of the momentum, viscosity, and incompressibility of the fluid-structure system. The original immersed boundary methods described immersed elastic structures using systems of flexible fibers, and even now, most immersed boundary methods still require Lagrangian meshes that are finer than the Eulerian grid. This work introduces a coupling scheme for the immersed boundary method to link the Lagrangian and Eulerian variables that facilitates independent spatial discretizations for the structure and background grid. This approach uses a finite element discretization of the structure while retaining a finite difference scheme for the Eulerian variables. We apply this method to benchmark problems involving elastic, rigid, and actively contracting structures, including an idealized model of the left ventricle of the heart. Our tests include cases in which, for a fixed Eulerian grid spacing, coarser Lagrangian structural meshes yield discretization errors that are as much as several orders of magnitude smaller than errors obtained using finer structural meshes. The Lagrangian-Eulerian coupling approach developed in this work enables the effective use of these coarse structural meshes with the immersed boundary method. This work also contrasts two different weak forms of the equations, one of which is demonstrated to be more effective for the coarse structural discretizations facilitated by our coupling approach. © 2017 The Authors International  Journal  for  Numerical  Methods  in  Biomedical  Engineering Published by John Wiley & Sons Ltd.

Interferon-α acutely impairs whole-brain functional connectivity network architecture - A preliminary study.

PubMed

Dipasquale, Ottavia; Cooper, Ella A; Tibble, Jeremy; Voon, Valerie; Baglio, Francesca; Baselli, Giuseppe; Cercignani, Mara; Harrison, Neil A

2016-11-01

Interferon-alpha (IFN-α) is a key mediator of antiviral immune responses used to treat Hepatitis C infection. Though clinically effective, IFN-α rapidly impairs mood, motivation and cognition, effects that can appear indistinguishable from major depression and provide powerful empirical support for the inflammation theory of depression. Though inflammation has been shown to modulate activity within discrete brain regions, how it affects distributed information processing and the architecture of whole brain functional connectivity networks have not previously been investigated. Here we use a graph theoretic analysis of resting state functional magnetic resonance imaging (rfMRI) to investigate acute effects of systemic interferon-alpha (IFN-α) on whole brain functional connectivity architecture and its relationship to IFN-α-induced mood change. Twenty-two patients with Hepatitis-C infection, initiating IFN-α-based therapy were scanned at baseline and 4h after their first IFN-α dose. The whole brain network was parcellated into 110 cortical and sub-cortical nodes based on the Oxford-Harvard Atlas and effects assessed on higher-level graph metrics, including node degree, betweenness centrality, global and local efficiency. IFN-α was associated with a significant reduction in global network connectivity (node degree) (p=0.033) and efficiency (p=0.013), indicating a global reduction of information transfer among the nodes forming the whole brain network. Effects were similar for highly connected (hub) and non-hub nodes, with no effect on betweenness centrality (p>0.1). At a local level, we identified regions with reduced efficiency of information exchange and a sub-network with decreased functional connectivity after IFN-α. Changes in local and particularly global functional connectivity correlated with associated changes in mood measured on the Profile of Mood States (POMS) questionnaire. IFN-α rapidly induced a profound shift in whole brain network structure, impairing global functional connectivity and the efficiency of parallel information exchange. Correlations with multiple indices of mood change support a role for global changes in brain functional connectivity architecture in coordinated behavioral responses to IFN-α. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Why Johnny Can't Read: An Applied Neurology Explanation Flesched Out.

ERIC Educational Resources Information Center

Preen, Bryan S.; Townsend, Diana O.

1993-01-01

Suggests that "Johnny can't read" because of high testosterone levels in fetal development and subsequent poor brain lateralization. Presents instructional strategies based on the principle of factorized teaching for each of three discrete lateralization categories. Notes that the use of factorized teaching appears to have improved diagnostic and…

Studies on the Release of Renin by Direct and Reflex Activation of Renal Sympathetic Nerves.

ERIC Educational Resources Information Center

Donald, David E.

1979-01-01

Presents data on release of renin during direct and indirect stimulation of renal nerves. Conclusions show that renin release is influenced by change in activity of carotid and cardiopulmonary baroreceptor systems, and excitation of discrete areas of brain and hypothalamus by changes in renal sympathetic nerve. (Author/SA)

The Memory Function of Noradrenergic Activity in Non-REM Sleep

ERIC Educational Resources Information Center

Gais, Steffen; Rasch, Bjorn; Dahmen, Johannes C.; Sara, Susan; Born, Jan

2011-01-01

There is a long-standing assumption that low noradrenergic activity during sleep reflects mainly the low arousal during this brain state. Nevertheless, recent research has demonstrated that the locus coeruleus, which is the main source of cortical noradrenaline, displays discrete periods of intense firing during non-REM sleep, without any signs of…

Homologous ligands accommodated by discrete conformations of a buried cavity

PubMed Central

Merski, Matthew; Fischer, Marcus; Balius, Trent E.; Eidam, Oliv; Shoichet, Brian K.

2015-01-01

Conformational change in protein–ligand complexes is widely modeled, but the protein accommodation expected on binding a congeneric series of ligands has received less attention. Given their use in medicinal chemistry, there are surprisingly few substantial series of congeneric ligand complexes in the Protein Data Bank (PDB). Here we determine the structures of eight alkyl benzenes, in single-methylene increases from benzene to n-hexylbenzene, bound to an enclosed cavity in T4 lysozyme. The volume of the apo cavity suffices to accommodate benzene but, even with toluene, larger cavity conformations become observable in the electron density, and over the series two other major conformations are observed. These involve discrete changes in main-chain conformation, expanding the site; few continuous changes in the site are observed. In most structures, two discrete protein conformations are observed simultaneously, and energetic considerations suggest that these conformations are low in energy relative to the ground state. An analysis of 121 lysozyme cavity structures in the PDB finds that these three conformations dominate the previously determined structures, largely modeled in a single conformation. An investigation of the few congeneric series in the PDB suggests that discrete changes are common adaptations to a series of growing ligands. The discrete, but relatively few, conformational states observed here, and their energetic accessibility, may have implications for anticipating protein conformational change in ligand design. PMID:25847998

Homologous ligands accommodated by discrete conformations of a buried cavity.

PubMed

Merski, Matthew; Fischer, Marcus; Balius, Trent E; Eidam, Oliv; Shoichet, Brian K

2015-04-21

Conformational change in protein-ligand complexes is widely modeled, but the protein accommodation expected on binding a congeneric series of ligands has received less attention. Given their use in medicinal chemistry, there are surprisingly few substantial series of congeneric ligand complexes in the Protein Data Bank (PDB). Here we determine the structures of eight alkyl benzenes, in single-methylene increases from benzene to n-hexylbenzene, bound to an enclosed cavity in T4 lysozyme. The volume of the apo cavity suffices to accommodate benzene but, even with toluene, larger cavity conformations become observable in the electron density, and over the series two other major conformations are observed. These involve discrete changes in main-chain conformation, expanding the site; few continuous changes in the site are observed. In most structures, two discrete protein conformations are observed simultaneously, and energetic considerations suggest that these conformations are low in energy relative to the ground state. An analysis of 121 lysozyme cavity structures in the PDB finds that these three conformations dominate the previously determined structures, largely modeled in a single conformation. An investigation of the few congeneric series in the PDB suggests that discrete changes are common adaptations to a series of growing ligands. The discrete, but relatively few, conformational states observed here, and their energetic accessibility, may have implications for anticipating protein conformational change in ligand design.

Inflammation and Alzheimer’s disease

PubMed Central

Akiyama, Haruhiko; Barger, Steven; Barnum, Scott; Bradt, Bonnie; Bauer, Joachim; Cole, Greg M.; Cooper, Neil R.; Eikelenboom, Piet; Emmerling, Mark; Fiebich, Berndt L.; Finch, Caleb E.; Frautschy, Sally; Griffin, W.S.T.; Hampel, Harald; Hull, Michael; Landreth, Gary; Lue, Lih–Fen; Mrak, Robert; Mackenzie, Ian R.; McGeer, Patrick L.; O’Banion, M. Kerry; Pachter, Joel; Pasinetti, Guilio; Plata–Salaman, Carlos; Rogers, Joseph; Rydel, Russell; Shen, Yong; Streit, Wolfgang; Strohmeyer, Ronald; Tooyoma, Ikuo; Van Muiswinkel, Freek L.; Veerhuis, Robert; Walker, Douglas; Webster, Scott; Wegrzyniak, Beatrice; Wenk, Gary; Wyss–Coray, Tony

2013-01-01

Inflammation clearly occurs in pathologically vulnerable regions of the Alzheimer’s disease (AD) brain, and it does so with the full complexity of local peripheral inflammatory responses. In the periphery, degenerating tissue and the deposition of highly insoluble abnormal materials are classical stimulants of inflammation. Likewise, in the AD brain damaged neurons and neurites and highly insoluble amyloid β peptide deposits and neurofibrillary tangles provide obvious stimuli for inflammation. Because these stimuli are discrete, microlocalized, and present from early preclinical to terminal stages of AD, local upregulation of complement, cytokines, acute phase reactants, and other inflammatory mediators is also discrete, microlocalized, and chronic. Cumulated over many years, direct and bystander damage from AD inflammatory mechanisms is likely to significantly exacerbate the very pathogenic processes that gave rise to it. Thus, animal models and clinical studies, although still in their infancy, strongly suggest that AD inflammation significantly contributes to AD pathogenesis. By better understanding AD inflammatory and immunoregulatory processes, it should be possible to develop anti-inflammatory approaches that may not cure AD but will likely help slow the progression or delay the onset of this devastating disorder. PMID:10858586

Reproducing the nonlinear dynamic behavior of a structured beam with a generalized continuum model

NASA Astrophysics Data System (ADS)

Vila, J.; Fernández-Sáez, J.; Zaera, R.

2018-04-01

In this paper we study the coupled axial-transverse nonlinear vibrations of a kind of one dimensional structured solids by application of the so called Inertia Gradient Nonlinear continuum model. To show the accuracy of this axiomatic model, previously proposed by the authors, its predictions are compared with numeric results from a previously defined finite discrete chain of lumped masses and springs, for several number of particles. A continualization of the discrete model equations based on Taylor series allowed us to set equivalent values of the mechanical properties in both discrete and axiomatic continuum models. Contrary to the classical continuum model, the inertia gradient nonlinear continuum model used herein is able to capture scale effects, which arise for modes in which the wavelength is comparable to the characteristic distance of the structured solid. The main conclusion of the work is that the proposed generalized continuum model captures the scale effects in both linear and nonlinear regimes, reproducing the behavior of the 1D nonlinear discrete model adequately.

On the lagrangian 1-form structure of the hyperbolic calogero-moser system

NASA Astrophysics Data System (ADS)

Jairuk, Umpon; Tanasittikosol, Monsit; Yoo-Kong, Sikarin

2017-06-01

In this work, we present the Lagrangian 1-form structure of the hyperbolic Calogero-Moser system in both discrete-time level and continuous-time level. The discrete-time hyperbolic Calogero-Moser system is obtained by considering pole reduction of the semi-discrete Kadomtsev-Petviashvili (KP) equation. Furthermore, it is shown that the hyperbolic Calogero-Moser system possesses the key relation, known as the discrete-time closure relation. This relation is a consequence of the compatibility property of the temporal Lax matrices. The continuous-time hierarchy of the hyperbolic Calogero-Moser system is obtained by taking two successive continuum limits, namely, the skewed limit and full limit. With these successive limits, the continuous-time closure relation is also obtained and is shown to hold at the continuous level.

The electrical behavior of GaAs-insulator interfaces - A discrete energy interface state model

NASA Technical Reports Server (NTRS)

Kazior, T. E.; Lagowski, J.; Gatos, H. C.

1983-01-01

The relationship between the electrical behavior of GaAs Metal Insulator Semiconductor (MIS) structures and the high density discrete energy interface states (0.7 and 0.9 eV below the conduction band) was investigated utilizing photo- and thermal emission from the interface states in conjunction with capacitance measurements. It was found that all essential features of the anomalous behavior of GaAs MIS structures, such as the frequency dispersion and the C-V hysteresis, can be explained on the basis of nonequilibrium charging and discharging of the high density discrete energy interface states.

Time crystals: a review

NASA Astrophysics Data System (ADS)

Sacha, Krzysztof; Zakrzewski, Jakub

2018-01-01

Time crystals are time-periodic self-organized structures postulated by Frank Wilczek in 2012. While the original concept was strongly criticized, it stimulated at the same time an intensive research leading to propositions and experimental verifications of discrete (or Floquet) time crystals—the structures that appear in the time domain due to spontaneous breaking of discrete time translation symmetry. The struggle to observe discrete time crystals is reviewed here together with propositions that generalize this concept introducing condensed matter like physics in the time domain. We shall also revisit the original Wilczek’s idea and review strategies aimed at spontaneous breaking of continuous time translation symmetry.

Ring-Opening Copolymerization of Epoxides and Cyclic Anhydrides with Discrete Metal Complexes: Structure-Property Relationships.

PubMed

Longo, Julie M; Sanford, Maria J; Coates, Geoffrey W

2016-12-28

Polyesters synthesized through the alternating copolymerization of epoxides and cyclic anhydrides compose a growing class of polymers that exhibit an impressive array of chemical and physical properties. Because they are synthesized through the chain-growth polymerization of two variable monomers, their syntheses can be controlled by discrete metal complexes, and the resulting materials vary widely in their functionality and physical properties. This polymer-focused review gives a perspective on the current state of the field of epoxide/anhydride copolymerization mediated by discrete catalysts and the relationships between the structures and properties of these polyesters.

Conservative discretization of the Landau collision integral

DOE PAGES

Hirvijoki, E.; Adams, M. F.

2017-03-28

Here we describe a density, momentum-, and energy-conserving discretization of the nonlinear Landau collision integral. The method is suitable for both the finite-element and discontinuous Galerkin methods and does not require structured meshes. The conservation laws for the discretization are proven algebraically and demonstrated numerically for an axially symmetric nonlinear relaxation problem using a finite-element implementation.

Time Span of Discretion and Administrative Work in School Systems: Results of a Pilot Study.

ERIC Educational Resources Information Center

Allison, Derek J.; Morfitt, Grace

This paper presents findings of a study that utilized Elliott Jaques' theories of organizational depth structure and time span of discretion in administrative work to examine administrators' responsibilities in two Ontario (Canada) school systems. The theory predicts that the time-span of discretion associated with the administrative tasks will…

Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

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

Dall-Anese, Emiliano; Zhou, Xinyang; Liu, Zhiyuan

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together withmore » pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.« less

A Pathological Brain Detection System based on Extreme Learning Machine Optimized by Bat Algorithm.

PubMed

Lu, Siyuan; Qiu, Xin; Shi, Jianping; Li, Na; Lu, Zhi-Hai; Chen, Peng; Yang, Meng-Meng; Liu, Fang-Yuan; Jia, Wen-Juan; Zhang, Yudong

2017-01-01

It is beneficial to classify brain images as healthy or pathological automatically, because 3D brain images can generate so much information which is time consuming and tedious for manual analysis. Among various 3D brain imaging techniques, magnetic resonance (MR) imaging is the most suitable for brain, and it is now widely applied in hospitals, because it is helpful in the four ways of diagnosis, prognosis, pre-surgical, and postsurgical procedures. There are automatic detection methods; however they suffer from low accuracy. Therefore, we proposed a novel approach which employed 2D discrete wavelet transform (DWT), and calculated the entropies of the subbands as features. Then, a bat algorithm optimized extreme learning machine (BA-ELM) was trained to identify pathological brains from healthy controls. A 10x10-fold cross validation was performed to evaluate the out-of-sample performance. The method achieved a sensitivity of 99.04%, a specificity of 93.89%, and an overall accuracy of 98.33% over 132 MR brain images. The experimental results suggest that the proposed approach is accurate and robust in pathological brain detection. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Compatible Spatial Discretizations for Partial Differential Equations

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

Arnold, Douglas, N, ed.

From May 11--15, 2004, the Institute for Mathematics and its Applications held a hot topics workshop on Compatible Spatial Discretizations for Partial Differential Equations. The numerical solution of partial differential equations (PDE) is a fundamental task in science and engineering. The goal of the workshop was to bring together a spectrum of scientists at the forefront of the research in the numerical solution of PDEs to discuss compatible spatial discretizations. We define compatible spatial discretizations as those that inherit or mimic fundamental properties of the PDE such as topology, conservation, symmetries, and positivity structures and maximum principles. A wide varietymore » of discretization methods applied across a wide range of scientific and engineering applications have been designed to or found to inherit or mimic intrinsic spatial structure and reproduce fundamental properties of the solution of the continuous PDE model at the finite dimensional level. A profusion of such methods and concepts relevant to understanding them have been developed and explored: mixed finite element methods, mimetic finite differences, support operator methods, control volume methods, discrete differential forms, Whitney forms, conservative differencing, discrete Hodge operators, discrete Helmholtz decomposition, finite integration techniques, staggered grid and dual grid methods, etc. This workshop seeks to foster communication among the diverse groups of researchers designing, applying, and studying such methods as well as researchers involved in practical solution of large scale problems that may benefit from advancements in such discretizations; to help elucidate the relations between the different methods and concepts; and to generally advance our understanding in the area of compatible spatial discretization methods for PDE. Particular points of emphasis included: + Identification of intrinsic properties of PDE models that are critical for the fidelity of numerical simulations. + Identification and design of compatible spatial discretizations of PDEs, their classification, analysis, and relations. + Relationships between different compatible spatial discretization methods and concepts which have been developed; + Impact of compatible spatial discretizations upon physical fidelity, verification and validation of simulations, especially in large-scale, multiphysics settings. + How solvers address the demands placed upon them by compatible spatial discretizations. This report provides information about the program and abstracts of all the presentations.« less

Transcriptional landscape of the prenatal human brain.

PubMed

Miller, Jeremy A; Ding, Song-Lin; Sunkin, Susan M; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L; Royall, Joshua J; Aiona, Kaylynn; Arnold, James M; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A; Dee, Nick; Dolbeare, Tim A; Facer, Benjamin A C; Feng, David; Fliss, Tim P; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W; Gu, Guangyu; Howard, Robert E; Jochim, Jayson M; Kuan, Chihchau L; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D; Parry, Sheana E; Stevens, Allison; Pletikos, Mihovil; Reding, Melissa; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V; Shen, Elaine H; Sjoquist, Nathan; Slaughterbeck, Clifford R; Smith, Michael; Sodt, Andy J; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B; Geschwind, Daniel H; Glass, Ian A; Hawrylycz, Michael J; Hevner, Robert F; Huang, Hao; Jones, Allan R; Knowles, James A; Levitt, Pat; Phillips, John W; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G; Lein, Ed S

2014-04-10

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

Bayesian networks in neuroscience: a survey.

PubMed

Bielza, Concha; Larrañaga, Pedro

2014-01-01

Bayesian networks are a type of probabilistic graphical models lie at the intersection between statistics and machine learning. They have been shown to be powerful tools to encode dependence relationships among the variables of a domain under uncertainty. Thanks to their generality, Bayesian networks can accommodate continuous and discrete variables, as well as temporal processes. In this paper we review Bayesian networks and how they can be learned automatically from data by means of structure learning algorithms. Also, we examine how a user can take advantage of these networks for reasoning by exact or approximate inference algorithms that propagate the given evidence through the graphical structure. Despite their applicability in many fields, they have been little used in neuroscience, where they have focused on specific problems, like functional connectivity analysis from neuroimaging data. Here we survey key research in neuroscience where Bayesian networks have been used with different aims: discover associations between variables, perform probabilistic reasoning over the model, and classify new observations with and without supervision. The networks are learned from data of any kind-morphological, electrophysiological, -omics and neuroimaging-, thereby broadening the scope-molecular, cellular, structural, functional, cognitive and medical- of the brain aspects to be studied.

Bayesian networks in neuroscience: a survey

PubMed Central

Bielza, Concha; Larrañaga, Pedro

2014-01-01

Bayesian networks are a type of probabilistic graphical models lie at the intersection between statistics and machine learning. They have been shown to be powerful tools to encode dependence relationships among the variables of a domain under uncertainty. Thanks to their generality, Bayesian networks can accommodate continuous and discrete variables, as well as temporal processes. In this paper we review Bayesian networks and how they can be learned automatically from data by means of structure learning algorithms. Also, we examine how a user can take advantage of these networks for reasoning by exact or approximate inference algorithms that propagate the given evidence through the graphical structure. Despite their applicability in many fields, they have been little used in neuroscience, where they have focused on specific problems, like functional connectivity analysis from neuroimaging data. Here we survey key research in neuroscience where Bayesian networks have been used with different aims: discover associations between variables, perform probabilistic reasoning over the model, and classify new observations with and without supervision. The networks are learned from data of any kind–morphological, electrophysiological, -omics and neuroimaging–, thereby broadening the scope–molecular, cellular, structural, functional, cognitive and medical– of the brain aspects to be studied. PMID:25360109

Ultrasound-mediated blood-brain barrier disruption for targeted drug delivery in the central nervous system

PubMed Central

Aryal, Muna; Arvanitis, Costas D.; Alexander, Phillip M.; McDannold, Nathan

2014-01-01

The physiology of the vasculature in the central nervous system (CNS), which includes the blood-brain barrier (BBB) and other factors, complicates the delivery of most drugs to the brain. Different methods have been used to bypass the BBB, but they have limitations such as being invasive, non-targeted or requiring the formulation of new drugs. Focused ultrasound (FUS), when combined with circulating microbubbles, is a noninvasive method to locally and transiently disrupt the BBB at discrete targets. This review provides insight on the current status of this unique drug delivery technique, experience in preclinical models, and potential for clinical translation. If translated to humans, this method would offer a flexible means to target therapeutics to desired points or volumes in the brain, and enable the whole arsenal of drugs in the CNS that are currently prevented by the BBB. PMID:24462453

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

PubMed Central

Ellington, Roni; Wachira, James

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems. PMID:20810968

RNA secondary structure prediction by using discrete mathematics: an interdisciplinary research experience for undergraduate students.

PubMed

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems.

Fast discrete cosine transform structure suitable for implementation with integer computation

NASA Astrophysics Data System (ADS)

Jeong, Yeonsik; Lee, Imgeun

2000-10-01

The discrete cosine transform (DCT) has wide applications in speech and image coding. We propose a fast DCT scheme with the property of reduced multiplication stages and fewer additions and multiplications. The proposed algorithm is structured so that most multiplications are performed at the final stage, which reduces the propagation error that could occur in the integer computation.

Forest structure estimation and pattern exploration from discrete return lidar in subalpine forests of the Central Rockies

Treesearch

K. R. Sherrill; M. A. Lefsky; J. B. Bradford; M. G. Ryan

2008-01-01

This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...

Surface metrics: An alternative to patch metrics for the quantification of landscape structure

Treesearch

Kevin McGarigal; Sermin Tagil; Samuel A. Cushman

2009-01-01

Modern landscape ecology is based on the patch mosaic paradigm, in which landscapes are conceptualized and analyzed as mosaics of discrete patches. While this model has been widely successful, there are many situations where it is more meaningful to model landscape structure based on continuous rather than discrete spatial heterogeneity. The growing field of surface...

Forest structure estimation and pattern exploration from discrete-return lidar in subalpine forests of the central Rockies

Treesearch

K.R. Sherrill; M.A. Lefsky; J.B. Bradford; M.G. Ryan

2008-01-01

This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...

Schroedinger's Wave Structure of Matter (WSM)

NASA Astrophysics Data System (ADS)

Wolff, Milo; Haselhurst, Geoff

2009-10-01

The puzzling electron is due to the belief that it is a discrete particle. Einstein deduced this structure was impossible since Nature does not allow the discrete particle. Clifford (1876) rejected discrete matter and suggested structures in `space'. Schroedinger, (1937) also eliminated discrete particles writing: What we observe as material bodies and forces are nothing but shapes and variations in the structure of space. Particles are just schaumkommen (appearances). He rejected wave-particle duality. Schroedinger's concept was developed by Milo Wolff and Geoff Haselhurst (SpaceAndMotion.com) using the Scalar Wave Equation to find spherical wave solutions in a 3D quantum space. This WSM, the origin of all the Natural Laws, contains all the electron's properties including the Schroedinger Equation. The origin of Newton's Law F=ma is no longer a puzzle; It originates from Mach's principle of inertia (1883) that depends on the space medium and the WSM. Carver Mead (1999) at CalTech used the WSM to design Intel micro-chips correcting errors of Maxwell's magnetic Equations. Applications of the WSM also describe matter at molecular dimensions: alloys, catalysts, biology and medicine, molecular computers and memories. See ``Schroedinger's Universe'' - at Amazon.com

Schroedinger's Wave Structure of Matter (WSM)

NASA Astrophysics Data System (ADS)

Wolff, Milo

2009-05-01

The puzzling electron is due to the belief that it is a discrete particle. Einstein deduced this structure impossible since Nature does not match the discrete particle. Clifford (1876) rejected discrete matter and suggested structures in `space'. Schroedinger, (1937) also eliminated discrete particles writing: What we observe as material bodies and forces are nothing but shapes and variations in the structure of space. Particles are just schaumkommen (appearances). He rejected wave-particle duality. Schroedinger's concept was developed by Milo Wolff and Geoff Haselhurst (http://www.SpaceAndMotion.com) using the Scalar Wave Equation to find spherical wave solutions in a 3D quantum space. This WSM is the origin of all the Natural Laws; thus it contains all the electron's properties including the Schroedinger Equation. The origin of Newton's Law F=ma is no longer a puzzle; it is shown to originate from Mach's principle of inertia (1883) that depends on the space medium. Carver Mead (1999) applied the WSM to design Intel micro-chips correcting errors of Maxwell's magnetic Equations. Applications of the WSM describe matter at molecular dimensions: alloys, catalysts, the mechanisms of biology and medicine, molecular computers and memories. See http://www.amazon.com/Schro at Amazon.com.

Explicit high-order non-canonical symplectic particle-in-cell algorithms for Vlasov-Maxwell systems

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

Xiao, Jianyuan; Qin, Hong; Liu, Jian

2015-11-01

Explicit high-order non-canonical symplectic particle-in-cell algorithms for classical particle-field systems governed by the Vlasov-Maxwell equations are developed. The algorithms conserve a discrete non-canonical symplectic structure derived from the Lagrangian of the particle-field system, which is naturally discrete in particles. The electromagnetic field is spatially discretized using the method of discrete exterior calculus with high-order interpolating differential forms for a cubic grid. The resulting time-domain Lagrangian assumes a non-canonical symplectic structure. It is also gauge invariant and conserves charge. The system is then solved using a structure-preserving splitting method discovered by He et al. [preprint arXiv: 1505.06076 (2015)], which produces fivemore » exactly soluble sub-systems, and high-order structure-preserving algorithms follow by combinations. The explicit, high-order, and conservative nature of the algorithms is especially suitable for long-term simulations of particle-field systems with extremely large number of degrees of freedom on massively parallel supercomputers. The algorithms have been tested and verified by the two physics problems, i.e., the nonlinear Landau damping and the electron Bernstein wave. (C) 2015 AIP Publishing LLC.« less

Virasoro symmetry of the constrained multicomponent Kadomtsev-Petviashvili hierarchy and its integrable discretization

NASA Astrophysics Data System (ADS)

Li, Chuanzhong; He, Jingsong

2016-06-01

We construct Virasoro-type additional symmetries of a kind of constrained multicomponent Kadomtsev-Petviashvili (KP) hierarchy and obtain the Virasoro flow equation for the eigenfunctions and adjoint eigenfunctions. We show that the algebraic structure of the Virasoro symmetry is retained under discretization from the constrained multicomponent KP hierarchy to the discrete constrained multicomponent KP hierarchy.

Finsler Geometry of Nonlinear Elastic Solids with Internal Structure

DTIC Science & Technology

2017-01-01

should enable regularized numerical solutions with discretization -size independence for representation of materials demonstrating softening, e.g...additional possibility of a discrete larger void/cavity forming at the core of the sphere. In the second case, comparison with the classical...core of the domain. This hollow sphere physically represents a discrete cavity, while the constant field ξH physically represents a continuous

Cortical Neural Computation by Discrete Results Hypothesis

PubMed Central

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called “Discrete Results” (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of “Discrete Results” is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel “Discrete Results” concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation. PMID:27807408

Cortical Neural Computation by Discrete Results Hypothesis.

PubMed

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.

A continuous-discrete approach for evaluation of natural frequencies and mode shapes of high-rise buildings

NASA Astrophysics Data System (ADS)

Malekinejad, Mohsen; Rahgozar, Reza; Malekinejad, Ali; Rahgozar, Peyman

2016-09-01

In this paper, a continuous-discrete approach based on the concept of lumped mass and equivalent continuous approach is proposed for free vibration analysis of combined system of framed tube, shear core and outrigger-belt truss in high-rise buildings. This system is treated as a continuous system (i.e., discrete beams and columns are replaced with equivalent continuous membranes) and a discrete system (or lumped mass system) at different stages of dynamic analysis. The structure is discretized at each floor of the building as a series of lumped masses placed at the center of shear core. Each mass has two transitional degrees of freedom (lateral and axial( and one rotational. The effect of shear core and outrigger-belt truss on framed tube system is modeled as a rotational spring placed at the location of outrigger-belt truss system along structure's height. By solving the resulting eigen problem, natural frequencies and mode-shapes are obtained. Numerical examples are presented to show acceptable accuracy of the procedure in estimating the fundamental frequencies and corresponding mode shapes of the combined system as compared to finite element analysis of the complete structure. The simplified proposed method is much faster and should be more suitable for rapid interactive design.

Directed self-assembly of proteins into discrete radial patterns

PubMed Central

Thakur, Garima; Prashanthi, Kovur; Thundat, Thomas

2013-01-01

Unlike physical patterning of materials at nanometer scale, manipulating soft matter such as biomolecules into patterns is still in its infancy. Self-assembled monolayer (SAM) with surface density gradient has the capability to drive biomolecules in specific directions to create hierarchical and discrete structures. Here, we report on a two-step process of self-assembly of the human serum albumin (HSA) protein into discrete ring structures based on density gradient of SAM. The methodology involves first creating a 2-dimensional (2D) polyethylene glycol (PEG) islands with responsive carboxyl functionalities. Incubation of proteins on such pre-patterned surfaces results in direct self-assembly of protein molecules around PEG islands. Immobilization and adsorption of protein on such structures over time evolve into the self-assembled patterns. PMID:23719678

Discrete size optimization of steel trusses using a refined big bang-big crunch algorithm

NASA Astrophysics Data System (ADS)

Hasançebi, O.; Kazemzadeh Azad, S.

2014-01-01

This article presents a methodology that provides a method for design optimization of steel truss structures based on a refined big bang-big crunch (BB-BC) algorithm. It is shown that a standard formulation of the BB-BC algorithm occasionally falls short of producing acceptable solutions to problems from discrete size optimum design of steel trusses. A reformulation of the algorithm is proposed and implemented for design optimization of various discrete truss structures according to American Institute of Steel Construction Allowable Stress Design (AISC-ASD) specifications. Furthermore, the performance of the proposed BB-BC algorithm is compared to its standard version as well as other well-known metaheuristic techniques. The numerical results confirm the efficiency of the proposed algorithm in practical design optimization of truss structures.

Alcohol-Binding Sites in Distinct Brain Proteins: The Quest for Atomic Level Resolution

PubMed Central

Howard, Rebecca J.; Slesinger, Paul A.; Davies, Daryl L.; Das, Joydip; Trudell, James R.; Harris, R. Adron

2011-01-01

Defining the sites of action of ethanol on brain proteins is a major prerequisite to understanding the molecular pharmacology of this drug. The main barrier to reaching an atomic-level understanding of alcohol action is the low potency of alcohols, ethanol in particular, which is a reflection of transient, low-affinity interactions with their targets. These mechanisms are difficult or impossible to study with traditional techniques such as radioligand binding or spectroscopy. However, there has been considerable recent progress in combining X-ray crystallography, structural modeling, and site-directed mutagenesis to define the sites and mechanisms of action of ethanol and related alcohols on key brain proteins. We review such insights for several diverse classes of proteins including inwardly rectifying potassium, transient receptor potential, and neurotransmit-ter-gated ion channels, as well as protein kinase C epsilon. Some common themes are beginning to emerge from these proteins, including hydrogen bonding of the hydroxyl group and van der Waals interactions of the methylene groups of ethanol with specific amino acid residues. The resulting binding energy is proposed to facilitate or stabilize low-energy state transitions in the bound proteins, allowing ethanol to act as a “molecular lubricant” for protein function. We discuss evidence for characteristic, discrete alcohol-binding sites on protein targets, as well as evidence that binding to some proteins is better characterized by an interaction region that can accommodate multiple molecules of ethanol. PMID:21676006

Sensitivity analysis of discrete structural systems: A survey

NASA Technical Reports Server (NTRS)

Adelman, H. M.; Haftka, R. T.

1984-01-01

Methods for calculating sensitivity derivatives for discrete structural systems are surveyed, primarily covering literature published during the past two decades. Methods are described for calculating derivatives of static displacements and stresses, eigenvalues and eigenvectors, transient structural response, and derivatives of optimum structural designs with respect to problem parameters. The survey is focused on publications addressed to structural analysis, but also includes a number of methods developed in nonstructural fields such as electronics, controls, and physical chemistry which are directly applicable to structural problems. Most notable among the nonstructural-based methods are the adjoint variable technique from control theory, and the Green's function and FAST methods from physical chemistry.

Age or stage structure? A comparison of dynamic outcomes from discrete age- and stage-structured population models.

PubMed

Wikan, Arild

2012-06-01

Discrete stage-structured density-dependent and discrete age-structured density-dependent population models are considered. Regarding the former, we prove that the model at hand is permanent (i.e., that the population will neither go extinct nor exhibit explosive oscillations) and given density dependent fecundity terms we also show that species with delayed semelparous life histories tend to be more stable than species which possess precocious semelparous life histories. Moreover, our findings together with results obtained from other stage-structured models seem to illustrate a fairly general ecological principle, namely that iteroparous species are more stable than semelparous species. Our analysis of various age-structured models does not necessarily support the conclusions above. In fact, species with precocious life histories now appear to possess better stability properties than species with delayed life histories, especially in the iteroparous case. We also show that there are dynamical outcomes from semelparous age-structured models which we are not able to capture in corresponding stage-structured cases. Finally, both age- and stage-structured population models may generate periodic dynamics of low period (either exact or approximate). The important prerequisite is to assume density-dependent survival probabilities.

Weak form of Stokes-Dirac structures and geometric discretization of port-Hamiltonian systems

NASA Astrophysics Data System (ADS)

Kotyczka, Paul; Maschke, Bernhard; Lefèvre, Laurent

2018-05-01

We present the mixed Galerkin discretization of distributed parameter port-Hamiltonian systems. On the prototypical example of hyperbolic systems of two conservation laws in arbitrary spatial dimension, we derive the main contributions: (i) A weak formulation of the underlying geometric (Stokes-Dirac) structure with a segmented boundary according to the causality of the boundary ports. (ii) The geometric approximation of the Stokes-Dirac structure by a finite-dimensional Dirac structure is realized using a mixed Galerkin approach and power-preserving linear maps, which define minimal discrete power variables. (iii) With a consistent approximation of the Hamiltonian, we obtain finite-dimensional port-Hamiltonian state space models. By the degrees of freedom in the power-preserving maps, the resulting family of structure-preserving schemes allows for trade-offs between centered approximations and upwinding. We illustrate the method on the example of Whitney finite elements on a 2D simplicial triangulation and compare the eigenvalue approximation in 1D with a related approach.

Methylphenidate administration determines enduring changes in neuroglial network in rats.

PubMed

Cavaliere, Carlo; Cirillo, Giovanni; Bianco, Maria Rosaria; Adriani, Walter; De Simone, Antonietta; Leo, Damiana; Perrone-Capano, Carla; Papa, Michele

2012-01-01

Repeated exposure to psychostimulant drugs induces complex molecular and structural modifications in discrete brain regions of the meso-cortico-limbic system. This structural remodeling is thought to underlie neurobehavioral adaptive responses. Administration to adolescent rats of methylphenidate (MPH), commonly used in attention deficit and hyperactivity disorder (ADHD), triggers alterations of reward-based behavior paralleled by persistent and plastic synaptic changes of neuronal and glial markers within key areas of the reward circuits. By immunohistochemistry, we observe a marked increase of glial fibrillary acidic protein (GFAP) and neuronal nitric oxide synthase (nNOS) expression and a down-regulation of glial glutamate transporter GLAST in dorso-lateral and ventro-medial striatum. Using electron microscopy, we find in the prefrontal cortex a significant reduction of the synaptic active zone length, paralleled by an increase of dendritic spines. We demonstrate that in limbic areas the MPH-induced reactive astrocytosis affects the glial glutamatergic uptake system that in turn could determine glutamate receptor sensitization. These processes could be sustained by NO production and synaptic rearrangement and contribute to MPH neuroglial induced rewiring. Copyright © 2011. Published by Elsevier B.V.

Cognitive-motor interactions of the basal ganglia in development

PubMed Central

Leisman, Gerry; Braun-Benjamin, Orit; Melillo, Robert

2014-01-01

Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, language comprehension, and other cognitive functions associated with frontal lobes. The basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human reasoning and adaptive function. The basal ganglia are key elements in the control of reward-based learning, sequencing, discrete elements that constitute a complete motor act, and cognitive function. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. We know that the relation between the basal ganglia and the cerebral cortical region allows for connections organized into discrete circuits. Rather than serving as a means for widespread cortical areas to gain access to the motor system, these loops reciprocally interconnect a large and diverse set of cerebral cortical areas with the basal ganglia. Neuronal activity within the basal ganglia associated with motor areas of the cerebral cortex is highly correlated with parameters of movement. Neuronal activity within the basal ganglia and cerebellar loops associated with the prefrontal cortex is related to the aspects of cognitive function. Thus, individual loops appear to be involved in distinct behavioral functions. Damage to the basal ganglia of circuits with motor areas of the cortex leads to motor symptoms, whereas damage to the subcortical components of circuits with non-motor areas of the cortex causes higher-order deficits. In this report, we review some of the anatomic, physiologic, and behavioral findings that have contributed to a reappraisal of function concerning the basal ganglia and cerebellar loops with the cerebral cortex and apply it in clinical applications to attention deficit/hyperactivity disorder (ADHD) with biomechanics and a discussion of retention of primitive reflexes being highly associated with the condition. PMID:24592214

Poly(malic acid) nanoconjugates containing various antibodies and oligonucleotides for multitargeting drug delivery

PubMed Central

Fujita, Manabu; Ljubimov, Alexander V; Torchilin, Vladimir P; Black, Keith L; Holler, Eggehard

2009-01-01

Nanoconjugates are emerging as promising drug-delivery vehicles because of their multimodular structure enabling them to actively target discrete cells, pass through biological barriers and simultaneously carry multiple drugs of various chemical nature. Nanoconjugates have matured from simple devices to multifunctional, biodegradable, nontoxic and nonimmunogenic constructs, capable of delivering synergistically functioning drugs in vivo. This review mainly concerns the Polycefin family of natural-derived polymeric drug-delivery devices as an example. This type of vehicle is built by hierarchic conjugation of functional groups onto the backbone of poly(malic acid), an aliphatic polyester obtained from the microorganism Physarum polycephalum. Particular Polycefin variants target human brain and breast tumors implanted into animals specifically and actively and could be detected easily by noninvasive imaging analysis. Delivery of antisense oligonucleotides to a tumor-specific angiogenic marker using Polycefin resulted in significant inhibition of tumor angiogenesis and increase of animal survival. PMID:18373429

The dispositions of things: the non-human dimension of power and ethics in patient-centred medicine.

PubMed

Gardner, John; Cribb, Alan

2016-09-01

This article explores power relations between clinicians, patients and families as clinicians engage in patient-centred ethical work. Specifically, we draw on actor-network theory to interrogate the role of non-human elements in distributing power relations in clinical settings, as clinicians attempt to manage the expectations of patients and families. Using the activities of a multidisciplinary team providing deep brain stimulation to children with severe movement disorders as an example, we illustrate how a patient-centred tool is implicated in establishing relations that constitute four modes of power: 'power over', 'power to', "power storage" and "power/discretion". We argue that understanding the role of non-human elements in structuring power relations can guide and inform bioethical discussions on the suitability of patient-centred approaches in clinical settings. © 2016 The Authors. Sociology of Health & Illness published by John Wiley & Sons Ltd on behalf of Foundation for SHIL.

Flexural waves induced by electro-impulse deicing forces

NASA Technical Reports Server (NTRS)

Gien, P. H.

1990-01-01

The generation, reflection and propagation of flexural waves created by electroimpulsive deicing forces are demonstrated both experimentally and analytically in a thin circular plate and a thin semicylindrical shell. Analytical prediction of these waves with finite element models shows good correlation with acceleration and displacement measurements at discrete points on the structures studied. However, sensitivity to spurious flexural waves resulting from the spatial discretization of the structures is shown to be significant. Consideration is also given to composite structures as an extension of these studies.

Multimodal MRI reveals structural connectivity differences in 22q11 deletion syndrome related to impaired spatial working memory.

PubMed

O'Hanlon, Erik; Howley, Sarah; Prasad, Sarah; McGrath, Jane; Leemans, Alexander; McDonald, Colm; Garavan, Hugh; Murphy, Kieran C

2016-12-01

Impaired spatial working memory is a core cognitive deficit observed in people with 22q11 Deletion syndrome (22q11DS) and has been suggested as a candidate endophenotype for schizophrenia. However, to date, the neuroanatomical mechanisms describing its structural and functional underpinnings in 22q11DS remain unclear. We quantitatively investigate the cognitive processes and associated neuroanatomy of spatial working memory in people with 22q11DS compared to matched controls. We examine whether there are significant between-group differences in spatial working memory using task related fMRI, Voxel based morphometry and white matter fiber tractography. Multimodal magnetic resonance imaging employing functional, diffusion and volumetric techniques were used to quantitatively assess the cognitive and neuroanatomical features of spatial working memory processes in 22q11DS. Twenty-six participants with genetically confirmed 22q11DS aged between 9 and 52 years and 26 controls aged between 8 and 46 years, matched for age, gender, and handedness were recruited. People with 22q11DS have significant differences in spatial working memory functioning accompanied by a gray matter volume reduction in the right precuneus. Gray matter volume was significantly correlated with task performance scores in these areas. Tractography revealed extensive differences along fibers between task-related cortical activations with pronounced differences localized to interhemispheric commissural fibers within the parietal section of the corpus callosum. Abnormal spatial working memory in 22q11DS is associated with aberrant functional activity in conjunction with gray and white matter structural abnormalities. These anomalies in discrete brain regions may increase susceptibility to the development of psychiatric disorders such as schizophrenia. Hum Brain Mapp 37:4689-4705, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Introducing Discrete Frequency Infrared Technology for High-Throughput Biofluid Screening

NASA Astrophysics Data System (ADS)

Hughes, Caryn; Clemens, Graeme; Bird, Benjamin; Dawson, Timothy; Ashton, Katherine M.; Jenkinson, Michael D.; Brodbelt, Andrew; Weida, Miles; Fotheringham, Edeline; Barre, Matthew; Rowlette, Jeremy; Baker, Matthew J.

2016-02-01

Accurate early diagnosis is critical to patient survival, management and quality of life. Biofluids are key to early diagnosis due to their ease of collection and intimate involvement in human function. Large-scale mid-IR imaging of dried fluid deposits offers a high-throughput molecular analysis paradigm for the biomedical laboratory. The exciting advent of tuneable quantum cascade lasers allows for the collection of discrete frequency infrared data enabling clinically relevant timescales. By scanning targeted frequencies spectral quality, reproducibility and diagnostic potential can be maintained while significantly reducing acquisition time and processing requirements, sampling 16 serum spots with 0.6, 5.1 and 15% relative standard deviation (RSD) for 199, 14 and 9 discrete frequencies respectively. We use this reproducible methodology to show proof of concept rapid diagnostics; 40 unique dried liquid biopsies from brain, breast, lung and skin cancer patients were classified in 2.4 cumulative seconds against 10 non-cancer controls with accuracies of up to 90%.

Designing in vivo concentration gradients with discrete controlled release: a computational model

NASA Astrophysics Data System (ADS)

Walker, Edgar Y.; Barbour, Dennis L.

2010-08-01

One promising neurorehabilitation therapy involves presenting neurotrophins directly into the brain to induce growth of new neural connections. The precise control of neurotrophin concentration gradients deep within neural tissue that would be necessary for such a therapy is not currently possible, however. Here we evaluate the theoretical potential of a novel method of drug delivery, discrete controlled release (DCR), to control effective neurotrophin concentration gradients in an isotropic region of neocortex. We do so by constructing computational models of neurotrophin concentration profiles resulting from discrete release locations into the cortex and then optimizing their design for uniform concentration gradients. The resulting model indicates that by rationally selecting initial neurotrophin concentrations for drug-releasing electrode coatings in a square 16-electrode array, nearly uniform concentration gradients (i.e. planar concentration profiles) from one edge of the electrode array to the other should be obtainable. DCR therefore represents a promising new method of precisely directing neuronal growth in vivo over a wider spatial profile than would be possible with single release points.

The Psychophysics of Brain Rhythms

PubMed Central

VanRullen, Rufin; Dubois, Julien

2011-01-01

It is becoming increasingly apparent that brain oscillations in various frequency bands play important roles in perceptual and attentional processes. Understandably, most of the associated experimental evidence comes from human or animal electrophysiological studies, allowing direct access to the oscillatory activities. However, such periodicities in perception and attention should, in theory, also be observable using the proper psychophysical tools. Here, we review a number of psychophysical techniques that have been used by us and other authors, in successful and sometimes unsuccessful attempts, to reveal the rhythmic nature of perceptual and attentional processes. We argue that the two existing and largely distinct debates about discrete vs. continuous perception and parallel vs. sequential attention should in fact be regarded as two facets of the same question: how do brain rhythms shape the psychological operations of perception and attention? PMID:21904532

Distribution of the hallucinogens N,N-dimethyltryptamine and 5-methoxy-N,N-dimethyltryptamine in rat brain following intraperitoneal injection: application of a new solid-phase extraction LC-APcI-MS-MS-isotope dilution method.

PubMed

Barker, S A; Littlefield-Chabaud, M A; David, C

2001-02-10

A method for the solid-phase extraction (SPE) and liquid chromatographic-atmospheric pressure chemical ionization-mass spectrometric-mass spectrometric-isotope dilution (LC-APcI-MS-MS-ID) analysis of the indole hallucinogens N,N-dimethyltryptamine (DMT) and 5-methoxy DMT (or O-methyl bufotenin, OMB) from rat brain tissue is reported. Rats were administered DMT or OMB by the intraperitoneal route at a dose of 5 mg/kg and sacrificed 15 min post treatment. Brains were dissected into discrete areas and analyzed by the methods described as a demonstration of the procedure's applicability. The synthesis and use of two new deuterated internal standards for these purposes are also reported.

The Myth of Optimality in Clinical Neuroscience.

PubMed

Holmes, Avram J; Patrick, Lauren M

2018-03-01

Clear evidence supports a dimensional view of psychiatric illness. Within this framework the expression of disorder-relevant phenotypes is often interpreted as a breakdown or departure from normal brain function. Conversely, health is reified, conceptualized as possessing a single ideal state. We challenge this concept here, arguing that there is no universally optimal profile of brain functioning. The evolutionary forces that shape our species select for a staggering diversity of human behaviors. To support our position we highlight pervasive population-level variability within large-scale functional networks and discrete circuits. We propose that, instead of examining behaviors in isolation, psychiatric illnesses can be best understood through the study of domains of functioning and associated multivariate patterns of variation across distributed brain systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Affective Core of Emotion: Linking Pleasure, Subjective Well-Being, and Optimal Metastability in the Brain

PubMed Central

Kringelbach, Morten L.; Berridge, Kent C.

2017-01-01

Arguably, emotion is always valenced—either pleasant or unpleasant—and dependent on the pleasure system. This system serves adaptive evolutionary functions; relying on separable wanting, liking, and learning neural mechanisms mediated by mesocorticolimbic networks driving pleasure cycles with appetitive, consummatory, and satiation phases. Liking is generated in a small set of discrete hedonic hotspots and coldspots, while wanting is linked to dopamine and to larger distributed brain networks. Breakdown of the pleasure system can lead to anhedonia and other features of affective disorders. Eudaimonia and well-being are difficult to study empirically, yet whole-brain computational models could offer novel insights (e.g., routes to eudaimonia such as caregiving of infants or music) potentially linking eudaimonia to optimal metastability in the pleasure system. PMID:28943891

The Sea Slug, Pleurobranchaea californica: A Signpost Species in the Evolution of Complex Nervous Systems and Behavior.

PubMed

Gillette, Rhanor; Brown, Jeffrey W

2015-12-01

How and why did complex brain and behavior evolve? Clues emerge from comparative studies of animals with simpler morphology, nervous system, and behavioral economics. The brains of vertebrates, arthropods, and some annelids have highly derived executive structures and function that control downstream, central pattern generators (CPGs) for locomotion, behavioral choice, and reproduction. For the vertebrates, these structures-cortex, basal ganglia, and hypothalamus-integrate topographically mapped sensory inputs with motivation and memory to transmit complex motor commands to relay stations controlling CPG outputs. Similar computations occur in the central complex and mushroom bodies of the arthropods, and in mammals these interactions structure subjective thought and socially based valuations. The simplest model systems available for comparison are opisthobranch molluscs, which have avoided selective pressure for complex bodies, brain, and behavior through potent chemical defenses. In particular, in the sea-slug Pleurobranchaea californica the functions of vertebrates' olfactory bulb and pallium are performed in the peripheral nervous system (PNS) of the chemotactile oral veil. Functions of hypothalamus and basal ganglia are combined in Pleurobranchaea's feeding motor network. The actions of basal ganglia on downstream locomotor regions and spinal CPGs are analogous to Pleurobranchaea's feeding network actions on CPGs for agonist and antagonist behaviors. The nervous systems of opisthobranch and pulmonate gastropods may conserve or reflect relations of the ancestral urbilaterian. Parallels and contrasts in neuronal circuits for action selection in Pleurobranchaea and vertebrates suggest how a basic set of decision circuitry was built upon in evolving segmentation, articulated skeletons, sociality, and highly invested reproductive strategies. They suggest (1) an origin of olfactory bulb and pallium from head-region PNS; (2) modularization of an ancestral feeding network into discrete but interacting executive modules for incentive comparison and decision (basal ganglia), and homeostatic functions (hypothalamus); (3) modification of a multifunctional premotor network for turns and locomotion, and its downstream targets for mid-brain and hind-brain motor areas and spinal CPGs; (4) condensation of a distributed serotonergic network for arousal into the raphe nuclei, with superimposed control by a peptidergic hypothalamic network mediating appetite and arousal; (5) centralization and condensation of the dopaminergic sensory afferents of the PNS, and/or the disperse dopaminergic elements of central CPGs, into the brain nuclei mediating valuation, reward, and motor arousal; and (6) the urbilaterian possessed the basic circuit relations integrating sensation, internal state, and learning for cost-benefit approach-avoidance decisions. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

Nonintegrable semidiscrete Hirota equation: gauge-equivalent structures and dynamical properties.

PubMed

Ma, Li-Yuan; Zhu, Zuo-Nong

2014-09-01

In this paper, we investigate nonintegrable semidiscrete Hirota equations, including the nonintegrable semidiscrete Hirota(-) equation and the nonintegrable semidiscrete Hirota(+) equation. We focus on the topics on gauge-equivalent structures and dynamical behaviors for the two nonintegrable semidiscrete equations. By using the concept of the prescribed discrete curvature, we show that, under the discrete gauge transformations, the nonintegrable semidiscrete Hirota(-) equation and the nonintegrable semidiscrete Hirota(+) equation are, respectively, gauge equivalent to the nonintegrable generalized semidiscrete modified Heisenberg ferromagnet equation and the nonintegrable generalized semidiscrete Heisenberg ferromagnet equation. We prove that the two discrete gauge transformations are reversible. We study the dynamical properties for the two nonintegrable semidiscrete Hirota equations. The exact spatial period solutions of the two nonintegrable semidiscrete Hirota equations are obtained through the constructions of period orbits of the stationary discrete Hirota equations. We discuss the topic regarding whether the spatial period property of the solution to the nonintegrable semidiscrete Hirota equation is preserved to that of the corresponding gauge-equivalent nonintegrable semidiscrete equations under the action of discrete gauge transformation. By using the gauge equivalent, we obtain the exact solutions to the nonintegrable generalized semidiscrete modified Heisenberg ferromagnet equation and the nonintegrable generalized semidiscrete Heisenberg ferromagnet equation. We also give the numerical simulations for the stationary discrete Hirota equations. We find that their dynamics are much richer than the ones of stationary discrete nonlinear Schrödinger equations.

Energy Criterion for the Spectral Stability of Discrete Breathers.

PubMed

Kevrekidis, Panayotis G; Cuevas-Maraver, Jesús; Pelinovsky, Dmitry E

2016-08-26

Discrete breathers are ubiquitous structures in nonlinear anharmonic models ranging from the prototypical example of the Fermi-Pasta-Ulam model to Klein-Gordon nonlinear lattices, among many others. We propose a general criterion for the emergence of instabilities of discrete breathers analogous to the well-established Vakhitov-Kolokolov criterion for solitary waves. The criterion involves the change of monotonicity of the discrete breather's energy as a function of the breather frequency. Our analysis suggests and numerical results corroborate that breathers with increasing (decreasing) energy-frequency dependence are generically unstable in soft (hard) nonlinear potentials.

On a new semi-discrete integrable combination of Burgers and Sharma-Tasso-Olver equation

NASA Astrophysics Data System (ADS)

Zhao, Hai-qiong

2017-02-01

In this paper, a new semi-discrete integrable combination of Burgers and Sharma-Tasso-Olver equation is investigated. The underlying integrable structures like the Lax pair, the infinite number of conservation laws, the Darboux-Bäcklund transformation, and the solutions are presented in the explicit form. The theory of the semi-discrete equation including integrable properties yields the corresponding theory of the continuous counterpart in the continuous limit. Finally, numerical experiments are provided to demonstrate the effectiveness of the developed integrable semi-discretization algorithms.

Exploring the relation between people’s theories of intelligence and beliefs about brain development

PubMed Central

Thomas, Ashley J.; Sarnecka, Barbara W.

2015-01-01

A person’s belief about whether intelligence can change (called their implicit theory of intelligence) predicts something about that person’s thinking and behavior. People who believe intelligence is fixed (called entity theorists) attribute failure to traits (i.e., “I failed the test because I’m not smart.”) and tend to be less motivated in school; those who believe intelligence is malleable (called incremental theorists) tend to attribute failure to behavior (i.e., “I failed the test because I didn’t study.”) and are more motivated in school. In previous studies, researchers have characterized participants as either entity or incremental theorists based on their agreement or disagreement with three statements. The present study further explored the theories-of-intelligence (TOI) construct in two ways: first, we asked whether these theories are coherent, in the sense that they show up not only in participants’ responses to the three standard assessment items, but on a broad range of questions about intelligence and the brain. Second, we asked whether these theories are discrete or continuous. In other words, we asked whether people believe one thing or the other (i.e., that intelligence is malleable or fixed), or if there is a continuous range of beliefs (i.e., people believe in malleability to a greater or lesser degree). Study (1) asked participants a range of general questions about the malleability of intelligence and the brain. Study (2) asked participants more specific questions about the brains of a pair of identical twins who were separated at birth. Results showed that TOI are coherent: participants’ responses to the three standard survey items are correlated with their responses to questions about the brain. But the theories are not discrete: although responses to the three standard survey items fell into a bimodal distribution, responses to the broader range of questions fell into a normal distribution suggesting the theories are continuous. PMID:26191027

Slow cortical potentials and "inner time consciousness" - A neuro-phenomenal hypothesis about the "width of present".

PubMed

Northoff, Georg

2016-05-01

William James postulated a "stream of consciousness" that presupposes temporal continuity. The neuronal mechanisms underlying the construction of such temporal continuity remain unclear, however, in my contribution, I propose a neuro-phenomenal hypothesis that is based on slow cortical potentials and their extension of the present moment as described in the phenomenal term of "width of present". More specifically, I focus on the way the brain's neural activity needs to be encoded in order to make possible the "stream of consciousness." This leads us again to the low-frequency fluctuations of the brain's neural activity and more specifically to slow cortical potentials (SCPs). Due to their long phase duration as low-frequency fluctuations, SCPs can integrate different stimuli and their associated neural activity from different regions in one converging region. Such integration may be central for consciousness to occur, as it was recently postulated by He and Raichle. They leave open, however, the question of the exact neuronal mechanisms, like the encoding strategy, that make possible the association of the otherwise purely neuronal SCP with consciousness and its phenomenal features. I hypothesize that SCPs allow for linking and connecting different discrete points in physical time by encoding their statistically based temporal differences rather than the single discrete time points by themselves. This presupposes difference-based coding rather than stimulus-based coding. The encoding of such statistically based temporal differences makes it possible to "go beyond" the merely physical features of the stimuli; that is, their single discrete time points and their conduction delays (as related to their neural processing in the brain). This, in turn, makes possible the constitution of "local temporal continuity" of neural activity in one particular region. The concept of "local temporal continuity" signifies the linkage and integration of different discrete time points into one neural activity in a particular region. How does such local temporal continuity predispose the experience of time in consciousness? For that, I turn to phenomenological philosopher Edmund Husserl and his description of what he calls "inner time consciousness" (Husserl and Brough, 1990). One hallmark of humans' "inner time consciousness" is that we experience events and objects in succession and duration in our consciousness; according to Husserl, this amounts to what he calls the "width of [the] present." The concept of the width of present describes the extension of the present beyond the single discrete time point, such as, for instance, when we perceive different tones as a melody. I now hypothesize the degree of the width of present to be directly dependent upon and thus predisposed by the degree of the temporal differences between two (or more) discrete time points as they are encoded into neural activity. I therefore conclude that the SCPs and their encoding of neural activity in terms of temporal differences must be regarded a neural predisposition of consciousness (NPC) as distinguished from a neural correlate of consciousness (NCC). Copyright © 2015 Elsevier B.V. All rights reserved.

Investigation into discretization methods of the six-parameter Iwan model

NASA Astrophysics Data System (ADS)

Li, Yikun; Hao, Zhiming; Feng, Jiaquan; Zhang, Dingguo

2017-02-01

Iwan model is widely applied for the purpose of describing nonlinear mechanisms of jointed structures. In this paper, parameter identification procedures of the six-parameter Iwan model based on joint experiments with different preload techniques are performed. Four kinds of discretization methods deduced from stiffness equation of the six-parameter Iwan model are provided, which can be used to discretize the integral-form Iwan model into a sum of finite Jenkins elements. In finite element simulation, the influences of discretization methods and numbers of Jenkins elements on computing accuracy are discussed. Simulation results indicate that a higher accuracy can be obtained with larger numbers of Jenkins elements. It is also shown that compared with other three kinds of discretization methods, the geometric series discretization based on stiffness provides the highest computing accuracy.

Combining Orthogonal Chain-End Deprotections and Thiol-Maleimide Michael Coupling: Engineering Discrete Oligomers by an Iterative Growth Strategy.

PubMed

Huang, Zhihao; Zhao, Junfei; Wang, Zimu; Meng, Fanying; Ding, Kunshan; Pan, Xiangqiang; Zhou, Nianchen; Li, Xiaopeng; Zhang, Zhengbiao; Zhu, Xiulin

2017-10-23

Orthogonal maleimide and thiol deprotections were combined with thiol-maleimide coupling to synthesize discrete oligomers/macromolecules on a gram scale with molecular weights up to 27.4 kDa (128mer, 7.9 g) using an iterative exponential growth strategy with a degree of polymerization (DP) of 2 n -1. Using the same chemistry, a "readable" sequence-defined oligomer and a discrete cyclic topology were also created. Furthermore, uniform dendrons were fabricated using sequential growth (DP=2 n -1) or double exponential dendrimer growth approaches (DP=22n -1) with significantly accelerated growth rates. A versatile, efficient, and metal-free method for construction of discrete oligomers with tailored structures and a high growth rate would greatly facilitate research into the structure-property relationships of sophisticated polymeric materials. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Template-free synthesis and structural evolution of discrete hydroxycancrinite zeolite nanorods from high-concentration hydrogels.

PubMed

Chen, Shaojiang; Sorge, Lukas P; Seo, Dong-Kyun

2017-12-07

We report the synthesis and characterization of hydroxycancrinite zeolite nanorods by a simple hydrothermal treatment of aluminosilicate hydrogels at high concentrations of precursors without the use of structure-directing agents. Transmission electron microscopy (TEM) analysis reveals that cancrinite nanorods, with lengths of 200-800 nm and diameters of 30-50 nm, exhibit a hexagonal morphology and are elongated along the crystallographic c direction. The powder X-ray diffraction (PXRD), Fourier transform infrared (FT-IR) and TEM studies revealed sequential events of hydrogel formation, the formation of aggregated sodalite nuclei, the conversion of sodalite to cancrinite and finally the growth of cancrinite nanorods into discrete particles. The aqueous dispersion of the discrete nanorods displays a good stability between pH 6-12 with the zeta potential no greater than -30 mV. The synthesis is unique in that the initial aggregated nanocrystals do not grow into microsized particles (aggregative growth) but into discrete nanorods. Our findings demonstrate an unconventional possibility that discrete zeolite nanocrystals could be produced from a concentrated hydrogel.

Discrete exterior calculus discretization of incompressible Navier-Stokes equations over surface simplicial meshes

NASA Astrophysics Data System (ADS)

Mohamed, Mamdouh S.; Hirani, Anil N.; Samtaney, Ravi

2016-05-01

A conservative discretization of incompressible Navier-Stokes equations is developed based on discrete exterior calculus (DEC). A distinguishing feature of our method is the use of an algebraic discretization of the interior product operator and a combinatorial discretization of the wedge product. The governing equations are first rewritten using the exterior calculus notation, replacing vector calculus differential operators by the exterior derivative, Hodge star and wedge product operators. The discretization is then carried out by substituting with the corresponding discrete operators based on the DEC framework. Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy for otherwise unstructured meshes. By construction, the method is conservative in that both mass and vorticity are conserved up to machine precision. The relative error in kinetic energy for inviscid flow test cases converges in a second order fashion with both the mesh size and the time step.

Factor structure and longitudinal measurement invariance of the demand control support model: an evidence from the Swedish Longitudinal Occupational Survey of Health (SLOSH).

PubMed

Chungkham, Holendro Singh; Ingre, Michael; Karasek, Robert; Westerlund, Hugo; Theorell, Töres

2013-01-01

To examine the factor structure and to evaluate the longitudinal measurement invariance of the demand-control-support questionnaire (DCSQ), using the Swedish Longitudinal Occupational Survey of Health (SLOSH). A confirmatory factor analysis (CFA) and multi-group confirmatory factor analysis (MGCFA) models within the framework of structural equation modeling (SEM) have been used to examine the factor structure and invariance across time. Four factors: psychological demand, skill discretion, decision authority and social support, were confirmed by CFA at baseline, with the best fit obtained by removing the item repetitive work of skill discretion. A measurement error correlation (0.42) between work fast and work intensively for psychological demands was also detected. Acceptable composite reliability measures were obtained except for skill discretion (0.68). The invariance of the same factor structure was established, but caution in comparing mean levels of factors over time is warranted as lack of intercept invariance was evident. However, partial intercept invariance was established for work intensively. Our findings indicate that skill discretion and decision authority represent two distinct constructs in the retained model. However removing the item repetitive work along with either work fast or work intensively would improve model fit. Care should also be taken while making comparisons in the constructs across time. Further research should investigate invariance across occupations or socio-economic classes.

Factor Structure and Longitudinal Measurement Invariance of the Demand Control Support Model: An Evidence from the Swedish Longitudinal Occupational Survey of Health (SLOSH)

PubMed Central

Chungkham, Holendro Singh; Ingre, Michael; Karasek, Robert; Westerlund, Hugo; Theorell, Töres

2013-01-01

Objectives To examine the factor structure and to evaluate the longitudinal measurement invariance of the demand-control-support questionnaire (DCSQ), using the Swedish Longitudinal Occupational Survey of Health (SLOSH). Methods A confirmatory factor analysis (CFA) and multi-group confirmatory factor analysis (MGCFA) models within the framework of structural equation modeling (SEM) have been used to examine the factor structure and invariance across time. Results Four factors: psychological demand, skill discretion, decision authority and social support, were confirmed by CFA at baseline, with the best fit obtained by removing the item repetitive work of skill discretion. A measurement error correlation (0.42) between work fast and work intensively for psychological demands was also detected. Acceptable composite reliability measures were obtained except for skill discretion (0.68). The invariance of the same factor structure was established, but caution in comparing mean levels of factors over time is warranted as lack of intercept invariance was evident. However, partial intercept invariance was established for work intensively. Conclusion Our findings indicate that skill discretion and decision authority represent two distinct constructs in the retained model. However removing the item repetitive work along with either work fast or work intensively would improve model fit. Care should also be taken while making comparisons in the constructs across time. Further research should investigate invariance across occupations or socio-economic classes. PMID:23950957

Analysis of passive damping in thick composite structures

NASA Technical Reports Server (NTRS)

Saravanos, D. A.

1993-01-01

Computational mechanics for the prediction of damping and other dynamic characteristics in composite structures of general thicknesses and laminations are presented. Discrete layer damping mechanics that account for the representation of interlaminar shear effects in the material are summarized. Finite element based structural mechanics for the analysis of damping are described, and a specialty finite element is developed. Applications illustrate the quality of the discrete layer damping mechanics in predicting the damped dynamic characteristics of composite structures with thicker sections and/or laminate configurations that induce interlaminar shear. The results also illustrate and quantify the significance of interlaminar shear damping in such composite structures.

Evidence for the Continuous Latent Structure of Mania in the Epidemiologic Catchment Area from Multiple Latent Structure and Construct Validation Methodologies

PubMed Central

Prisciandaro, James J.; Roberts, John E.

2011-01-01

Background Although psychiatric diagnostic systems have conceptualized mania as a discrete phenomenon, appropriate latent structure investigations testing this conceptualization are lacking. In contrast to these diagnostic systems, several influential theories of mania have suggested a continuous conceptualization. The present study examined whether mania has a continuous or discrete latent structure using a comprehensive approach including taxometric, information-theoretic latent distribution modeling (ITLDM), and predictive validity methodologies in the Epidemiologic Catchment Area (ECA) study. Methods Eight dichotomous manic symptom items were submitted to a variety of latent structural analyses; including factor analyses, taxometric procedures, and ITLDM; in 10,105 ECA community participants. Additionally, a variety of continuous and discrete models of mania were compared in terms of their relative abilities to predict outcomes (i.e., health service utilization, internalizing and externalizing disorders, and suicidal behavior). Results Taxometric and ITLDM analyses consistently supported a continuous conceptualization of mania. In ITLDM analyses, a continuous model of mania demonstrated 6:52:1 odds over the best fitting latent class model of mania. Factor analyses suggested that the continuous structure of mania was best represented by a single latent factor. Predictive validity analyses demonstrated a consistent superior ability of continuous models of mania relative to discrete models. Conclusions The present study provided three independent lines of support for a continuous conceptualization of mania. The implications of a continuous model of mania are discussed. PMID:20507671

From Discrete Space-Time to Minkowski Space: Basic Mechanisms, Methods and Perspectives

NASA Astrophysics Data System (ADS)

Finster, Felix

This survey article reviews recent results on fermion systems in discrete space-time and corresponding systems in Minkowski space. After a basic introduction to the discrete setting, we explain a mechanism of spontaneous symmetry breaking which leads to the emergence of a discrete causal structure. As methods to study the transition between discrete space-time and Minkowski space, we describe a lattice model for a static and isotropic space-time, outline the analysis of regularization tails of vacuum Dirac sea configurations, and introduce a Lorentz invariant action for the masses of the Dirac seas. We mention the method of the continuum limit, which allows to analyze interacting systems. Open problems are discussed.

Neurobiological correlates of distinct post-traumatic stress disorder symptom profiles during threat anticipation in combat veterans.

PubMed

Grupe, D W; Wielgosz, J; Davidson, R J; Nitschke, J B

2016-07-01

Previous research in post-traumatic stress disorder (PTSD) has identified disrupted ventromedial prefrontal cortex (vmPFC) function in those with v. without PTSD. It is unclear whether this brain region is uniformly affected in all individuals with PTSD, or whether vmPFC dysfunction is related to individual differences in discrete features of this heterogeneous disorder. In a sample of 51 male veterans of Operation Enduring Freedom/Operation Iraqi Freedom, we collected functional magnetic resonance imaging data during a novel threat anticipation task with crossed factors of threat condition and temporal unpredictability. Voxelwise regression analyses related anticipatory brain activation to individual differences in overall PTSD symptom severity, as well as individual differences in discrete symptom subscales (re-experiencing, emotional numbing/avoidance, and hyperarousal). The vmPFC showed greater anticipatory responses for safety relative to threat, driven primarily by deactivation during threat anticipation. During unpredictable threat anticipation, increased PTSD symptoms were associated with relatively greater activation for threat v. However, simultaneous regression on individual symptom subscales demonstrated that this effect was driven specifically by individual differences in hyperarousal symptoms. Furthermore, this analysis revealed an additional, anatomically distinct region of the vmPFC in which re-experiencing symptoms were associated with greater activation during threat anticipation. Increased anticipatory responses to unpredictable threat in distinct vmPFC subregions were uniquely associated with elevated hyperarousal and re-experiencing symptoms in combat veterans. These results underscore the disruptive impact of uncertainty for veterans, and suggest that investigating individual differences in discrete aspects of PTSD may advance our understanding of underlying neurobiological mechanisms.

Adolescent cocaine exposure simplifies orbitofrontal cortical dendritic arbors

PubMed Central

DePoy, Lauren M.; Perszyk, Riley E.; Zimmermann, Kelsey S.; Koleske, Anthony J.; Gourley, Shannon L.

2014-01-01

Cocaine and amphetamine remodel dendritic spines within discrete cortico-limbic brain structures including the orbitofrontal cortex (oPFC). Whether dendrite structure is similarly affected, and whether pre-existing cellular characteristics influence behavioral vulnerabilities to drugs of abuse, remain unclear. Animal models provide an ideal venue to address these issues because neurobehavioral phenotypes can be defined both before, and following, drug exposure. We exposed mice to cocaine from postnatal days 31–35, corresponding to early adolescence, using a dosing protocol that causes impairments in an instrumental reversal task in adulthood. We then imaged and reconstructed excitatory neurons in deep-layer oPFC. Prior cocaine exposure shortened and simplified arbors, particularly in the basal region. Next, we imaged and reconstructed orbital neurons in a developmental-genetic model of cocaine vulnerability—the p190rhogap+/– mouse. p190RhoGAP is an actin cytoskeleton regulatory protein that stabilizes dendrites and dendritic spines, and p190rhogap+/– mice develop rapid and robust locomotor activation in response to cocaine. Despite this, oPFC dendritic arbors were intact in drug-naïve p190rhogap+/– mice. Together, these findings provide evidence that adolescent cocaine exposure has long-term effects on dendrite structure in the oPFC, and they suggest that cocaine-induced modifications in dendrite structure may contribute to the behavioral effects of cocaine more so than pre-existing structural abnormalities in this cell population. PMID:25452728

Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment.

PubMed

Peters, Sarah K; Dunlop, Katharine; Downar, Jonathan

2016-01-01

The salience network (SN) plays a central role in cognitive control by integrating sensory input to guide attention, attend to motivationally salient stimuli and recruit appropriate functional brain-behavior networks to modulate behavior. Mounting evidence suggests that disturbances in SN function underlie abnormalities in cognitive control and may be a common etiology underlying many psychiatric disorders. Such functional and anatomical abnormalities have been recently apparent in studies and meta-analyses of psychiatric illness using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). Of particular importance, abnormal structure and function in major cortical nodes of the SN, the dorsal anterior cingulate cortex (dACC) and anterior insula (AI), have been observed as a common neurobiological substrate across a broad spectrum of psychiatric disorders. In addition to cortical nodes of the SN, the network's associated subcortical structures, including the dorsal striatum, mediodorsal thalamus and dopaminergic brainstem nuclei, comprise a discrete regulatory loop circuit. The SN's cortico-striato-thalamo-cortical loop increasingly appears to be central to mechanisms of cognitive control, as well as to a broad spectrum of psychiatric illnesses and their available treatments. Functional imbalances within the SN loop appear to impair cognitive control, and specifically may impair self-regulation of cognition, behavior and emotion, thereby leading to symptoms of psychiatric illness. Furthermore, treating such psychiatric illnesses using invasive or non-invasive brain stimulation techniques appears to modulate SN cortical-subcortical loop integrity, and these effects may be central to the therapeutic mechanisms of brain stimulation treatments in many psychiatric illnesses. Here, we review clinical and experimental evidence for abnormalities in SN cortico-striatal-thalamic loop circuits in major depression, substance use disorders (SUD), anxiety disorders, schizophrenia and eating disorders (ED). We also review emergent therapeutic evidence that novel invasive and non-invasive brain stimulation treatments may exert therapeutic effects by normalizing abnormalities in the SN loop, thereby restoring the capacity for cognitive control. Finally, we consider a series of promising directions for future investigations on the role of SN cortico-striatal-thalamic loop circuits in the pathophysiology and treatment of psychiatric disorders.

Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment

PubMed Central

Peters, Sarah K.; Dunlop, Katharine; Downar, Jonathan

2016-01-01

The salience network (SN) plays a central role in cognitive control by integrating sensory input to guide attention, attend to motivationally salient stimuli and recruit appropriate functional brain-behavior networks to modulate behavior. Mounting evidence suggests that disturbances in SN function underlie abnormalities in cognitive control and may be a common etiology underlying many psychiatric disorders. Such functional and anatomical abnormalities have been recently apparent in studies and meta-analyses of psychiatric illness using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). Of particular importance, abnormal structure and function in major cortical nodes of the SN, the dorsal anterior cingulate cortex (dACC) and anterior insula (AI), have been observed as a common neurobiological substrate across a broad spectrum of psychiatric disorders. In addition to cortical nodes of the SN, the network’s associated subcortical structures, including the dorsal striatum, mediodorsal thalamus and dopaminergic brainstem nuclei, comprise a discrete regulatory loop circuit. The SN’s cortico-striato-thalamo-cortical loop increasingly appears to be central to mechanisms of cognitive control, as well as to a broad spectrum of psychiatric illnesses and their available treatments. Functional imbalances within the SN loop appear to impair cognitive control, and specifically may impair self-regulation of cognition, behavior and emotion, thereby leading to symptoms of psychiatric illness. Furthermore, treating such psychiatric illnesses using invasive or non-invasive brain stimulation techniques appears to modulate SN cortical-subcortical loop integrity, and these effects may be central to the therapeutic mechanisms of brain stimulation treatments in many psychiatric illnesses. Here, we review clinical and experimental evidence for abnormalities in SN cortico-striatal-thalamic loop circuits in major depression, substance use disorders (SUD), anxiety disorders, schizophrenia and eating disorders (ED). We also review emergent therapeutic evidence that novel invasive and non-invasive brain stimulation treatments may exert therapeutic effects by normalizing abnormalities in the SN loop, thereby restoring the capacity for cognitive control. Finally, we consider a series of promising directions for future investigations on the role of SN cortico-striatal-thalamic loop circuits in the pathophysiology and treatment of psychiatric disorders. PMID:28082874

Matching Extension in Regular Graphs

DTIC Science & Technology

1989-01-01

Plummer, Matching Theory, Ann. Discrete Math . 29, North- Holland, Amsterdam, 1986. [101 , The matching structure of graphs: some recent re- sults...maximums d’un graphe, These, Dr. troisieme cycle, Univ. Grenoble, 1978. [12 ] D. Naddef and W.R. Pulleyblank, Matching in regular graphs, Discrete Math . 34...1981, 283-291. [13 1 M.D. Plummer, On n-extendable graphs, Discrete Math . 31, 1980, 201-210. . [ 141 ,Matching extension in planar graphs IV

Peridynamics with LAMMPS : a user guide.

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

Lehoucq, Richard B.; Silling, Stewart Andrew; Plimpton, Steven James

2008-01-01

Peridynamics is a nonlocal formulation of continuum mechanics. The discrete peridynamic model has the same computational structure as a molecular dynamic model. This document details the implementation of a discrete peridynamic model within the LAMMPS molecular dynamic code. This document provides a brief overview of the peridynamic model of a continuum, then discusses how the peridynamic model is discretized, and overviews the LAMMPS implementation. A nontrivial example problem is also included.

A combined MR and CT study for precise quantitative analysis of the avian brain

NASA Astrophysics Data System (ADS)

Jirak, Daniel; Janacek, Jiri; Kear, Benjamin P.

2015-10-01

Brain size is widely used as a measure of behavioural complexity and sensory-locomotive capacity in avians but has largely relied upon laborious dissections, endoneurocranial tissue displacement, and physical measurement to derive comparative volumes. As an alternative, we present a new precise calculation method based upon coupled magnetic resonance (MR) imaging and computed tomography (CT). Our approach utilizes a novel interactive Fakir probe cross-referenced with an automated CT protocol to efficiently generate total volumes and surface areas of the brain tissue and endoneurocranial space, as well as the discrete cephalic compartments. We also complemented our procedures by using sodium polytungstate (SPT) as a contrast agent. This greatly enhanced CT applications but did not degrade MR quality and is therefore practical for virtual brain tissue reconstructions employing multiple imaging modalities. To demonstrate our technique, we visualized sex-based brain size differentiation in a sample set of Ring-necked pheasants (Phasianus colchicus). This revealed no significant variance in relative volume or surface areas of the primary brain regions. Rather, a trend towards isometric enlargement of the total brain and endoneurocranial space was evidenced in males versus females, thus advocating a non-differential sexually dimorphic pattern of brain size increase amongst these facultatively flying birds.

A Cobalt Supramolecular Triple-Stranded Helicate-based Discrete Molecular Cage

PubMed Central

Mai, Hien Duy; Kang, Philjae; Kim, Jin Kyung; Yoo, Hyojong

2017-01-01

We report a strategy to achieve a discrete cage molecule featuring a high level of structural hierarchy through a multiple-assembly process. A cobalt (Co) supramolecular triple-stranded helicate (Co-TSH)-based discrete molecular cage (1) is successfully synthesized and fully characterized. The solid-state structure of 1 shows that it is composed of six triple-stranded helicates interconnected by four linking cobalt species. This is an unusual example of a highly symmetric cage architecture resulting from the coordination-driven assembly of metallosupramolecular modules. The molecular cage 1 shows much higher CO2 uptake properties and selectivity compared with the separate supramolecular modules (Co-TSH, complex 2) and other molecular platforms. PMID:28262690

Computing approximate solutions of the protein structure determination problem using global constraints on discrete crystal lattices.

PubMed

Dal Palù, Alessandro; Dovier, Agostino; Pontelli, Enrico

2010-01-01

Crystal lattices are discrete models of the three-dimensional space that have been effectively employed to facilitate the task of determining proteins' natural conformation. This paper investigates alternative global constraints that can be introduced in a constraint solver over discrete crystal lattices. The objective is to enhance the efficiency of lattice solvers in dealing with the construction of approximate solutions of the protein structure determination problem. Some of them (e.g., self-avoiding-walk) have been explicitly or implicitly already used in previous approaches, while others (e.g., the density constraint) are new. The intrinsic complexities of all of them are studied and preliminary experimental results are discussed.

RELATIONSHIP BETWEEN LINGUISTIC UNITS AND MOTOR COMMANDS.

ERIC Educational Resources Information Center

FROMKIN, VICTORIA A.

ASSUMING THAT SPEECH IS THE RESULT OF A NUMBER OF DISCRETE NEUROMUSCULAR EVENTS AND THAT THE BRAIN CAN STORE ONLY A LIMITED NUMBER OF MOTOR COMMANDS WITH WHICH TO CONTROL THESE EVENTS, THE RESEARCH REPORTED IN THIS PAPER WAS DIRECTED TO A DETERMINATION OF THE SIZE AND NATURE OF THE STORED ITEMS AND AN EXPLANATION OF HOW SPEAKERS ENCODE A SEQUENCE…

Biomarkers for visceral hypersensitivity identified by classification of electroencephalographic frequency alterations

NASA Astrophysics Data System (ADS)

Graversen, Carina; Brock, Christina; Mohr Drewes, Asbjørn; Farina, Dario

2011-10-01

Abdominal pain is frequently related to visceral hypersensitivity. This is associated with increased neuronal excitability in the central nervous system (CNS), which can be manifested as discrete electroencephalographic (EEG) alterations. In the current placebo-controlled study, visceral hypersensitivity was evoked by chemical irritation of the esophagus with acid and capsaicin perfusion. The resulting hyperexcitability of the CNS was evaluated by evoked brain potentials following painful electrical stimulations of a remote organ—the rectosigmoid colon. Alterations in individual EEG power distributions between baseline and after perfusion were quantified by extracting features from the evoked brain potentials using an optimized discrete wavelet transform. Visceral hypersensitivity was identified as increased EEG power in the delta, theta and alpha frequency bands. By applying a support vector machine in regression mode, the individual baseline corrected alterations after sensitization were discriminated from alterations caused by placebo perfusions. An accuracy of 91.7% was obtained (P < 0.01). The regression value representing the overall alteration of the EEG correlated with the degree of hyperalgesia (P = 0.03). In conclusion, this study showed that classification of EEG can be used to detect biomarkers reflecting central neuronal changes. In the future, this may be used in studies of pain physiology and pharmacological interventions.

High-grade glioma diffusive modeling using statistical tissue information and diffusion tensors extracted from atlases.

PubMed

Roniotis, Alexandros; Manikis, Georgios C; Sakkalis, Vangelis; Zervakis, Michalis E; Karatzanis, Ioannis; Marias, Kostas

2012-03-01

Glioma, especially glioblastoma, is a leading cause of brain cancer fatality involving highly invasive and neoplastic growth. Diffusive models of glioma growth use variations of the diffusion-reaction equation in order to simulate the invasive patterns of glioma cells by approximating the spatiotemporal change of glioma cell concentration. The most advanced diffusive models take into consideration the heterogeneous velocity of glioma in gray and white matter, by using two different discrete diffusion coefficients in these areas. Moreover, by using diffusion tensor imaging (DTI), they simulate the anisotropic migration of glioma cells, which is facilitated along white fibers, assuming diffusion tensors with different diffusion coefficients along each candidate direction of growth. Our study extends this concept by fully exploiting the proportions of white and gray matter extracted by normal brain atlases, rather than discretizing diffusion coefficients. Moreover, the proportions of white and gray matter, as well as the diffusion tensors, are extracted by the respective atlases; thus, no DTI processing is needed. Finally, we applied this novel glioma growth model on real data and the results indicate that prognostication rates can be improved. © 2012 IEEE

Genetic Approaches to Reveal the Connectivity of Adult-Born Neurons

PubMed Central

Arenkiel, Benjamin R.

2011-01-01

Much has been learned about the environmental and molecular factors that influence the division, migration, and programmed cell death of adult-born neurons in the mammalian brain. However, detailed knowledge of the mechanisms that govern the formation and maintenance of functional circuit connectivity via adult neurogenesis remains elusive. Recent advances in genetic technologies now afford the ability to precisely target discrete brain tissues, neuronal subtypes, and even single neurons for vital reporter expression and controlled activity manipulations. Here, I review current viral tracing methods, heterologous receptor expression systems, and optogenetic technologies that hold promise toward elucidating the wiring diagrams and circuit properties of adult-born neurons. PMID:21519388

Inferring network structure in non-normal and mixed discrete-continuous genomic data.

PubMed

Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2018-03-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. © 2017, The International Biometric Society.

Inferring network structure in non-normal and mixed discrete-continuous genomic data

PubMed Central

Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran

2017-01-01

Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. PMID:28437848

Fundamentals of translational neuroscience in toxicologic pathology: optimizing the value of animal data for human risk assessment.

PubMed

Morrison, James P; Sharma, Alok K; Rao, Deepa; Pardo, Ingrid D; Garman, Robert H; Kaufmann, Wolfgang; Bolon, Brad

2015-01-01

A half-day Society of Toxicologic Pathology continuing education course on "Fundamentals of Translational Neuroscience in Toxicologic Pathology" presented some current major issues faced when extrapolating animal data regarding potential neurological consequences to assess potential human outcomes. Two talks reviewed functional-structural correlates in rodent and nonrodent mammalian brains needed to predict behavioral consequences of morphologic changes in discrete neural cell populations. The third lecture described practical steps for ensuring that specimens from rodent developmental neurotoxicity tests will be processed correctly to produce highly homologous sections. The fourth talk detailed demographic factors (e.g., species, strain, sex, and age); physiological traits (body composition, brain circulation, pharmacokinetic/pharmacodynamic patterns, etc.); and husbandry influences (e.g., group housing) known to alter the effects of neuroactive agents. The last presentation discussed the appearance, unknown functional effects, and potential relevance to humans of polyethylene glycol (PEG)-associated vacuoles within the choroid plexus epithelium of animals. Speakers provided real-world examples of challenges with data extrapolation among species or with study design considerations that may impact the interpretability of results. Translational neuroscience will be bolstered in the future as less invasive and/or more quantitative techniques are devised for linking overt functional deficits to subtle anatomic and chemical lesions. © 2014 by The Author(s).

Broadband superior electromagnetic absorption of a discrete-structure microwave coating

NASA Astrophysics Data System (ADS)

Duan, Yuping; Xi, Qun; Liu, Wei; Wang, Tongmin

2016-10-01

A method of improving the electromagnetic (EM) absorption property of conventional microwave absorber (CMA) is proposed here. The structural design process was mainly concerned with systematic analysis and research into the impedance matching characteristic and induced current. By processing a CMA-carbonyl-iron powder (CIP) coating into many isolated regions, the discrete-structure microwave absorber (DMA) had a much better absorption property than the corresponding CMA. When the thickness was only 2.0 mm and the component content was 33 wt%, the loss of reflection was less than -10 dB shifted from 6-7 GHz to 7-13 GHz and the loss of minimum reflection decreased from 12.5 dB lost to 32 dB lost through a discrete-structure process. The microwave absorption properties of coatings with different component contents and thicknesses were investigated. The minimum reflection peaks tended to shift towards the lower frequency region as CIP content or coating thickness increased. By adjusting these three factors, a high-performance broadband absorber was produced.

Discrete particle model for cement infiltration within open-cell structures: Prevention of osteoporotic fracture.

PubMed

Ramos-Infante, Samuel Jesús; Ten-Esteve, Amadeo; Alberich-Bayarri, Angel; Pérez, María Angeles

2018-01-01

This paper proposes a discrete particle model based on the random-walk theory for simulating cement infiltration within open-cell structures to prevent osteoporotic proximal femur fractures. Model parameters consider the cement viscosity (high and low) and the desired direction of injection (vertical and diagonal). In vitro and in silico characterizations of augmented open-cell structures validated the computational model and quantified the improved mechanical properties (Young's modulus) of the augmented specimens. The cement injection pattern was successfully predicted in all the simulated cases. All the augmented specimens exhibited enhanced mechanical properties computationally and experimentally (maximum improvements of 237.95 ± 12.91% and 246.85 ± 35.57%, respectively). The open-cell structures with high porosity fraction showed a considerable increase in mechanical properties. Cement augmentation in low porosity fraction specimens resulted in a lesser increase in mechanical properties. The results suggest that the proposed discrete particle model is adequate for use as a femoroplasty planning framework.

The modified semi-discrete two-dimensional Toda lattice with self-consistent sources

NASA Astrophysics Data System (ADS)

Gegenhasi

2017-07-01

In this paper, we derive the Grammian determinant solutions to the modified semi-discrete two-dimensional Toda lattice equation, and then construct the semi-discrete two-dimensional Toda lattice equation with self-consistent sources via source generation procedure. The algebraic structure of the resulting coupled modified differential-difference equation is clarified by presenting its Grammian determinant solutions and Casorati determinant solutions. As an application of the Grammian determinant and Casorati determinant solution, the explicit one-soliton and two-soliton solution of the modified semi-discrete two-dimensional Toda lattice equation with self-consistent sources are given. We also construct another form of the modified semi-discrete two-dimensional Toda lattice equation with self-consistent sources which is the Bäcklund transformation for the semi-discrete two-dimensional Toda lattice equation with self-consistent sources.

Boundaries, kinetic properties, and final domain structure of plane discrete uniform Poisson-Voronoi tessellations with von Neumann neighborhoods.

PubMed

Korobov, A

2009-03-01

Discrete random tessellations appear not infrequently in describing nucleation and growth transformations. Generally, several non-Euclidean metrics are possible in this case. Previously [A. Korobov, Phys. Rev. B 76, 085430 (2007)] continual analogs of such tessellations have been studied. Here one of the simplest discrete varieties of the Kolmogorov-Johnson-Mehl-Avrami model, namely, the model with von Neumann neighborhoods, has been examined per se, i.e., without continualization. The tessellation is uniform in the sense that domain boundaries consist of tiles. Similarities and distinctions between discrete and continual models are discussed.

Reflexive aerostructures: increased vehicle survivability

NASA Astrophysics Data System (ADS)

Margraf, Thomas W.; Hemmelgarn, Christopher D.; Barnell, Thomas J.; Franklin, Mark A.

2007-04-01

Aerospace systems stand to benefit significantly from the advancement of reflexive aerostructure technologies for increased vehicle survivability. Cornerstone Research Group Inc. (CRG) is developing lightweight, healable composite systems for use as primary load-bearing aircraft components. The reflexive system is comprised of piezoelectric structural health monitoring systems, localized thermal activation systems, and lightweight, healable composite structures. The reflexive system is designed to mimic the involuntary human response to damage. Upon impact, the structural health monitoring system will identify the location and magnitude of the damage, sending a signal to a discrete thermal activation control system to resistively heat the shape memory polymer (SMP) matrix composite above activation temperature, resulting in localized shape recovery and healing of the damaged areas. CRG has demonstrated SMP composites that can recover 90 percent of flexural yield stress and modulus after postfailure healing. During the development, CRG has overcome issues of discrete activation, structural health monitoring integration, and healable resin systems. This paper will address the challenges associated with development of a reflexive aerostructure, including integration of structural health monitoring, discrete healing, and healable shape memory resin systems.

Brain glycogen decreases during prolonged exercise

PubMed Central

Matsui, Takashi; Soya, Shingo; Okamoto, Masahiro; Ichitani, Yukio; Kawanaka, Kentaro; Soya, Hideaki

2011-01-01

Abstract Brain glycogen could be a critical energy source for brain activity when the glucose supply from the blood is inadequate (hypoglycaemia). Although untested, it is hypothesized that during prolonged exhaustive exercise that induces hypoglycaemia and muscular glycogen depletion, the resultant hypoglycaemia may cause a decrease in brain glycogen. Here, we tested this hypothesis and also investigated the possible involvement of brain monoamines with the reduced levels of brain glycogen. For this purpose, we exercised male Wistar rats on a treadmill for different durations (30–120 min) at moderate intensity (20 m min−1) and measured their brain glycogen levels using high-power microwave irradiation (10 kW). At the end of 30 and 60 min of running, the brain glycogen levels remained unchanged from resting levels, but liver and muscle glycogen decreased. After 120 min of running, the glycogen levels decreased significantly by ∼37–60% in five discrete brain loci (the cerebellum 60%, cortex 48%, hippocampus 43%, brainstem 37% and hypothalamus 34%) compared to those of the sedentary control. The brain glycogen levels in all five regions after running were positively correlated with the respective blood and brain glucose levels. Further, in the cortex, the levels of methoxyhydroxyphenylglycol (MHPG) and 5-hydroxyindoleacetic acid (5-HIAA), potential involved in degradation of the brain glycogen, increased during prolonged exercise and negatively correlated with the glycogen levels. These results support the hypothesis that brain glycogen could decrease with prolonged exhaustive exercise. Increased monoamines together with hypoglycaemia should be associated with the development of decreased brain glycogen, suggesting a new clue towards the understanding of central fatigue during prolonged exercise. PMID:21521757

Psychiatry as a Clinical Neuroscience Discipline

PubMed Central

Insel, Thomas R.; Quirion, Remi

2006-01-01

One of the fundamental insights emerging from contemporary neuroscience is that mental illnesses are brain disorders. In contrast to classic neurological illnesses that involve discrete brain lesions, mental disorders need to be addressed as disorders of distributed brain systems with symptoms forged by developmental and social experiences. While genomics will be important for revealing risk, and cellular neuroscience should provide targets for novel treatments for these disorders, it is most likely that the tools of systems neuroscience will yield the biomarkers needed to revolutionize psychiatric diagnosis and treatment. This essay considers the discoveries that will be necessary over the next two decades to translate the promise of modern neuroscience into strategies for prevention and cures of mental disorders. To deliver on this spectacular new potential, clinical neuroscience must be integrated into the discipline of psychiatry, thereby transforming current psychiatric training, tools, and practices. PMID:16264165

Time course of brain activation elicited by basic emotions.

PubMed

Hot, Pascal; Sequeira, Henrique

2013-11-13

Whereas facial emotion recognition protocols have shown that each discrete emotion has a specific time course of brain activation, there is no electrophysiological evidence to support these findings for emotional induction by complex pictures. Our objective was to specify the differences between the time courses of brain activation elicited by feelings of happiness and, with unpleasant pictures, by feelings of disgust and sadness. We compared event-related potentials (ERPs) elicited by the watching of high-arousing pictures from the International Affective Picture System, selected to induce specific emotions. In addition to a classical arousal effect on late positive components, we found specific ERP patterns for each emotion in early temporal windows (<200 ms). Disgust was the first emotion to be associated with different brain processing after 140 ms, whereas happiness and sadness differed in ERPs elicited at the frontal and central sites after 160 ms. Our findings highlight the limits of the classical averaging of ERPs elicited by different emotions inside the same valence and suggest that each emotion could elicit a specific temporal pattern of brain activation, similar to those observed with emotional face recognition.

Building an organic computing device with multiple interconnected brains

PubMed Central

Pais-Vieira, Miguel; Chiuffa, Gabriela; Lebedev, Mikhail; Yadav, Amol; Nicolelis, Miguel A. L.

2015-01-01

Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical neurons distributed across multiple rats chronically implanted with multi-electrode arrays. Cortical neuronal activity was recorded and analyzed in real time, and then delivered to the somatosensory cortices of other animals that participated in the Brainet using intracortical microstimulation (ICMS). Using this approach, different Brainet architectures solved a number of useful computational problems, such as discrete classification, image processing, storage and retrieval of tactile information, and even weather forecasting. Brainets consistently performed at the same or higher levels than single rats in these tasks. Based on these findings, we propose that Brainets could be used to investigate animal social behaviors as well as a test bed for exploring the properties and potential applications of organic computers. PMID:26158615

A program for calculating photonic band structures, Green's functions and transmission/reflection coefficients using a non-orthogonal FDTD method

NASA Astrophysics Data System (ADS)

Ward, A. J.; Pendry, J. B.

2000-06-01

In this paper we present an updated version of our ONYX program for calculating photonic band structures using a non-orthogonal finite difference time domain method. This new version employs the same transparent formalism as the first version with the same capabilities for calculating photonic band structures or causal Green's functions but also includes extra subroutines for the calculation of transmission and reflection coefficients. Both the electric and magnetic fields are placed onto a discrete lattice by approximating the spacial and temporal derivatives with finite differences. This results in discrete versions of Maxwell's equations which can be used to integrate the fields forwards in time. The time required for a calculation using this method scales linearly with the number of real space points used in the discretization so the technique is ideally suited to handling systems with large and complicated unit cells.

A computer-assisted study of pulse dynamics in anisotropic media

NASA Astrophysics Data System (ADS)

Krishnan, J.; Engelborghs, K.; Bär, M.; Lust, K.; Roose, D.; Kevrekidis, I. G.

2001-06-01

This study focuses on the computer-assisted stability analysis of travelling pulse-like structures in spatially periodic heterogeneous reaction-diffusion media. The physical motivation comes from pulse propagation in thin annular domains on a diffusionally anisotropic catalytic surface. The study was performed by computing the travelling pulse-like structures as limit cycles of the spatially discretized PDE, which in turn is performed in two ways: a Newton method based on a pseudospectral discretization of the PDE, and a Newton-Picard method based on a finite difference discretization. Details about the spectra of these modulated pulse-like structures are discussed, including how they may be compared with the spectra of pulses in homogeneous media. The effects of anisotropy on the dynamics of pulses and pulse pairs are studied. Beyond shifting the location of bifurcations present in homogeneous media, anisotropy can also introduce certain new instabilities.

2D discontinuous piecewise linear map: Emergence of fashion cycles.

PubMed

Gardini, L; Sushko, I; Matsuyama, K

2018-05-01

We consider a discrete-time version of the continuous-time fashion cycle model introduced in Matsuyama, 1992. Its dynamics are defined by a 2D discontinuous piecewise linear map depending on three parameters. In the parameter space of the map periodicity, regions associated with attracting cycles of different periods are organized in the period adding and period incrementing bifurcation structures. The boundaries of all the periodicity regions related to border collision bifurcations are obtained analytically in explicit form. We show the existence of several partially overlapping period incrementing structures, that is, a novelty for the considered class of maps. Moreover, we show that if the time-delay in the discrete time formulation of the model shrinks to zero, the number of period incrementing structures tends to infinity and the dynamics of the discrete time fashion cycle model converges to those of continuous-time fashion cycle model.

Metriplectic integrators for the Landau collision operator

DOE PAGES

Kraus, Michael; Hirvijoki, Eero

2017-10-02

Here, we present a novel framework for addressing the nonlinear Landau collision integral in terms of finite element and other subspace projection methods. We employ the underlying metriplectic structure of the Landau collision integral and, using a Galerkin discretization for the velocity space, we transform the infinite-dimensional system into a finite-dimensional, time-continuous metriplectic system. Temporal discretization is accomplished using the concept of discrete gradients. The conservation of energy, momentum, and particle densities, as well as the production of entropy is demonstrated algebraically for the fully discrete system. Due to the generality of our approach, the conservation properties and the monotonicmore » behavior of entropy are guaranteed for finite element discretizations, in general, independently of the mesh configuration.« less

Effect of the surface charge discretization on electric double layers: a Monte Carlo simulation study.

PubMed

Madurga, Sergio; Martín-Molina, Alberto; Vilaseca, Eudald; Mas, Francesc; Quesada-Pérez, Manuel

2007-06-21

The structure of the electric double layer in contact with discrete and continuously charged planar surfaces is studied within the framework of the primitive model through Monte Carlo simulations. Three different discretization models are considered together with the case of uniform distribution. The effect of discreteness is analyzed in terms of charge density profiles. For point surface groups, a complete equivalence with the situation of uniformly distributed charge is found if profiles are exclusively analyzed as a function of the distance to the charged surface. However, some differences are observed moving parallel to the surface. Significant discrepancies with approaches that do not account for discreteness are reported if charge sites of finite size placed on the surface are considered.

Identification of a set of genes showing regionally enriched expression in the mouse brain

PubMed Central

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa LC; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven JM

2008-01-01

Background The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. Results We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Conclusion Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression. PMID:18625066

Identification of a set of genes showing regionally enriched expression in the mouse brain.

PubMed

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa L C; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven J M

2008-07-14

The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

Discrete Kalman filtering equations of second-order form for control-structure interaction simulations

NASA Technical Reports Server (NTRS)

Park, K. C.; Alvin, K. F.; Belvin, W. Keith

1991-01-01

A second-order form of discrete Kalman filtering equations is proposed as a candidate state estimator for efficient simulations of control-structure interactions in coupled physical coordinate configurations as opposed to decoupled modal coordinates. The resulting matrix equation of the present state estimator consists of the same symmetric, sparse N x N coupled matrices of the governing structural dynamics equations as opposed to unsymmetric 2N x 2N state space-based estimators. Thus, in addition to substantial computational efficiency improvement, the present estimator can be applied to control-structure design optimization for which the physical coordinates associated with the mass, damping and stiffness matrices of the structure are needed instead of modal coordinates.

Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations

PubMed Central

Brodie, Nicholas I.; Popov, Konstantin I.; Petrotchenko, Evgeniy V.; Dokholyan, Nikolay V.; Borchers, Christoph H.

2017-01-01

We present an integrated experimental and computational approach for de novo protein structure determination in which short-distance cross-linking data are incorporated into rapid discrete molecular dynamics (DMD) simulations as constraints, reducing the conformational space and achieving the correct protein folding on practical time scales. We tested our approach on myoglobin and FK506 binding protein—models for α helix–rich and β sheet–rich proteins, respectively—and found that the lowest-energy structures obtained were in agreement with the crystal structure, hydrogen-deuterium exchange, surface modification, and long-distance cross-linking validation data. Our approach is readily applicable to other proteins with unknown structures. PMID:28695211

Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations.

PubMed

Brodie, Nicholas I; Popov, Konstantin I; Petrotchenko, Evgeniy V; Dokholyan, Nikolay V; Borchers, Christoph H

2017-07-01

We present an integrated experimental and computational approach for de novo protein structure determination in which short-distance cross-linking data are incorporated into rapid discrete molecular dynamics (DMD) simulations as constraints, reducing the conformational space and achieving the correct protein folding on practical time scales. We tested our approach on myoglobin and FK506 binding protein-models for α helix-rich and β sheet-rich proteins, respectively-and found that the lowest-energy structures obtained were in agreement with the crystal structure, hydrogen-deuterium exchange, surface modification, and long-distance cross-linking validation data. Our approach is readily applicable to other proteins with unknown structures.

A new spatial multiple discrete-continuous modeling approach to land use change analysis.

DOT National Transportation Integrated Search

2013-09-01

This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

40 CFR 401.11 - General definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Environmental Protection Agency. (d) The term point source means any discernible, confined and discrete conveyance, including but not limited to any pipe, ditch, channel, tunnel, conduit, well, discrete fissure... which pollutants are or may be discharged. (e) The term new source means any building, structure...

Structure and Development of the Subesophageal Zone of the Drosophila Brain. II. Sensory Compartments

PubMed Central

Kendroud, Sarah; Bohra, Ali Asgar; Kuert, Philipp A.; Nguyen, Bao; Guillermin, Oriane; Sprecher, Simon G.; Reichert, Heinrich; VijayRaghavan, Krishnaswamy; Hartenstein, Volker

2018-01-01

The subesophageal zone (SEZ) of the Drosophila brain processes mechanosensory and gustatory sensory input from sensilla located on the head, mouth cavity and trunk. Motor output from the SEZ directly controls the movements involved in feeding behavior. In an accompanying paper (Hartenstein et al., 2017) we analyzed the systems of fiber tracts and secondary lineages to establish reliable criteria for defining boundaries between the four neuromeres of the SEZ, as well as discrete longitudinal neuropil domains within each SEZ neuromere. Here we use this anatomical framework to systematically map the sensory projections entering the SEZ throughout development. Our findings show a continuity between larval and adult sensory neuropils. Gustatory axons from internal and external taste sensilla of the larva and adult form two closely related sensory projections, (1) the anterior central sensory center (ACSC) located deep in the ventromedial neuropil of the tritocerebrum and mandibular neuromere, and (2) the anterior ventral sensory center (AVSC), occupying a superficial layer within the ventromedial tritocerebrum. Additional, presumed mechanosensory terminal axons entering via the labial nerve define the ventromedial sensory center (VMSC) in the maxilla and labium. Mechanosensory afferents of the massive array of chordotonal organs (Johnston’s organ) of the adult antenna project into the centrolateral neuropil column of the anterior SEZ, creating the antenno-mechanosensory and motor center (AMMC). Dendritic projections of dye back-filled motor neurons extend throughout a ventral layer of the SEZ, overlapping widely with the AVSC and VMSC. Our findings elucidate fundamental structural aspects of the developing sensory systems in Drosophila. PMID:28875566

Single-Cell Transcriptomics Reveals a Population of Dormant Neural Stem Cells that Become Activated upon Brain Injury.

PubMed

Llorens-Bobadilla, Enric; Zhao, Sheng; Baser, Avni; Saiz-Castro, Gonzalo; Zwadlo, Klara; Martin-Villalba, Ana

2015-09-03

Heterogeneous pools of adult neural stem cells (NSCs) contribute to brain maintenance and regeneration after injury. The balance of NSC activation and quiescence, as well as the induction of lineage-specific transcription factors, may contribute to diversity of neuronal and glial fates. To identify molecular hallmarks governing these characteristics, we performed single-cell sequencing of an unbiased pool of adult subventricular zone NSCs. This analysis identified a discrete, dormant NSC subpopulation that already expresses distinct combinations of lineage-specific transcription factors during homeostasis. Dormant NSCs enter a primed-quiescent state before activation, which is accompanied by downregulation of glycolytic metabolism, Notch, and BMP signaling and a concomitant upregulation of lineage-specific transcription factors and protein synthesis. In response to brain ischemia, interferon gamma signaling induces dormant NSC subpopulations to enter the primed-quiescent state. This study unveils general principles underlying NSC activation and lineage priming and opens potential avenues for regenerative medicine in the brain. Copyright © 2015 Elsevier Inc. All rights reserved.

Fluid and flexible minds: Intelligence reflects synchrony in the brain’s intrinsic network architecture

PubMed Central

Ferguson, Michael A.; Anderson, Jeffrey S.; Spreng, R. Nathan

2017-01-01

Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease.

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

Local atomic and electronic structure of oxide/GaAs and SiO2/Si interfaces using high-resolution XPS

NASA Technical Reports Server (NTRS)

Grunthaner, F. J.; Grunthaner, P. J.; Vasquez, R. P.; Lewis, B. F.; Maserjian, J.; Madhukar, A.

1979-01-01

The chemical structures of thin SiO2 films, thin native oxides of GaAs (20-30 A), and the respective oxide-semiconductor interfaces, have been investigated using high-resolution X-ray photoelectron spectroscopy. Depth profiles of these structures have been obtained using argon ion bombardment and wet chemical etching techniques. The chemical destruction induced by the ion profiling method is shown by direct comparison of these methods for identical samples. Fourier transform data-reduction methods based on linear prediction with maximum entropy constraints are used to analyze the discrete structure in oxides and substrates. This discrete structure is interpreted by means of a structure-induced charge-transfer model.

Topology and layout optimization of discrete and continuum structures

NASA Technical Reports Server (NTRS)

Bendsoe, Martin P.; Kikuchi, Noboru

1993-01-01

The basic features of the ground structure method for truss structure an continuum problems are described. Problems with a large number of potential structural elements are considered using the compliance of the structure as the objective function. The design problem is the minimization of compliance for a given structural weight, and the design variables for truss problems are the cross-sectional areas of the individual truss members, while for continuum problems they are the variable densities of material in each of the elements of the FEM discretization. It is shown how homogenization theory can be applied to provide a relation between material density and the effective material properties of a periodic medium with a known microstructure of material and voids.

A discrete search algorithm for finding the structure of protein backbones and side chains.

PubMed

Sallaume, Silas; Martins, Simone de Lima; Ochi, Luiz Satoru; Da Silva, Warley Gramacho; Lavor, Carlile; Liberti, Leo

2013-01-01

Some information about protein structure can be obtained by using Nuclear Magnetic Resonance (NMR) techniques, but they provide only a sparse set of distances between atoms in a protein. The Molecular Distance Geometry Problem (MDGP) consists in determining the three-dimensional structure of a molecule using a set of known distances between some atoms. Recently, a Branch and Prune (BP) algorithm was proposed to calculate the backbone of a protein, based on a discrete formulation for the MDGP. We present an extension of the BP algorithm that can calculate not only the protein backbone, but the whole three-dimensional structure of proteins.

Theoretical model for the discrete flexoelectric effect and a description for the sequence of intermediate smectic phases with increasing periodicity.

PubMed

Emelyanenko, A V; Osipov, M A

2003-11-01

A general phenomenological description and a simple molecular model is proposed for the "discrete" flexoelectric effect in tilted smectic liquid crystal phases. This effect defines a polarization in a smectic layer induced by a difference of director orientations in the two smectic layers adjacent to it. It is shown that the "discrete" flexoelectric effect is determined by electrostatic dipole-quadrupole interaction between positionally correlated molecules located in adjacent smectic layers, while the corresponding dipole-dipole interaction is responsible for a coupling between polarization vectors in neighboring layers. It is shown that a simple phenomenological model of a ferrielectric smectic liquid crystal, which has recently been proposed in the literature, can be used to describe the whole sequence of intermediate chiral smectic C* phases with increasing periods, and to determine the nonplanar structure of each phase without additional assumptions. In this sequence the phases with three- and four-layer periodicities have the same structure, as observed in the experiment. The theory predicts also the structure of intermediate phases with longer periods that have not been studied experimentally so far. The structures of intermediate phases with periodicities of up to nine layers are presented together with the phase diagrams, and a relationship between molecular chirality and the three-dimensional structure of intermediate phases is discussed. It is considered also how the coupling between the spontaneous polarization determined by molecular chirality and the induced polarization determined by the discrete flexoelectric effect stabilizes the nonplanar structure of intermediate phases.

Variational discretization of the nonequilibrium thermodynamics of simple systems

NASA Astrophysics Data System (ADS)

Gay-Balmaz, François; Yoshimura, Hiroaki

2018-04-01

In this paper, we develop variational integrators for the nonequilibrium thermodynamics of simple closed systems. These integrators are obtained by a discretization of the Lagrangian variational formulation of nonequilibrium thermodynamics developed in (Gay-Balmaz and Yoshimura 2017a J. Geom. Phys. part I 111 169–93 Gay-Balmaz and Yoshimura 2017b J. Geom. Phys. part II 111 194–212) and thus extend the variational integrators of Lagrangian mechanics, to include irreversible processes. In the continuous setting, we derive the structure preserving property of the flow of such systems. This property is an extension of the symplectic property of the flow of the Euler–Lagrange equations. In the discrete setting, we show that the discrete flow solution of our numerical scheme verifies a discrete version of this property. We also present the regularity conditions which ensure the existence of the discrete flow. We finally illustrate our discrete variational schemes with the implementation of an example of a simple and closed system.

A pediatric brain structure atlas from T1-weighted MR images

NASA Astrophysics Data System (ADS)

Shan, Zuyao Y.; Parra, Carlos; Ji, Qing; Ogg, Robert J.; Zhang, Yong; Laningham, Fred H.; Reddick, Wilburn E.

2006-03-01

In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. We constructed a 3D triangular mesh model for each structure by triangulation of the structure's reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/BrainAtlas) can be used to plan treatment, to conduct knowledge and modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.

Generation Algorithm of Discrete Line in Multi-Dimensional Grids

NASA Astrophysics Data System (ADS)

Du, L.; Ben, J.; Li, Y.; Wang, R.

2017-09-01

Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.

A receptor autoradiographic and in situ hybridization analysis of the distribution of the 5-ht7 receptor in rat brain.

PubMed Central

Gustafson, E. L.; Durkin, M. M.; Bard, J. A.; Zgombick, J.; Branchek, T. A.

1996-01-01

1. Receptor autoradiography and in situ hybridization histochemistry have been used to delineate the distribution of the 5-ht7 receptor and its mRNA in rat brain. Receptor autoradiographic studies were performed using [3H]-5-carboxamidotryptamine (5-CT) as the radioligand. The binding characteristics of the masking compounds were determined in Cos-7 cells transfected with a panel of 5-HT receptor subtype cDNAs, including the rat 5-ht7 cDNA. In situ hybridization studies were carried out with 35S-labelled oligonucleotide probes to the rat 5-ht7 mRNA. 2. Specific binding of [3H]-5-CT was observed in many areas of the rat brain. Following co-incubation with 1 microM ergotamine, this binding was completely eliminated. After addition of the masking ligands, [3H]-5-CT binding remained in layers 1-3 of cortex, septum, globus pallidus, thalamus, hypothalamus, centromedial amygdala, substantia nigra, periaquaductal gray, and superior colliculus. Addition of the antagonist, methiothepin, to the incubation regimen eliminated most of the remaining [3H]-5-CT binding in the brain, with the exception of the globus pallidus and substantia nigra. 3. The 5-ht7 mRNA was discretely localized in rat brain. The most intense hybridization signals were observed over the thalamus, the anterior hippocampal rudiment, and over the CA3 region of the hippocampus. Other regions containing hybridization signals included the septum, the hypothalamus, the centromedial amygdala and the periaquaductal gray. The regions exhibiting a modest receptor binding signal after methiothepin incubation, the globus pallidus and the substantia nigra, contained no 5-ht7 hybridization signals, suggesting a non-5-ht7 subtype in these two related structures. 4. The distribution of the 5-ht7 receptor and its mRNA is suggestive of multiple roles for this novel 5-HT receptor, within several brain systems. The limbic system (centromedial amygdala, anterior hippocampal rudiment, hypothalamus) is particularly well-represented, indicating a potential role for the 5-ht7 receptor in affective processes. Images Figure 2 Figure 3 Figure 4 PMID:8646411

High frequency oscillations are associated with cognitive processing in human recognition memory.

PubMed

Kucewicz, Michal T; Cimbalnik, Jan; Matsumoto, Joseph Y; Brinkmann, Benjamin H; Bower, Mark R; Vasoli, Vincent; Sulc, Vlastimil; Meyer, Fred; Marsh, W R; Stead, S M; Worrell, Gregory A

2014-08-01

High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations extend beyond the gamma frequency range, but their function in human cognitive processing has not been fully elucidated. Here we investigate high frequency oscillations spanning the high gamma (50-125 Hz), ripple (125-250 Hz) and fast ripple (250-500 Hz) frequency bands using intracranial recordings from 12 patients (five males and seven females, age 21-63 years) during memory encoding and recall of a series of affectively charged images. Presentation of the images induced high frequency oscillations in all three studied bands within the primary visual, limbic and higher order cortical regions in a sequence consistent with the visual processing stream. These induced oscillations were detected on individual electrodes localized in the amygdala, hippocampus and specific neocortical areas, revealing discrete oscillations of characteristic frequency, duration and latency from image presentation. Memory encoding and recall significantly modulated the number of induced high gamma, ripple and fast ripple detections in the studied structures, which was greater in the primary sensory areas during the encoding (Wilcoxon rank sum test, P = 0.002) and in the higher-order cortical association areas during the recall (Wilcoxon rank sum test, P = 0.001) of memorized images. Furthermore, the induced high gamma, ripple and fast ripple responses discriminated the encoded and the affectively charged images. In summary, our results show that high frequency oscillations, spanning a wide range of frequencies, are associated with memory processing and generated along distributed cortical and limbic brain regions. These findings support an important role for fast network synchronization in human cognition and extend our understanding of normal physiological brain activity during memory processing. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Rewarding and Locomotor-Sensitizing Effects of Repeated Cocaine Administration are Distinct and Separable in Mice

PubMed Central

Riday, Thorfinn T.; Kosofsky, Barry E.; Malanga, C.J.

2011-01-01

Repeated psychostimulant exposure progressively increases their potency to stimulate motor activity in rodents. This behavioral or locomotor sensitization is considered a model for some aspects of drug addiction in humans, particularly drug craving during abstinence. However, the role of increased motor behavior in drug reward remains incompletely understood. Intracranial self-stimulation (ICSS) was measured concurrently with locomotor activity to determine if acute intermittent cocaine administration had distinguishable effects on motor behavior and perception of brain stimulation-reward (BSR) in the same mice. Sensitization is associated with changes in neuronal activity and glutamatergic neurotransmission in brain reward circuitry. Expression of AMPA receptor subunits (GluR1 and GluR2) and CRE binding protein (CREB) was measured in the ventral tegmental area (VTA), dorsolateral striatum (STR) and nucleus accumbens (NAc) before and after a sensitizing regimen of cocaine, with and without ICSS. Repeated cocaine administration sensitized mice to its locomotor stimulating effects but not its ability to potentiate BSR. ICSS increased GluR1 in the VTA but not NAc or STR, demonstrating selective changes in protein expression with electrical stimulation of discrete brain structures. Repeated cocaine reduced GluR1, GluR2 and CREB expression in the NAc, and reductions of GluR1 and GluR2 but not CREB were further enhanced by ICSS. These data suggest that the effects of repeated cocaine exposure on reward and motor processes are dissociable in mice, and that reduction of excitatory neurotransmission in the NAc may predict altered motor function independently from changes in reward perception. PMID:22197517

Understanding How the Subcommissural Organ and Other Periventricular Secretory Structures Contribute via the Cerebrospinal Fluid to Neurogenesis

PubMed Central

Guerra, Maria M.; González, César; Caprile, Teresa; Jara, Maryoris; Vío, Karin; Muñoz, Rosa I.; Rodríguez, Sara; Rodríguez, Esteban M.

2015-01-01

The dynamic and molecular composition of the cerebrospinal fluid (CSF) and, consequently, the CSF physiology is much more complex and fascinating than the simplistic view held for decades. Signal molecules either transported from blood to CSF or secreted into the CSF by circumventricular organs and CSF-contacting neurons, use the CSF to reach their targets in the brain, including the pre- and postnatal neurogenic niche. The subcommissural organ (SCO), a highly conserved brain gland present throughout the vertebrate phylum, is one of the sources for signals, as well as the choroid plexus, tanycytes and CSF-contacting neurons. The SCO secretes into the fetal and adult CSF SCO-spondin, transthyretin, and basic fibroblast growth factor. These proteins participate in certain aspects of neurogenesis, such as cell cycle of neural stem cells, neuronal differentiation, and axon pathfinding. Through the CSF, the SCO-secretory proteins may reach virtually any target in the embryonic and adult central nervous system. Since the SCO continues to secrete throughout life span, it seems likely that the neurogenetic property of the SCO compounds would be targeted to the niches where neurogenesis continues in adulthood. This review is aimed to bring into discussion early and new evidence concerning the role(s) of the SCO, and the probable mechanisms by which SCO compounds can readily reach the neurogenic niche of the subventricular zone flowing with the CSF to participate in the regulation of the neurogenic niche. As we unfold the multiples trans-fluid talks between discrete brain domains we will have more tools to influence such talks. PMID:26778959

Chronic cannabis users show altered neurophysiological functioning on Stroop task conflict resolution.

PubMed

Battisti, Robert A; Roodenrys, Steven; Johnstone, Stuart J; Pesa, Nicole; Hermens, Daniel F; Solowij, Nadia

2010-12-01

Chronic cannabis use has been related to deficits in cognition (particularly memory) and the normal functioning of brain structures sensitive to cannabinoids. There is increasing evidence that conflict monitoring and resolution processes (i.e. the ability to detect and respond to change) may be affected. This study examined the ability to inhibit an automatic reading response in order to activate a more difficult naming response (i.e. conflict resolution) in a variant of the discrete trial Stroop colour-naming task. Event-related brain potentials to neutral, congruent and incongruent trials were compared between 21 cannabis users (mean 16.4 years of near daily use) in the unintoxicated state and 19 non-using controls. Cannabis users showed increased errors on colour-incongruent trials (e.g. "RED" printed in blue ink) but no performance differences from controls on colour congruent (e.g. "RED" printed in red ink) or neutral trials (e.g. "*****" printed in green ink). Poorer incongruent trial performance was predicted by an earlier age of onset of regular cannabis use. Users showed altered expression of a late sustained potential related to conflict resolution, evident by opposite patterns of activity between trial types at midline and central sites, and altered relationships between neurophysiological and behavioural outcome measures not evident in the control group. These findings indicate that chronic use of cannabis may impair the brain's ability to respond optimally in the presence of events that require conflict resolution and hold implications for the ability to refrain from substance misuse and/or maintain substance abstention behaviours.

Iron Accumulates in Huntington’s Disease Neurons: Protection by Deferoxamine

PubMed Central

Chen, Jianfang; Lai, Barry; Zhang, Zhaojie; Duce, James A.; Lam, Linh Q.; Volitakis, Irene; Bush, Ashley I.; Hersch, Steven

2013-01-01

Huntington’s disease (HD) is a progressive neurodegenerative disorder caused by a polyglutamine-encoding CAG expansion in the huntingtin gene. Iron accumulates in the brains of HD patients and mouse disease models. However, the cellular and subcellular sites of iron accumulation, as well as significance to disease progression are not well understood. We used independent approaches to investigate the location of brain iron accumulation. In R6/2 HD mouse brain, synchotron x-ray fluorescence analysis revealed iron accumulation as discrete puncta in the perinuclear cytoplasm of striatal neurons. Further, perfusion Turnbull’s staining for ferrous iron (II) combined with transmission electron microscope ultra-structural analysis revealed increased staining in membrane bound peri-nuclear vesicles in R6/2 HD striatal neurons. Analysis of iron homeostatic proteins in R6/2 HD mice revealed decreased levels of the iron response proteins (IRPs 1 and 2) and accordingly decreased expression of iron uptake transferrin receptor (TfR) and increased levels of neuronal iron export protein ferroportin (FPN). Finally, we show that intra-ventricular delivery of the iron chelator deferoxamine results in an improvement of the motor phenotype in R6/2 HD mice. Our data supports accumulation of redox-active ferrous iron in the endocytic / lysosomal compartment in mouse HD neurons. Expression changes of IRPs, TfR and FPN are consistent with a compensatory response to an increased intra-neuronal labile iron pool leading to increased susceptibility to iron-associated oxidative stress. These findings, together with protection by deferoxamine, support a potentiating role of neuronal iron accumulation in HD. PMID:24146952

Tracking the Fear Memory Engram: Discrete Populations of Neurons within Amygdala, Hypothalamus, and Lateral Septum Are Specifically Activated by Auditory Fear Conditioning

ERIC Educational Resources Information Center

Butler, Christopher W.; Wilson, Yvette M.; Gunnersen, Jenny M.; Murphy, Mark

2015-01-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used "fos-tau-lacZ" ("FTL") transgenic mice to identify…

Identifying Degenerative Brain Disease Using Rough Set Classifier Based on Wavelet Packet Method.

PubMed

Cheng, Ching-Hsue; Liu, Wei-Xiang

2018-05-28

Population aging has become a worldwide phenomenon, which causes many serious problems. The medical issues related to degenerative brain disease have gradually become a concern. Magnetic Resonance Imaging is one of the most advanced methods for medical imaging and is especially suitable for brain scans. From the literature, although the automatic segmentation method is less laborious and time-consuming, it is restricted in several specific types of images. In addition, hybrid techniques segmentation improves the shortcomings of the single segmentation method. Therefore, this study proposed a hybrid segmentation combined with rough set classifier and wavelet packet method to identify degenerative brain disease. The proposed method is a three-stage image process method to enhance accuracy of brain disease classification. In the first stage, this study used the proposed hybrid segmentation algorithms to segment the brain ROI (region of interest). In the second stage, wavelet packet was used to conduct the image decomposition and calculate the feature values. In the final stage, the rough set classifier was utilized to identify the degenerative brain disease. In verification and comparison, two experiments were employed to verify the effectiveness of the proposed method and compare with the TV-seg (total variation segmentation) algorithm, Discrete Cosine Transform, and the listing classifiers. Overall, the results indicated that the proposed method outperforms the listing methods.

Geometric Structure-Preserving Discretization Schemes for Nonlinear Elasticity

DTIC Science & Technology

2015-08-13

conditions. 15.  SUBJECT TERMS geometric theory for nonlinear elasticity, discrete exterior calculus 16.  SECURITY CLASSIFICATION OF: 17.  LIMITATION...associated Laplacian. We use the general theory for approximation of Hilbert complexes and the finite element exterior calculus and introduce some stable mixed

Discrete-time stability of continuous-time controller designs for large space structures

NASA Technical Reports Server (NTRS)

Balas, M. J.

1982-01-01

In most of the stable control designs for flexible structures, continuous time is assumed. However, in view of the implementation of the controllers by on-line digital computers, the discrete-time stability of such controllers is an important consideration. In the case of direct-velocity feedback (DVFB), involving negative feedback from collocated force actuators and velocity sensors, it is not immediately apparent how much delay due to digital implementation of DVFB can be tolerated without loss of stability. The present investigation is concerned with such questions. A study is conducted of the discrete-time stability of DVFB, taking into account an employment of Euler's method of approximation of the time derivative. The obtained result gives an indication of the acceptable time-step size for stable digital implementation of DVFB. A result derived in connection with the consideration of the discrete-time stability of stable continuous-time systems provides a general condition under which digital implementation of such a system will remain stable.

Time-domain damping models in structural acoustics using digital filtering

NASA Astrophysics Data System (ADS)

Parret-Fréaud, Augustin; Cotté, Benjamin; Chaigne, Antoine

2016-02-01

This paper describes a new approach in order to formulate well-posed time-domain damping models able to represent various frequency domain profiles of damping properties. The novelty of this approach is to represent the behavior law of a given material directly in a discrete-time framework as a digital filter, which is synthesized for each material from a discrete set of frequency-domain data such as complex modulus through an optimization process. A key point is the addition of specific constraints to this process in order to guarantee stability, causality and verification of thermodynamics second law when transposing the resulting discrete-time behavior law into the time domain. Thus, this method offers a framework which is particularly suitable for time-domain simulations in structural dynamics and acoustics for a wide range of materials (polymers, wood, foam, etc.), allowing to control and even reduce the distortion effects induced by time-discretization schemes on the frequency response of continuous-time behavior laws.

Plane stress problems using hysteretic rigid body spring network models

NASA Astrophysics Data System (ADS)

Christos, Sofianos D.; Vlasis, Koumousis K.

2017-10-01

In this work, a discrete numerical scheme is presented capable of modeling the hysteretic behavior of 2D structures. Rigid Body Spring Network (RBSN) models that were first proposed by Kawai (Nucl Eng Des 48(1):29-207, 1978) are extended to account for hysteretic elastoplastic behavior. Discretization is based on Voronoi tessellation, as proposed specifically for RBSN models to ensure uniformity. As a result, the structure is discretized into convex polygons that form the discrete rigid bodies of the model. These are connected with three zero length, i.e., single-node springs in the middle of their common facets. The springs follow the smooth hysteretic Bouc-Wen model which efficiently incorporates classical plasticity with no direct reference to a yield surface. Numerical results for both static and dynamic loadings are presented, which validate the proposed simplified spring-mass formulation. In addition, they verify the model's applicability on determining primarily the displacement field and plastic zones compared to the standard elastoplastic finite element method.

Modelling Dowel Action of Discrete Reinforcing Bars in Cracked Concrete Structures

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

Kwan, A. K. H.; Ng, P. L.; Lam, J. Y. K.

2010-05-21

Dowel action is one of the component actions for shear force transfer in cracked reinforced concrete. In finite element analysis of concrete structures, the use of discrete representation of reinforcing bars is considered advantageous over the smeared representation due to the relative ease of modelling the bond-slip behaviour. However, there is very limited research on how to simulate the dowel action of discrete reinforcing bars. Herein, a numerical model for dowel action of discrete reinforcing bars crossing cracks in concrete is developed. The model features the derivation of dowel stiffness matrix based on beam-on-elastic-foundation theory and the direct assemblage ofmore » dowel stiffness into the concrete element stiffness matrices. The dowel action model is incorporated in a nonlinear finite element programme with secant stiffness formulation. Deep beams tested in the literature are analysed and it is found that the incorporation of dowel action model improves the accuracy of analysis.« less

Symplectic discretization for spectral element solution of Maxwell's equations

NASA Astrophysics Data System (ADS)

Zhao, Yanmin; Dai, Guidong; Tang, Yifa; Liu, Qinghuo

2009-08-01

Applying the spectral element method (SEM) based on the Gauss-Lobatto-Legendre (GLL) polynomial to discretize Maxwell's equations, we obtain a Poisson system or a Poisson system with at most a perturbation. For the system, we prove that any symplectic partitioned Runge-Kutta (PRK) method preserves the Poisson structure and its implied symplectic structure. Numerical examples show the high accuracy of SEM and the benefit of conserving energy due to the use of symplectic methods.

Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter.

PubMed

Bonny, Jean Marie; Boespflug-Tanguly, Odile; Zanca, Michel; Renou, Jean Pierre

2003-03-01

A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.

GDNF family receptor α-1 in the catfish: Possible implication to brain dopaminergic activity.

PubMed

Mamta, Sajwan-Khatri; Senthilkumaran, Balasubramanian

2018-05-31

Glial cell line-derived neurotrophic factor (GDNF)is a potent trophic factor that preferentially binds to GDNF family receptor α-1 (GFRα-1)by regulating dopaminergic (DA-ergic) neuronsin brain. Present study aimed to evaluate the significance of GFRα-1 expression during early brain development in catfish. Initially, the full-length cDNA of GFRα-1 was cloned from adult brain which showed high homology with other vertebrate counterparts. Quantitative PCR analysis of tissue distribution revealed ubiquitous expression of GFRα-1 in the tissues analyzed with high levels in female brain and ovary. Significant high expression was evident in brain at 75 and 100 days post hatch females than the respective age-match males. Expression of GFRα-1 was high in brain during the spawning phase when compared to other reproductive phases. Localization of GFRα-1 revealed its presence in preoptic area-hypothalamus which correlated well with the expression profile in discrete areas of brain in adult catfish. Transient silencing of GFRα-1through siRNA lowered expression levels of GFRα-1, which further down regulated the expression of certain brain-specific genes. Expression of GFRα-1 in brain declined significantly upon treatment with the 1-methyl-1,2,3,6-tetrahydropyridinecausing neurodegeneration which further correlated with catecholamines (CA), L-3,4-dihydroxyphenylalanine, DA and norepinephrine levels. Taken together, GFRα-1 plausibly entrains gonadotropin-releasing hormone and gonadotropin axiseither directly or indirectly, at least by partially targeting CA-ergic activity. Copyright © 2018 Elsevier Inc. All rights reserved.

Concurrent Tumor Segmentation and Registration with Uncertainty-based Sparse non-Uniform Graphs

PubMed Central

Parisot, Sarah; Wells, William; Chemouny, Stéphane; Duffau, Hugues; Paragios, Nikos

2014-01-01

In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model. PMID:24717540

Discrete integration of continuous Kalman filtering equations for time invariant second-order structural systems

NASA Technical Reports Server (NTRS)

Park, K. C.; Belvin, W. Keith

1990-01-01

A general form for the first-order representation of the continuous second-order linear structural-dynamics equations is introduced to derive a corresponding form of first-order continuous Kalman filtering equations. Time integration of the resulting equations is carried out via a set of linear multistep integration formulas. It is shown that a judicious combined selection of computational paths and the undetermined matrices introduced in the general form of the first-order linear structural systems leads to a class of second-order discrete Kalman filtering equations involving only symmetric sparse N x N solution matrices.

Second-order discrete Kalman filtering equations for control-structure interaction simulations

NASA Technical Reports Server (NTRS)

Park, K. C.; Belvin, W. Keith; Alvin, Kenneth F.

1991-01-01

A general form for the first-order representation of the continuous, second-order linear structural dynamics equations is introduced in order to derive a corresponding form of first-order Kalman filtering equations (KFE). Time integration of the resulting first-order KFE is carried out via a set of linear multistep integration formulas. It is shown that a judicious combined selection of computational paths and the undetermined matrices introduced in the general form of the first-order linear structural systems leads to a class of second-order discrete KFE involving only symmetric, N x N solution matrix.

A mathematical model of the structure and evolution of small-scale discrete auroral arcs

NASA Technical Reports Server (NTRS)

Seyler, Charles E.

1990-01-01

A three-dimensional fluid model for the structure and evolution of small-scale discrete auroral arcs originating from Alfven waves is developed and used to study the nonlinear macroscopic plasma dynamics of these auroral arcs. The results of simulations show that stationary auroral arcs can be unstable to a collisionless tearing mode which may be responsible for the observed transverse structuring in the form of folds and curls. At late times, the plasma becomes turbulent having transverse electric field power spectra that tend toward a universal k exp -5/3 spectral form.

Energy transfer, orbital angular momentum, and discrete current in a double-ring fiber array

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

Alexeyev, C. N.; Volyar, A. V.; Yavorsky, M. A.

We study energy transfer and orbital angular momentum of supermodes in a double-ring array of evanescently coupled monomode optical fibers. The structure of supermodes and the spectra of their propagation constants are obtained. The geometrical parameters of the array, at which the energy is mostly confined within the layers, are determined. The developed method for finding the supermodes of concentric arrays is generalized for the case of multiring arrays. The orbital angular momentum carried by a supermode of a double-ring array is calculated. The discrete lattice current is introduced. It is shown that the sum of discrete currents over themore » array is a conserved quantity. The connection of the total discrete current with orbital angular momentum of discrete optical vortices is made.« less

Multi-functional composite structures

DOEpatents

Mulligan, Anthony C.; Halloran, John; Popovich, Dragan; Rigali, Mark J.; Sutaria, Manish P.; Vaidyanathan, K. Ranji; Fulcher, Michael L.; Knittel, Kenneth L.

2004-10-19

Fibrous monolith processing techniques to fabricate multifunctional structures capable of performing more than one discrete function such as structures capable of bearing structural loads and mechanical stresses in service and also capable of performing at least one additional non-structural function.

Multi-functional composite structures

DOEpatents

Mulligan, Anthony C.; Halloran, John; Popovich, Dragan; Rigali, Mark J.; Sutaria, Manish P.; Vaidyanathan, K. Ranji; Fulcher, Michael L.; Knittel, Kenneth L.

2010-04-27

Fibrous monolith processing techniques to fabricate multifunctional structures capable of performing more than one discrete function such as structures capable of bearing structural loads and mechanical stresses in service and also capable of performing at least one additional non-structural function.

Mathematics and Computer Science: Exploring a Symbiotic Relationship

ERIC Educational Resources Information Center

Bravaco, Ralph; Simonson, Shai

2004-01-01

This paper describes a "learning community" designed for sophomore computer science majors who are simultaneously studying discrete mathematics. The learning community consists of three courses: Discrete Mathematics, Data Structures and an Integrative Seminar/Lab. The seminar functions as a link that integrates the two disciplines. Participation…

Analysis of reinforced concrete structures with occurrence of discrete cracks at arbitrary positions

NASA Technical Reports Server (NTRS)

Blaauwendraad, J.; Grootenboer, H. J.; Bouma, A. L.; Reinhardt, H. W.

1980-01-01

A nonlinear analysis of in-plane loaded plates is presented, which eliminates the disadvantages of the smeared crack approach. The elements used and the computational method are discussed. An example is shown in which one or more discrete cracks are dominant.

Neocortical neurogenesis in humans is restricted to development

PubMed Central

Bhardwaj, Ratan D.; Curtis, Maurice A.; Spalding, Kirsty L.; Buchholz, Bruce A.; Fink, David; Björk-Eriksson, Thomas; Nordborg, Claes; Gage, Fred H.; Druid, Henrik; Eriksson, Peter S.; Frisén, Jonas

2006-01-01

Stem cells generate neurons in discrete regions in the postnatal mammalian brain. However, the extent of neurogenesis in the adult human brain has been difficult to establish. We have taken advantage of the integration of 14C, generated by nuclear bomb tests during the Cold War, in DNA to establish the age of neurons in the major areas of the human cerebral neocortex. Together with the analysis of the neocortex from patients who received BrdU, which integrates in the DNA of dividing cells, our results demonstrate that, whereas nonneuronal cells turn over, neurons in the human cerebral neocortex are not generated in adulthood at detectable levels but are generated perinatally. PMID:16901981

Sex Differences in Serotonin 1 Receptor Binding in Rat Brain

NASA Astrophysics Data System (ADS)

Fischette, Christine T.; Biegon, Anat; McEwen, Bruce S.

1983-10-01

Male and female rats exhibit sex differences in binding by serotonin 1 receptors in discrete areas of the brain, some of which have been implicated in the control of ovulation and of gonadotropin release. The sex-specific changes in binding, which occur in response to the same hormonal (estrogenic) stimulus, are due to changes in the number of binding sites. Castration alone also affects the number of binding sites in certain areas. The results lead to the conclusion that peripheral hormones modulate binding by serotonin 1 receptors. The status of the serotonin receptor system may affect the reproductive capacity of an organism and may be related to sex-linked emotional disturbances in humans.

Hybrid ICA-Bayesian Network approach reveals distinct effective connectivity differences in schizophrenia

PubMed Central

Kim, D.; Burge, J.; Lane, T.; Pearlson, G. D; Kiehl, K. A; Calhoun, V. D.

2008-01-01

We utilized a discrete dynamic Bayesian network (dDBN) approach (Burge et al., 2007) to determine differences in brain regions between patients with schizophrenia and healthy controls on a measure of effective connectivity, termed the approximate conditional likelihood score (ACL) (Burge and Lane, 2005). The ACL score represents a class-discriminative measure of effective connectivity by measuring the relative likelihood of the correlation between brain regions in one group versus another. The algorithm is capable of finding non-linear relationships between brain regions because it uses discrete rather than continuous values and attempts to model temporal relationships with a first-order Markov and stationary assumption constraint (Papoulis, 1991). Since Bayesian networks are overly sensitive to noisy data, we introduced an independent component analysis (ICA) filtering approach that attempted to reduce the noise found in fMRI data by unmixing the raw datasets into a set of independent spatial component maps. Components that represented noise were removed and the remaining components reconstructed into the dimensions of the original fMRI datasets. We applied the dDBN algorithm to a group of 35 patients with schizophrenia and 35 matched healthy controls using an ICA filtered and unfiltered approach. We determined that filtering the data significantly improved the magnitude of the ACL score. Patients showed the greatest ACL scores in several regions, most markedly the cerebellar vermis and hemispheres. Our findings suggest that schizophrenia patients exhibit weaker connectivity than healthy controls in multiple regions, including bilateral temporal and frontal cortices, plus cerebellum during an auditory paradigm. PMID:18602482

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

PubMed

Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G

2017-03-01

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Neuroendocrine profiles associated with discrete behavioural variation in Symphodus ocellatus, a species with male alternative reproductive tactics.

PubMed

Nugent, B M; Stiver, K A; Alonzo, S H; Hofmann, H A

2016-10-01

The molecular mechanisms underlying phenotypic plasticity are not well understood. Identifying mechanisms underlying alternative reproductive tactics (ARTs) in species for which the behavioural and fitness consequences of this variation are well characterized provides an opportunity to integrate evolutionary and mechanistic understanding of the maintenance of variation within populations. In the ocellated wrasse Symphodus ocellatus, the behavioural phenotypes of three distinct male morphs (sneakers, satellites and nesting males), which arise from a single genome, have been thoroughly characterized. To determine the neuroendocrine and genomic mechanisms associated with discrete phenotypic variation and ARTs in S. ocellatus in their natural environment, we constructed a whole-brain de novo transcriptome and compared global patterns of gene expression between sexes and male morphs. Next, we quantified circulating cortisol and 11-ketotestosterone (11-kt), mediators of male reproductive behaviours, as well as stress and gonadal steroid hormone receptor expression in the preoptic area, ventral subpallial division of the telencephalon and dorsolateral telencephalon, critical brain regions for social and reproductive behaviours. We found higher levels of 11-kt in nesting males and higher levels of cortisol in sneaker males relative to other male morphs and females. We also identified distinct patterns of brain region-specific hormone receptor expression between males such that most hormone receptors are more highly expressed in satellites and nesting males relative to sneakers and females. Our results establish the neuroendocrine and molecular mechanisms that underlie ARTs in the wild and provide a foundation for experimentally testing hypotheses about the relationship between neuromolecular processes and reproductive success. © 2016 John Wiley & Sons Ltd.

Error Correcting Codes and Related Designs

DTIC Science & Technology

1990-09-30

Theory, IT-37 (1991), 1222-1224. 6. Codes and designs, existence and uniqueness, Discrete Math ., to appear. 7. (with R. Brualdi and N. Cai), Orphan...structure of the first order Reed-Muller codes, Discrete Math ., to appear. 8. (with J. H. Conway and N.J.A. Sloane), The binary self-dual codes of length up...18, 1988. 4. "Codes and Designs," Mathematics Colloquium, Technion, Haifa, Israel, March 6, 1989. 5. "On the Covering Radius of Codes," Discrete Math . Group

Casting Metal Nanowires Within Discrete Self-Assembled Peptide Nanotubes

NASA Astrophysics Data System (ADS)

Reches, Meital; Gazit, Ehud

2003-04-01

Tubular nanostructures are suggested to have a wide range of applications in nanotechnology. We report our observation of the self-assembly of a very short peptide, the Alzheimer's β-amyloid diphenylalanine structural motif, into discrete and stiff nanotubes. Reduction of ionic silver within the nanotubes, followed by enzymatic degradation of the peptide backbone, resulted in the production of discrete nanowires with a long persistence length. The same dipeptide building block, made of D-phenylalanine, resulted in the production of enzymatically stable nanotubes.

Necessary and sufficient conditions for discrete wavelet frames in CN

NASA Astrophysics Data System (ADS)

Deepshikha; Vashisht, Lalit K.

2017-07-01

We present necessary and sufficient conditions with explicit frame bounds for a discrete wavelet system of the form {DaTk ϕ } a ∈ U(N) , k ∈IN to be a frame for the unitary space CN. It is shown that the canonical dual of a discrete wavelet frame for CN has the same structure. This is not true (well known) for canonical dual of a wavelet frame for L2(R) . Several numerical examples are given to illustrate the results.

Modelling of high-frequency structure-borne sound transmission on FEM grids using the Discrete Flow Mapping technique

NASA Astrophysics Data System (ADS)

Hartmann, Timo; Tanner, Gregor; Xie, Gang; Chappell, David; Bajars, Janis

2016-09-01

Dynamical Energy Analysis (DEA) combined with the Discrete Flow Mapping technique (DFM) has recently been introduced as a mesh-based high frequency method modelling structure borne sound for complex built-up structures. This has proven to enhance vibro-acoustic simulations considerably by making it possible to work directly on existing finite element meshes circumventing time-consuming and costly re-modelling strategies. In addition, DFM provides detailed spatial information about the vibrational energy distribution within a complex structure in the mid-to-high frequency range. We will present here progress in the development of the DEA method towards handling complex FEM-meshes including Rigid Body Elements. In addition, structure borne transmission paths due to spot welds are considered. We will present applications for a car floor structure.

Translating birdsong: songbirds as a model for basic and applied medical research.

PubMed

Brainard, Michael S; Doupe, Allison J

2013-07-08

Songbirds, long of interest to basic neuroscience, have great potential as a model system for translational neuroscience. Songbirds learn their complex vocal behavior in a manner that exemplifies general processes of perceptual and motor skill learning and, more specifically, resembles human speech learning. Song is subserved by circuitry that is specialized for vocal learning and production but that has strong similarities to mammalian brain pathways. The combination of highly quantifiable behavior and discrete neural substrates facilitates understanding links between brain and behavior, both in normal states and in disease. Here we highlight (a) behavioral and mechanistic parallels between birdsong and aspects of speech and social communication, including insights into mirror neurons, the function of auditory feedback, and genes underlying social communication disorders, and (b) contributions of songbirds to understanding cortical-basal ganglia circuit function and dysfunction, including the possibility of harnessing adult neurogenesis for brain repair.

Translating Birdsong: Songbirds as a model for basic and applied medical research

PubMed Central

2014-01-01

Songbirds, long of interest to basic neuroscientists, have great potential as a model system for translational neuroscience. Songbirds learn their complex vocal behavior in a manner that exemplifies general processes of perceptual and motor skill learning, and more specifically resembles human speech learning. Song is subserved by circuitry that is specialized for vocal learning and production, but that has strong similarities to mammalian brain pathways. The combination of a highly quantifiable behavior and discrete neural substrates facilitates understanding links between brain and behavior, both normally and in disease. Here we highlight 1) behavioral and mechanistic parallels between birdsong and aspects of speech and social communication, including insights into mirror neurons, the function of auditory feedback, and genes underlying social communication disorders, and 2) contributions of songbirds to understanding cortical-basal ganglia circuit function and dysfunction, including the possibility of harnessing adult neurogenesis for brain repair. PMID:23750515

Neural evidence that human emotions share core affective properties.

PubMed

Wilson-Mendenhall, Christine D; Barrett, Lisa Feldman; Barsalou, Lawrence W

2013-06-01

Research on the "emotional brain" remains centered around the idea that emotions like fear, happiness, and sadness result from specialized and distinct neural circuitry. Accumulating behavioral and physiological evidence suggests, instead, that emotions are grounded in core affect--a person's fluctuating level of pleasant or unpleasant arousal. A neuroimaging study revealed that participants' subjective ratings of valence (i.e., pleasure/displeasure) and of arousal evoked by various fear, happiness, and sadness experiences correlated with neural activity in specific brain regions (orbitofrontal cortex and amygdala, respectively). We observed these correlations across diverse instances within each emotion category, as well as across instances from all three categories. Consistent with a psychological construction approach to emotion, the results suggest that neural circuitry realizes more basic processes across discrete emotions. The implicated brain regions regulate the body to deal with the world, producing the affective changes at the core of emotions and many other psychological phenomena.

FPGA implementation of motifs-based neuronal network and synchronization analysis

NASA Astrophysics Data System (ADS)

Deng, Bin; Zhu, Zechen; Yang, Shuangming; Wei, Xile; Wang, Jiang; Yu, Haitao

2016-06-01

Motifs in complex networks play a crucial role in determining the brain functions. In this paper, 13 kinds of motifs are implemented with Field Programmable Gate Array (FPGA) to investigate the relationships between the networks properties and motifs properties. We use discretization method and pipelined architecture to construct various motifs with Hindmarsh-Rose (HR) neuron as the node model. We also build a small-world network based on these motifs and conduct the synchronization analysis of motifs as well as the constructed network. We find that the synchronization properties of motif determine that of motif-based small-world network, which demonstrates effectiveness of our proposed hardware simulation platform. By imitation of some vital nuclei in the brain to generate normal discharges, our proposed FPGA-based artificial neuronal networks have the potential to replace the injured nuclei to complete the brain function in the treatment of Parkinson's disease and epilepsy.

Invariant measures in brain dynamics

NASA Astrophysics Data System (ADS)

Boyarsky, Abraham; Góra, Paweł

2006-10-01

This note concerns brain activity at the level of neural ensembles and uses ideas from ergodic dynamical systems to model and characterize chaotic patterns among these ensembles during conscious mental activity. Central to our model is the definition of a space of neural ensembles and the assumption of discrete time ensemble dynamics. We argue that continuous invariant measures draw the attention of deeper brain processes, engendering emergent properties such as consciousness. Invariant measures supported on a finite set of ensembles reflect periodic behavior, whereas the existence of continuous invariant measures reflect the dynamics of nonrepeating ensemble patterns that elicit the interest of deeper mental processes. We shall consider two different ways to achieve continuous invariant measures on the space of neural ensembles: (1) via quantum jitters, and (2) via sensory input accompanied by inner thought processes which engender a “folding” property on the space of ensembles.

Characterization of the Distance Relationship Between Localized Serotonin Receptors and Glia Cells on Fluorescence Microscopy Images of Brain Tissue.

PubMed

Jacak, Jaroslaw; Schaller, Susanne; Borgmann, Daniela; Winkler, Stephan M

2015-08-01

We here present two new methods for the characterization of fluorescent localization microscopy images obtained from immunostained brain tissue sections. Direct stochastic optical reconstruction microscopy images of 5-HT1A serotonin receptors and glial fibrillary acidic proteins in healthy cryopreserved brain tissues are analyzed. In detail, we here present two image processing methods for characterizing differences in receptor distribution on glial cells and their distribution on neural cells: One variant relies on skeleton extraction and adaptive thresholding, the other on k-means based discrete layer segmentation. Experimental results show that both methods can be applied for distinguishing classes of images with respect to serotonin receptor distribution. Quantification of nanoscopic changes in relative protein expression on particular cell types can be used to analyze degeneration in tissues caused by diseases or medical treatment.

Genetic-evolution-based optimization methods for engineering design

NASA Technical Reports Server (NTRS)

Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

1990-01-01

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

Peridynamics with LAMMPS : a user guide.

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

Lehoucq, Richard B.; Silling, Stewart Andrew; Seleson, Pablo

Peridynamics is a nonlocal extension of classical continuum mechanics. The discrete peridynamic model has the same computational structure as a molecular dynamics model. This document provides a brief overview of the peridynamic model of a continuum, then discusses how the peridynamic model is discretized within LAMMPS. An example problem is also included.

Manipulative and Numerical Spreadsheet Templates for the Study of Discrete Structures.

ERIC Educational Resources Information Center

Abramovich, Sergei

1998-01-01

Argues that basic components of discrete mathematics can be introduced to students through gradual elaboration of experiences with iconic spreadsheet-based simulations of concrete materials. Suggests that the study of homogeneous and heterogeneous patterns of manipulative spreadsheet templates allows for appreciation of the development of…

Structural Equations and Path Analysis for Discrete Data.

ERIC Educational Resources Information Center

Winship, Christopher; Mare, Robert D.

1983-01-01

Presented is an approach to causal models in which some or all variables are discretely measured, showing that path analytic methods permit quantification of causal relationships among variables with the same flexibility and power of interpretation as is feasible in models including only continuous variables. Examples are provided. (Author/IS)

Discrete elliptic solitons in two-dimensional waveguide arrays

NASA Astrophysics Data System (ADS)

Ye, Fangwei; Dong, Liangwei; Wang, Jiandong; Cai, Tian; Li, Yong-Ping

2005-04-01

The fundamental properties of discrete elliptic solitons (DESs) in the two-dimensional waveguide arrays were studied. The DESs show nontrivial spatial structures in their parameters space due to the introduction of the new freedom of ellipticity, and their stability is closely linked to their propagation directions in the transverse plane.

Atomically informed nonlocal semi-discrete variational Peierls-Nabarro model for planar core dislocations

PubMed Central

Liu, Guisen; Cheng, Xi; Wang, Jian; Chen, Kaiguo; Shen, Yao

2017-01-01

Prediction of Peierls stress associated with dislocation glide is of fundamental concern in understanding and designing the plasticity and mechanical properties of crystalline materials. Here, we develop a nonlocal semi-discrete variational Peierls-Nabarro (SVPN) model by incorporating the nonlocal atomic interactions into the semi-discrete variational Peierls framework. The nonlocal kernel is simplified by limiting the nonlocal atomic interaction in the nearest neighbor region, and the nonlocal coefficient is directly computed from the dislocation core structure. Our model is capable of accurately predicting the displacement profile, and the Peierls stress, of planar-extended core dislocations in face-centered cubic structures. Our model could be extended to study more complicated planar-extended core dislocations, such as <110> {111} dislocations in Al-based and Ti-based intermetallic compounds. PMID:28252102

Nonlinear wave propagation in discrete and continuous systems

NASA Astrophysics Data System (ADS)

Rothos, V. M.

2016-09-01

In this review we try to capture some of the recent excitement induced by a large volume of theoretical and computational studies addressing nonlinear Schrödinger models (discrete and continuous) and the localized structures that they support. We focus on some prototypical structures, namely the breather solutions and solitary waves. In particular, we investigate the bifurcation of travelling wave solution in Discrete NLS system applying dynamical systems methods. Next, we examine the combined effects of cubic and quintic terms of the long range type in the dynamics of a double well potential. The relevant bifurcations, the stability of the branches and their dynamical implications are examined both in the reduced (ODE) and in the full (PDE) setting. We also offer an outlook on interesting possibilities for future work on this theme.

Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change.

PubMed

Williams, Owen A; Zeestraten, Eva A; Benjamin, Philip; Lambert, Christian; Lawrence, Andrew J; Mackinnon, Andrew D; Morris, Robin G; Markus, Hugh S; Charlton, Rebecca A; Barrick, Thomas R

2017-01-01

Cerebral small vessel disease (SVD) is the primary cause of vascular cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related changes in a single unitary score across the whole cerebrum, to investigate its relationship with cognitive change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to change in EF and IPS ( p  < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of change in EF and IPS in the multivariate models ( p  = 0.002). Change in DSEG θ was also related to change in all other MRI markers ( p  < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain change in SVD that has a negative impact on cognition and remains a significant predictor of cognitive change when other MRI markers of brain change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural changes and successfully predicts cognitive change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs).

Developmental metaplasticity in neural circuit codes of firing and structure.

PubMed

Baram, Yoram

2017-01-01

Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plasticity, we suggest that the external expression of plasticity by changes in the firing-rate dynamics represents a more general notion of plasticity. Hypothesizing that time constants of plasticity and firing dynamics increase with age, and employing the filtering property of the neuron, we obtain the elementary code of global attractors associated with the firing-rate dynamics in each developmental stage. We define a neural circuit connectivity code as an indivisible set of circuit structures generated by membrane and synapse activation and silencing. Synchronous firing patterns under parameter uniformity, and asynchronous circuit firing are shown to be driven, respectively, by membrane and synapse silencing and reactivation, and maintained by the neuronal filtering property. Analytic, graphical and simulation representation of the discrete iteration maps and of the global attractor codes of neural firing rate are found to be consistent with previous empirical neurobiological findings, which have lacked, however, a specific correspondence between firing modes, time constants, circuit connectivity and cortical developmental stages. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effects of musical training on structural brain development: a longitudinal study.

PubMed

Hyde, Krista L; Lerch, Jason; Norton, Andrea; Forgeard, Marie; Winner, Ellen; Evans, Alan C; Schlaug, Gottfried

2009-07-01

Long-term instrumental music training is an intense, multisensory and motor experience that offers an ideal opportunity to study structural brain plasticity in the developing brain in correlation with behavioral changes induced by training. Here, for the first time, we demonstrate structural brain changes after only 15 months of musical training in early childhood, which were correlated with improvements in musically relevant motor and auditory skills. These findings shed light on brain plasticity, and suggest that structural brain differences in adult experts (whether musicians or experts in other areas) are likely due to training-induced brain plasticity.

A Protein Synthesis and Nitric Oxide-Dependent Presynaptic Enhancement in Persistent Forms of Long-Term Potentiation

ERIC Educational Resources Information Center

Johnstone, Victoria P. A.; Raymond, Clarke R.

2011-01-01

Long-term potentiation (LTP) is an important process underlying learning and memory in the brain. At CA3-CA1 synapses in the hippocampus, three discrete forms of LTP (LTP1, 2, and 3) can be differentiated on the basis of maintenance and induction mechanisms. However, the relative roles of pre- and post-synaptic expression mechanisms in LTP1, 2,…

Medication Overuse Headache: Pathophysiological Insights from Structural and Functional Brain MRI Research.

PubMed

Schwedt, Todd J; Chong, Catherine D

2017-07-01

Research imaging of brain structure and function has helped to elucidate the pathophysiology of medication overuse headache (MOH). This is a narrative review of imaging research studies that have investigated brain structural and functional alterations associated with MOH. Studies included in this review have investigated abnormal structure and function of pain processing regions in people with MOH, functional patterns that might predispose individuals to development of MOH, similarity of brain functional patterns in patients with MOH to those found in people with addiction, brain structure that could predict headache improvement following discontinuation of the overused medication, and changes in brain structure and function after discontinuation of medication overuse. MOH is associated with atypical structure and function of brain regions responsible for pain processing as well as brain regions that are commonly implicated in addiction. Several studies have shown "normalization" of structure and function in pain processing regions following discontinuation of the overused medication and resolution of MOH. However, some of the abnormalities in regions also implicated in addiction tend to persist following discontinuation of the overused medication, suggesting that they are a brain trait that predisposes certain individuals to medication overuse and MOH. © 2017 American Headache Society.

A patient-specific CFD-based study of embolic particle transport for stroke

NASA Astrophysics Data System (ADS)

Mukherjee, Debanjan; Shadden, Shawn C.

2014-11-01

Roughly 1/3 of all strokes are caused by an embolus traveling to a cerebral artery and blocking blood flow in the brain. A detailed understanding of the dynamics of embolic particles within arteries is the basis for this study. Blood flow velocities and emboli trajectories are resolved using a coupled Euler-Lagrange approach. Computer model of the major arteries is extracted from patient image data. Blood is modeled as a Newtonian fluid, discretized using the Finite Volume method, with physiologically appropriate inflow and outflow boundary conditions. The embolus trajectory is modeled using Lagrangian particle equations accounting for embolus interaction with blood as well as vessel wall. Both one and two way fluid-particle coupling are considered, the latter being implemented using momentum sources augmented to the discretized flow equations. The study determines individual embolus path up to arteries supplying the brain, and compares the size-dependent distribution of emboli amongst vessels superior to the aortic-arch, and the role of fully coupled blood-embolus interactions in modifying both trajectory and distribution when compared with one-way coupling. Specifically for intermediate particle sizes the model developed will better characterize the risks for embolic stroke. American Heart Association (AHA) Grant: Embolic Stroke: Anatomic and Physiologic Insights from Image-Based CFD.

Evidence for discrete solar and lunar orientation mechanisms in the beach amphipod, Talitrus saltator Montagu (Crustacea, Amphipoda)

PubMed Central

Ugolini, Alberto; Hoelters, Laura S.; Ciofini, Alice; Pasquali, Vittorio; Wilcockson, David C.

2016-01-01

Animals that use astronomical cues to orientate must make continuous adjustment to account for temporal changes in azimuth caused by Earth’s rotation. For example, the Monarch butterfly possesses a time-compensated sun compass dependent upon a circadian clock in the antennae. The amphipod Talitrus saltator possesses both a sun compass and a moon compass. We reasoned that the time-compensated compass mechanism that enables solar orientation of T. saltator is located in the antennae, as is the case for Monarch butterflies. We examined activity rhythms and orientation of sandhoppers with antennae surgically removed, or unilaterally occluded with black paint. Removing or painting the antennae did not affect daily activity rhythms or competence to orientate using the sun. However, when tested at night these animals were unable to orientate correctly to the moon. We subsequently measured circadian gene expression in the antennae and brain of T. saltator and show the clock genes period and cryptochrome 2 are rhythmically expressed in both tissues, reminiscent of other arthropods known to possess antennal clocks. Together, our behavioural and molecular data suggest that, T. saltator has anatomically discrete lunar and solar orientation apparatus; a sun compass, likely located in the brain and a moon compass in the antennae. PMID:27759059

Evidence for discrete solar and lunar orientation mechanisms in the beach amphipod, Talitrus saltator Montagu (Crustacea, Amphipoda)

NASA Astrophysics Data System (ADS)

Ugolini, Alberto; Hoelters, Laura S.; Ciofini, Alice; Pasquali, Vittorio; Wilcockson, David C.

2016-10-01

Animals that use astronomical cues to orientate must make continuous adjustment to account for temporal changes in azimuth caused by Earth’s rotation. For example, the Monarch butterfly possesses a time-compensated sun compass dependent upon a circadian clock in the antennae. The amphipod Talitrus saltator possesses both a sun compass and a moon compass. We reasoned that the time-compensated compass mechanism that enables solar orientation of T. saltator is located in the antennae, as is the case for Monarch butterflies. We examined activity rhythms and orientation of sandhoppers with antennae surgically removed, or unilaterally occluded with black paint. Removing or painting the antennae did not affect daily activity rhythms or competence to orientate using the sun. However, when tested at night these animals were unable to orientate correctly to the moon. We subsequently measured circadian gene expression in the antennae and brain of T. saltator and show the clock genes period and cryptochrome 2 are rhythmically expressed in both tissues, reminiscent of other arthropods known to possess antennal clocks. Together, our behavioural and molecular data suggest that, T. saltator has anatomically discrete lunar and solar orientation apparatus; a sun compass, likely located in the brain and a moon compass in the antennae.

Discrete Electronic Bands in Semiconductors and Insulators: Potential High-Light-Yield Scintillators

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

Shi, Hongliang; Du, Mao-Hua

Bulk semiconductors and insulators typically have continuous valence and conduction bands. In this paper, we show that valence and conduction bands of a multinary semiconductor or insulator can be split to narrow discrete bands separated by large energy gaps. This unique electronic structure is demonstrated by first-principles calculations in several quaternary elpasolite compounds, i.e., Cs 2NaInBr 6, Cs 2NaBiCl 6, and Tl 2NaBiCl 6. The narrow discrete band structure in these quaternary elpasolites is due to the large electronegativity difference among cations and the large nearest-neighbor distances in cation sublattices. We further use Cs 2NaInBr 6 as an example tomore » show that the narrow bands can stabilize self-trapped and dopant-bound excitons (in which both the electron and the hole are strongly localized in static positions on adjacent sites) and promote strong exciton emission at room temperature. The discrete band structure should further suppress thermalization of hot carriers and may lead to enhanced impact ionization, which is usually considered inefficient in bulk semiconductors and insulators. Finally, these characteristics can enable efficient room-temperature light emission in low-gap scintillators and may overcome the light-yield bottleneck in current scintillator research.« less

Discrete Electronic Bands in Semiconductors and Insulators: Potential High-Light-Yield Scintillators

DOE PAGES

Shi, Hongliang; Du, Mao-Hua

2015-05-12

Bulk semiconductors and insulators typically have continuous valence and conduction bands. In this paper, we show that valence and conduction bands of a multinary semiconductor or insulator can be split to narrow discrete bands separated by large energy gaps. This unique electronic structure is demonstrated by first-principles calculations in several quaternary elpasolite compounds, i.e., Cs 2NaInBr 6, Cs 2NaBiCl 6, and Tl 2NaBiCl 6. The narrow discrete band structure in these quaternary elpasolites is due to the large electronegativity difference among cations and the large nearest-neighbor distances in cation sublattices. We further use Cs 2NaInBr 6 as an example tomore » show that the narrow bands can stabilize self-trapped and dopant-bound excitons (in which both the electron and the hole are strongly localized in static positions on adjacent sites) and promote strong exciton emission at room temperature. The discrete band structure should further suppress thermalization of hot carriers and may lead to enhanced impact ionization, which is usually considered inefficient in bulk semiconductors and insulators. Finally, these characteristics can enable efficient room-temperature light emission in low-gap scintillators and may overcome the light-yield bottleneck in current scintillator research.« less

Dynamico-FE: A Structure-Preserving Hydrostatic Dynamical Core

NASA Astrophysics Data System (ADS)

Eldred, Christopher; Dubos, Thomas; Kritsikis, Evaggelos

2017-04-01

It is well known that the inviscid, adiabatic equations of atmospheric motion constitute a non-canonical Hamiltonian system, and therefore posses many important conserved quantities such as as mass, potential vorticity and total energy. In addition, there are also key mimetic properties (such as curl grad = 0) of the underlying continuous vector calculus. Ideally, a dynamical core should have similar properties. A general approach to deriving such structure-preserving numerical schemes has been developed under the frameworks of Hamiltonian methods and mimetic discretizations, and over the past decade, there has been a great deal of work on the development of atmospheric dynamical cores using these techniques. An important example is Dynamico, which conserves mass, potential vorticity and total energy; and possesses additional mimetic properties such as a curl-free pressure gradient. Unfortunately, the underlying finite-difference discretization scheme used in Dynamico has been shown to be inconsistent on general grids. To resolve these accuracy issues, a scheme based on mimetic Galerkin discretizations has been developed that achieves higher-order accuracy while retaining the structure-preserving properties of the existing discretization. This presentation will discuss the new dynamical core, termed Dynamico-FE, and show results from a standard set of test cases on both the plane and the sphere.

Discrete Model for the Structure and Strength of Cementitious Materials

NASA Astrophysics Data System (ADS)

Balopoulos, Victor D.; Archontas, Nikolaos; Pantazopoulou, Stavroula J.

2017-12-01

Cementitious materials are characterized by brittle behavior in direct tension and by transverse dilatation (due to microcracking) under compression. Microcracking causes increasingly larger transverse strains and a phenomenological Poisson's ratio that gradually increases to about ν =0.5 and beyond, at the limit point in compression. This behavior is due to the underlying structure of cementitious pastes which is simulated here with a discrete physical model. The computational model is generic, assembled from a statistically generated, continuous network of flaky dendrites consisting of cement hydrates that emanate from partially hydrated cement grains. In the actual amorphous material, the dendrites constitute the solid phase of the cement gel and interconnect to provide the strength and stiffness against load. The idealized dendrite solid is loaded in compression and tension to compute values for strength and Poisson's effects. Parametric studies are conducted, to calibrate the statistical parameters of the discrete model with the physical and mechanical characteristics of the material, so that the familiar experimental trends may be reproduced. The model provides a framework for the study of the mechanical behavior of the material under various states of stress and strain and can be used to model the effects of additives (e.g., fibers) that may be explicitly simulated in the discrete structure.

Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders

PubMed Central

Sun, Yu; Li, Junhua; Suckling, John; Feng, Lei

2017-01-01

Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. PMID:29209197

Immersogeometric cardiovascular fluid–structure interaction analysis with divergence-conforming B-splines

PubMed Central

Kamensky, David; Hsu, Ming-Chen; Yu, Yue; Evans, John A.; Sacks, Michael S.; Hughes, Thomas J. R.

2016-01-01

This paper uses a divergence-conforming B-spline fluid discretization to address the long-standing issue of poor mass conservation in immersed methods for computational fluid–structure interaction (FSI) that represent the influence of the structure as a forcing term in the fluid subproblem. We focus, in particular, on the immersogeometric method developed in our earlier work, analyze its convergence for linear model problems, then apply it to FSI analysis of heart valves, using divergence-conforming B-splines to discretize the fluid subproblem. Poor mass conservation can manifest as effective leakage of fluid through thin solid barriers. This leakage disrupts the qualitative behavior of FSI systems such as heart valves, which exist specifically to block flow. Divergence-conforming discretizations can enforce mass conservation exactly, avoiding this problem. To demonstrate the practical utility of immersogeometric FSI analysis with divergence-conforming B-splines, we use the methods described in this paper to construct and evaluate a computational model of an in vitro experiment that pumps water through an artificial valve. PMID:28239201

Discrete distributed strain sensing of intelligent structures

NASA Technical Reports Server (NTRS)

Anderson, Mark S.; Crawley, Edward F.

1992-01-01

Techniques are developed for the design of discrete highly distributed sensor systems for use in intelligent structures. First the functional requirements for such a system are presented. Discrete spatially averaging strain sensors are then identified as satisfying the functional requirements. A variety of spatial weightings for spatially averaging sensors are examined, and their wave number characteristics are determined. Preferable spatial weightings are identified. Several numerical integration rules used to integrate such sensors in order to determine the global deflection of the structure are discussed. A numerical simulation is conducted using point and rectangular sensors mounted on a cantilevered beam under static loading. Gage factor and sensor position uncertainties are incorporated to assess the absolute error and standard deviation of the error in the estimated tip displacement found by numerically integrating the sensor outputs. An experiment is carried out using a statically loaded cantilevered beam with five point sensors. It is found that in most cases the actual experimental error is within one standard deviation of the absolute error as found in the numerical simulation.

Structured Overlapping Grid Simulations of Contra-rotating Open Rotor Noise

NASA Technical Reports Server (NTRS)

Housman, Jeffrey A.; Kiris, Cetin C.

2015-01-01

Computational simulations using structured overlapping grids with the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for predicting tonal noise generated by a contra-rotating open rotor (CROR) propulsion system. A coupled Computational Fluid Dynamics (CFD) and Computational AeroAcoustics (CAA) numerical approach is applied. Three-dimensional time-accurate hybrid Reynolds Averaged Navier-Stokes/Large Eddy Simulation (RANS/LES) CFD simulations are performed in the inertial frame, including dynamic moving grids, using a higher-order accurate finite difference discretization on structured overlapping grids. A higher-order accurate free-stream preserving metric discretization with discrete enforcement of the Geometric Conservation Law (GCL) on moving curvilinear grids is used to create an accurate, efficient, and stable numerical scheme. The aeroacoustic analysis is based on a permeable surface Ffowcs Williams-Hawkings (FW-H) approach, evaluated in the frequency domain. A time-step sensitivity study was performed using only the forward row of blades to determine an adequate time-step. The numerical approach is validated against existing wind tunnel measurements.

Mind the Gap: A Semicontinuum Model for Discrete Electrical Propagation in Cardiac Tissue.

PubMed

Costa, Caroline Mendonca; Silva, Pedro Andre Arroyo; dos Santos, Rodrigo Weber

2016-04-01

Electrical propagation in cardiac tissue is a discrete or discontinuous phenomenon that reflects the complexity of the anatomical structures and their organization in the heart, such as myocytes, gap junctions, microvessels, and extracellular matrix, just to name a few. Discrete models or microscopic and discontinuous models are, so far, the best options to accurately study how structural properties of cardiac tissue influence electrical propagation. These models are, however, inappropriate in the context of large scale simulations, which have been traditionally performed by the use of continuum and macroscopic models, such as the monodomain and the bidomain models. However, continuum models may fail to reproduce many important physiological and physiopathological aspects of cardiac electrophysiology, for instance, those related to slow conduction. In this study, we develop a new mathematical model that combines characteristics of both continuum and discrete models. The new model was evaluated in scenarios of low gap-junctional coupling, where slow conduction is observed, and was able to reproduce conduction block, increase of the maximum upstroke velocity and of the repolarization dispersion. None of these features can be captured by continuum models. In addition, the model overcomes a great disadvantage of discrete models, as it allows variation of the spatial resolution within a certain range.

Stochastic thermodynamics across scales: Emergent inter-attractoral discrete Markov jump process and its underlying continuous diffusion

NASA Astrophysics Data System (ADS)

Santillán, Moisés; Qian, Hong

2013-01-01

We investigate the internal consistency of a recently developed mathematical thermodynamic structure across scales, between a continuous stochastic nonlinear dynamical system, i.e., a diffusion process with Langevin and Fokker-Planck equations, and its emergent discrete, inter-attractoral Markov jump process. We analyze how the system’s thermodynamic state functions, e.g. free energy F, entropy S, entropy production ep, free energy dissipation Ḟ, etc., are related when the continuous system is described with coarse-grained discrete variables. It is shown that the thermodynamics derived from the underlying, detailed continuous dynamics gives rise to exactly the free-energy representation of Gibbs and Helmholtz. That is, the system’s thermodynamic structure is the same as if one only takes a middle road and starts with the natural discrete description, with the corresponding transition rates empirically determined. By natural we mean in the thermodynamic limit of a large system, with an inherent separation of time scales between inter- and intra-attractoral dynamics. This result generalizes a fundamental idea from chemistry, and the theory of Kramers, by incorporating thermodynamics: while a mechanical description of a molecule is in terms of continuous bond lengths and angles, chemical reactions are phenomenologically described by a discrete representation, in terms of exponential rate laws and a stochastic thermodynamics.

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

PubMed

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

2014-07-01

Tinnitus is a considered to be an auditory phantom phenomenon, a persistent conscious percept of a salient memory trace, externally attributed, in the absence of a sound source. It is perceived as a phenomenological unified coherent percept, binding multiple separable clinical characteristics, such as its loudness, the sidedness, the type (pure tone, noise), the associated distress and so on. A theoretical pathophysiological framework capable of explaining all these aspects in one model is highly needed. The model must incorporate both the deafferentation based neurophysiological models and the dysfunctional noise canceling model, and propose a 'tinnitus core' subnetwork. The tinnitus core can be defined as the minimal set of brain areas that needs to be jointly activated (=subnetwork) for tinnitus to be consciously perceived, devoid of its affective components. The brain areas involved in the other separable characteristics of tinnitus can be retrieved by studies on spontaneous resting state magnetic and electrical activity in people with tinnitus, evaluated for the specific aspect investigated and controlled for other factors. By combining these functional imaging studies with neuromodulation techniques some of the correlations are turned into causal relationships. Thereof, a heuristic pathophysiological framework is constructed, integrating the tinnitus perceptual core with the other tinnitus related aspects. This phenomenological unified percept of tinnitus can be considered an emergent property of multiple, parallel, dynamically changing and partially overlapping subnetworks, each with a specific spontaneous oscillatory pattern and functional connectivity signature. Communication between these different subnetworks is proposed to occur at hubs, brain areas that are involved in multiple subnetworks simultaneously. These hubs can take part in each separable subnetwork at different frequencies. Communication between the subnetworks is proposed to occur at discrete oscillatory frequencies. As such, the brain uses multiple nonspecific networks in parallel, each with their own oscillatory signature, that adapt to the context to construct a unified percept possibly by synchronized activation integrated at hubs at discrete oscillatory frequencies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Numerical modeling of fluid-structure interaction in arteries with anisotropic polyconvex hyperelastic and anisotropic viscoelastic material models at finite strains.

PubMed

Balzani, Daniel; Deparis, Simone; Fausten, Simon; Forti, Davide; Heinlein, Alexander; Klawonn, Axel; Quarteroni, Alfio; Rheinbach, Oliver; Schröder, Joerg

2016-10-01

The accurate prediction of transmural stresses in arterial walls requires on the one hand robust and efficient numerical schemes for the solution of boundary value problems including fluid-structure interactions and on the other hand the use of a material model for the vessel wall that is able to capture the relevant features of the material behavior. One of the main contributions of this paper is the application of a highly nonlinear, polyconvex anisotropic structural model for the solid in the context of fluid-structure interaction, together with a suitable discretization. Additionally, the influence of viscoelasticity is investigated. The fluid-structure interaction problem is solved using a monolithic approach; that is, the nonlinear system is solved (after time and space discretizations) as a whole without splitting among its components. The linearized block systems are solved iteratively using parallel domain decomposition preconditioners. A simple - but nonsymmetric - curved geometry is proposed that is demonstrated to be suitable as a benchmark testbed for fluid-structure interaction simulations in biomechanics where nonlinear structural models are used. Based on the curved benchmark geometry, the influence of different material models, spatial discretizations, and meshes of varying refinement is investigated. It turns out that often-used standard displacement elements with linear shape functions are not sufficient to provide good approximations of the arterial wall stresses, whereas for standard displacement elements or F-bar formulations with quadratic shape functions, suitable results are obtained. For the time discretization, a second-order backward differentiation formula scheme is used. It is shown that the curved geometry enables the analysis of non-rotationally symmetric distributions of the mechanical fields. For instance, the maximal shear stresses in the fluid-structure interface are found to be higher in the inner curve that corresponds to clinical observations indicating a high plaque nucleation probability at such locations. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

A primary microcephaly protein complex forms a ring around parental centrioles.

PubMed

Sir, Joo-Hee; Barr, Alexis R; Nicholas, Adeline K; Carvalho, Ofelia P; Khurshid, Maryam; Sossick, Alex; Reichelt, Stefanie; D'Santos, Clive; Woods, C Geoffrey; Gergely, Fanni

2011-10-09

Autosomal recessive primary microcephaly (MCPH) is characterized by a substantial reduction in prenatal human brain growth without alteration of the cerebral architecture and is caused by biallelic mutations in genes coding for a subset of centrosomal proteins. Although at least three of these proteins have been implicated in centrosome duplication, the nature of the centrosome dysfunction that underlies the neurodevelopmental defect in MCPH is unclear. Here we report a homozygous MCPH-causing mutation in human CEP63. CEP63 forms a complex with another MCPH protein, CEP152, a conserved centrosome duplication factor. Together, these two proteins are essential for maintaining normal centrosome numbers in cells. Using super-resolution microscopy, we found that CEP63 and CEP152 co-localize in a discrete ring around the proximal end of the parental centriole, a pattern specifically disrupted in CEP63-deficient cells derived from patients with MCPH. This work suggests that the CEP152-CEP63 ring-like structure ensures normal neurodevelopment and that its impairment particularly affects human cerebral cortex growth.

Is there a relationship between adult neurogenesis and neuron generation following injury across evolution?

PubMed

Ferretti, Patrizia

2011-09-01

All vertebrates can produce new neurons postnatally in discrete regions of their nervous system, but only some lower vertebrates (fish and amphibians) can significantly repair several neural structures, including brain, spinal cord, retina, olfactory and auditory-vestibular system, to compensate for neural tissue loss and recover significant functionality. Some regenerative ability, however, is found also in reptiles and birds, and even in mammals. The recognition that neurogenesis indeed occurs in the CNS of all adult vertebrates challenges the view that there is a simple relationship between maintenance of neurogenic regions in the adult CNS and regenerative capability. The aim of this review is to revisit this relationship in the light of recent literature focusing on selected examples of neurogenesis and regeneration, and discuss possible frameworks that may help to elucidate the relationship between adult neurogenesis and regeneration. This could provide useful paradigms for harnessing regeneration in the human CNS. © 2011 The Author. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

What can we learn about emotion by studying psychopathy?

PubMed Central

Marsh, Abigail A.

2013-01-01

Psychopathy is a developmental disorder associated with core affective traits, such as low empathy, guilt, and remorse, and with antisocial and aggressive behaviors. Recent neurocognitive and neuroimaging studies of psychopathy in both institutionalized and community samples have begun to illuminate the basis of this condition, in particular the ways that psychopathy affects the experience and recognition of fear. In this review, I will consider how understanding emotional processes in psychopathy can shed light on the three questions central to the study of emotion: (1) Are emotions discrete, qualitatively distinct phenomena, or quantitatively varying phenomena best described in terms of dimensions like arousal and valence? (2) What are the brain structures involved in generating specific emotions like fear, if any? And (3) how do our own experiences of emotion pertain to our perceptions of and responses to others' emotion? I conclude that insights afforded by the study of psychopathy may provide better understanding of not only fundamental social phenomena like empathy and aggression, but of the basic emotional processes that motivate these behaviors. PMID:23675335

How far could we make ourselves understood by the Andromedans? - an evolutionary cybernetic problem in hierarchical dynamics

NASA Astrophysics Data System (ADS)

Santoli, Salvatore

1994-01-01

The mechanistic interpretation of the communication process between cognitive hierarchical systems as an iterated pair of convolutions between the incoming discrete time series signals and the chaotic dynamics (CD) at the nm-scale of the perception (energy) wetware level, with the consequent feeding of the resulting collective properties to the CD software (symbolic) level, shows that the category of quality, largely present in Galilean quantitative-minded science, is to be increasingly made into quantity for finding optimum common codes for communication between different intelligent beings. The problem is similar to that solved by biological evolution, of communication between the conscious logic brain and the underlying unfelt ultimate extra-logical processes, as well as to the problem of the mind-body or the structure-function dichotomies. Perspective cybernated nanotechnological and/or nanobiological interfaces, and time evolution of the 'contact language' (the iterated dialogic process) as a self-organising system might improve human-alien understanding.

Comparative analysis of two discretizations of Ricci curvature for complex networks.

PubMed

Samal, Areejit; Sreejith, R P; Gu, Jiao; Liu, Shiping; Saucan, Emil; Jost, Jürgen

2018-06-05

We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth notion, and thus, the two notions shed light on different aspects of network structure and behavior. Nevertheless, our extensive computational analysis in a wide range of both model and real-world networks shows that the two discretizations of Ricci curvature are highly correlated in many networks. Moreover, we show that if one considers the augmented Forman-Ricci curvature which also accounts for the two-dimensional simplicial complexes arising in graphs, the observed correlation between the two discretizations is even higher, especially, in real networks. Besides the potential theoretical implications of these observations, the close relationship between the two discretizations has practical implications whereby Forman-Ricci curvature can be employed in place of Ollivier-Ricci curvature for faster computation in larger real-world networks whenever coarse analysis suffices.

State transformations and Hamiltonian structures for optimal control in discrete systems

NASA Astrophysics Data System (ADS)

Sieniutycz, S.

2006-04-01

Preserving usual definition of Hamiltonian H as the scalar product of rates and generalized momenta we investigate two basic classes of discrete optimal control processes governed by the difference rather than differential equations for the state transformation. The first class, linear in the time interval θ, secures the constancy of optimal H and satisfies a discrete Hamilton-Jacobi equation. The second class, nonlinear in θ, does not assure the constancy of optimal H and satisfies only a relationship that may be regarded as an equation of Hamilton-Jacobi type. The basic question asked is if and when Hamilton's canonical structures emerge in optimal discrete systems. For a constrained discrete control, general optimization algorithms are derived that constitute powerful theoretical and computational tools when evaluating extremum properties of constrained physical systems. The mathematical basis is Bellman's method of dynamic programming (DP) and its extension in the form of the so-called Carathéodory-Boltyanski (CB) stage optimality criterion which allows a variation of the terminal state that is otherwise fixed in Bellman's method. For systems with unconstrained intervals of the holdup time θ two powerful optimization algorithms are obtained: an unconventional discrete algorithm with a constant H and its counterpart for models nonlinear in θ. We also present the time-interval-constrained extension of the second algorithm. The results are general; namely, one arrives at: discrete canonical equations of Hamilton, maximum principles, and (at the continuous limit of processes with free intervals of time) the classical Hamilton-Jacobi theory, along with basic results of variational calculus. A vast spectrum of applications and an example are briefly discussed with particular attention paid to models nonlinear in the time interval θ.

Electrical Stimulation Modulates High γ Activity and Human Memory Performance

PubMed Central

Berry, Brent M.; Miller, Laura R.; Khadjevand, Fatemeh; Ezzyat, Youssef; Wanda, Paul; Sperling, Michael R.; Lega, Bradley; Stead, S. Matt

2018-01-01

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62–118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with “poor” memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation. PMID:29404403

An anatomically comprehensive atlas of the adult human brain transcriptome

PubMed Central

Guillozet-Bongaarts, Angela L.; Shen, Elaine H.; Ng, Lydia; Miller, Jeremy A.; van de Lagemaat, Louie N.; Smith, Kimberly A.; Ebbert, Amanda; Riley, Zackery L.; Abajian, Chris; Beckmann, Christian F.; Bernard, Amy; Bertagnolli, Darren; Boe, Andrew F.; Cartagena, Preston M.; Chakravarty, M. Mallar; Chapin, Mike; Chong, Jimmy; Dalley, Rachel A.; David Daly, Barry; Dang, Chinh; Datta, Suvro; Dee, Nick; Dolbeare, Tim A.; Faber, Vance; Feng, David; Fowler, David R.; Goldy, Jeff; Gregor, Benjamin W.; Haradon, Zeb; Haynor, David R.; Hohmann, John G.; Horvath, Steve; Howard, Robert E.; Jeromin, Andreas; Jochim, Jayson M.; Kinnunen, Marty; Lau, Christopher; Lazarz, Evan T.; Lee, Changkyu; Lemon, Tracy A.; Li, Ling; Li, Yang; Morris, John A.; Overly, Caroline C.; Parker, Patrick D.; Parry, Sheana E.; Reding, Melissa; Royall, Joshua J.; Schulkin, Jay; Sequeira, Pedro Adolfo; Slaughterbeck, Clifford R.; Smith, Simon C.; Sodt, Andy J.; Sunkin, Susan M.; Swanson, Beryl E.; Vawter, Marquis P.; Williams, Derric; Wohnoutka, Paul; Zielke, H. Ronald; Geschwind, Daniel H.; Hof, Patrick R.; Smith, Stephen M.; Koch, Christof; Grant, Seth G. N.; Jones, Allan R.

2014-01-01

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography— the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function. PMID:22996553

Genetic dissection of neural circuits underlying sexually dimorphic social behaviours

PubMed Central

Bayless, Daniel W.; Shah, Nirao M.

2016-01-01

The unique hormonal, genetic and epigenetic environments of males and females during development and adulthood shape the neural circuitry of the brain. These differences in neural circuitry result in sex-typical displays of social behaviours such as mating and aggression. Like other neural circuits, those underlying sex-typical social behaviours weave through complex brain regions that control a variety of diverse behaviours. For this reason, the functional dissection of neural circuits underlying sex-typical social behaviours has proved to be difficult. However, molecularly discrete neuronal subpopulations can be identified in the heterogeneous brain regions that control sex-typical social behaviours. In addition, the actions of oestrogens and androgens produce sex differences in gene expression within these brain regions, thereby highlighting the neuronal subpopulations most likely to control sexually dimorphic social behaviours. These conditions permit the implementation of innovative genetic approaches that, in mammals, are most highly advanced in the laboratory mouse. Such approaches have greatly advanced our understanding of the functional significance of sexually dimorphic neural circuits in the brain. In this review, we discuss the neural circuitry of sex-typical social behaviours in mice while highlighting the genetic technical innovations that have advanced the field. PMID:26833830

Discrete piezoelectric sensors and actuators for active control of two-dimensional spacecraft components

NASA Technical Reports Server (NTRS)

Bayer, Janice I.; Varadan, V. V.; Varadan, V. K.

1991-01-01

This paper describes research into the use of discrete piezoelectric sensors and actuators for active modal control of flexible two-dimensional structures such as might be used as components for spacecraft. A dynamic coupling term is defined between the sensor/actuator and the structure in terms of structural model shapes, location and piezoelectric behavior. The relative size of the coupling term determines sensor/actuator placement. Results are shown for a clamped square plate and for a large antenna. An experiment was performed on a thin foot-square plate clamped on all sides. Sizable vibration control was achieved for first, second/third (degenerate) and fourth modes.

Coupled NASTRAN/boundary element formulation for acoustic scattering

NASA Technical Reports Server (NTRS)

Everstine, Gordon C.; Henderson, Francis M.; Schuetz, Luise S.

1987-01-01

A coupled finite element/boundary element capability is described for calculating the sound pressure field scattered by an arbitrary submerged 3-D elastic structure. Structural and fluid impedances are calculated with no approximation other than discretization. The surface fluid pressures and normal velocities are first calculated by coupling a NASTRAN finite element model of the structure with a discretized form of the Helmholtz surface integral equation for the exterior field. Far field pressures are then evaluated from the surface solution using the Helmholtz exterior integral equation. The overall approach is illustrated and validated using a known analytic solution for scattering from submerged spherical shells.

Structured approaches to large-scale systems: Variational integrators for interconnected Lagrange-Dirac systems and structured model reduction on Lie groups

NASA Astrophysics Data System (ADS)

Parks, Helen Frances

This dissertation presents two projects related to the structured integration of large-scale mechanical systems. Structured integration uses the considerable differential geometric structure inherent in mechanical motion to inform the design of numerical integration schemes. This process improves the qualitative properties of simulations and becomes especially valuable as a measure of accuracy over long time simulations in which traditional Gronwall accuracy estimates lose their meaning. Often, structured integration schemes replicate continuous symmetries and their associated conservation laws at the discrete level. Such is the case for variational integrators, which discretely replicate the process of deriving equations of motion from variational principles. This results in the conservation of momenta associated to symmetries in the discrete system and conservation of a symplectic form when applicable. In the case of Lagrange-Dirac systems, variational integrators preserve a discrete analogue of the Dirac structure preserved in the continuous flow. In the first project of this thesis, we extend Dirac variational integrators to accommodate interconnected systems. We hope this work will find use in the fields of control, where a controlled system can be thought of as a "plant" system joined to its controller, and in the approach of very large systems, where modular modeling may prove easier than monolithically modeling the entire system. The second project of the thesis considers a different approach to large systems. Given a detailed model of the full system, can we reduce it to a more computationally efficient model without losing essential geometric structures in the system? Asked without the reference to structure, this is the essential question of the field of model reduction. The answer there has been a resounding yes, with Principal Orthogonal Decomposition (POD) with snapshots rising as one of the most successful methods. Our project builds on previous work to extend POD to structured settings. In particular, we consider systems evolving on Lie groups and make use of canonical coordinates in the reduction process. We see considerable improvement in the accuracy of the reduced model over the usual structure-agnostic POD approach.

Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images

PubMed Central

Lahmiri, Salim; Boukadoum, Mounir

2013-01-01

A new methodology for automatic feature extraction from biomedical images and subsequent classification is presented. The approach exploits the spatial orientation of high-frequency textural features of the processed image as determined by a two-step process. First, the two-dimensional discrete wavelet transform (DWT) is applied to obtain the HH high-frequency subband image. Then, a Gabor filter bank is applied to the latter at different frequencies and spatial orientations to obtain new Gabor-filtered image whose entropy and uniformity are computed. Finally, the obtained statistics are fed to a support vector machine (SVM) binary classifier. The approach was validated on mammograms, retina, and brain magnetic resonance (MR) images. The obtained classification accuracies show better performance in comparison to common approaches that use only the DWT or Gabor filter banks for feature extraction. PMID:27006906

Attractors for discrete periodic dynamical systems

Treesearch

John E. Franke; James F. Selgrade

2003-01-01

A mathematical framework is introduced to study attractors of discrete, nonautonomous dynamical systems which depend periodically on time. A structure theorem for such attractors is established which says that the attractor of a time-periodic dynamical system is the unin of attractors of appropriate autonomous maps. If the nonautonomous system is a perturbation of an...

Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

ERIC Educational Resources Information Center

Zhu, Xiaoshu

2013-01-01

The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

Taxometric Investigation of PTSD: Data from Two Nationally Representative Samples

ERIC Educational Resources Information Center

Broman-Fulks, Joshua J.; Ruggiero, Kenneth J.; Green, Bradley A.; Kilpatrick, Dean G.; Danielson, Carla Kmett; Resnick, Heidi S.; Saunders, Benjamin E.

2006-01-01

Current psychiatric nosology depicts posttraumatic stress disorder (PTSD) as a discrete diagnostic category. However, only one study has examined the latent structure of PTSD, and this study suggested that PTSD may be more accurately conceptualized as an extreme reaction to traumatic life events rather than a discrete clinical syndrome. To build…

Software for the Application of Discrete Latent Structure Models to Item Response Data.

ERIC Educational Resources Information Center

Haertel, Edward H.

These FORTRAN programs and MATHEMATICA routines were developed in the course of a research project titled "Achievement and Assessment in School Science: Modeling and Mapping Ability and Performance." Their use is described in other publications from that project, including "Latent Traits or Latent States? The Role of Discrete Models…

Direct evidence on the existence of [Mo132]Keplerate-type species in aqueous solution.

PubMed

Roy, Soumyajit; Planken, Karel L; Kim, Robbert; Mandele, Dexx v d; Kegel, Willem K

2007-10-15

We demonstrate the existence of discrete single molecular [Mo(132)] Keplerate-type clusters in aqueous solution. Starting from a discrete spherical [Mo(132)] cluster, the formation of an open-basket-type [Mo(116)] defect structure is shown for the first time in solution using analytical ultracentrifugation sedimentation velocity experiments.

Time-Span of Discretion and Administrative Work in School Systems: Results of a Pilot Study.

ERIC Educational Resources Information Center

Allison, Derek J.; Morfitt, Grace

1996-01-01

Investigated Elliott Jaques's theories of organizational depth structure and timespan of discretion in two Ontario school systems. Both superintendents and principals were working at two-year timespans; system directors worked at a maximum three-year timespan. Findings imply that principals' responsibilities resemble those of assistant…

A Kronecker product splitting preconditioner for two-dimensional space-fractional diffusion equations

NASA Astrophysics Data System (ADS)

Chen, Hao; Lv, Wen; Zhang, Tongtong

2018-05-01

We study preconditioned iterative methods for the linear system arising in the numerical discretization of a two-dimensional space-fractional diffusion equation. Our approach is based on a formulation of the discrete problem that is shown to be the sum of two Kronecker products. By making use of an alternating Kronecker product splitting iteration technique we establish a class of fixed-point iteration methods. Theoretical analysis shows that the new method converges to the unique solution of the linear system. Moreover, the optimal choice of the involved iteration parameters and the corresponding asymptotic convergence rate are computed exactly when the eigenvalues of the system matrix are all real. The basic iteration is accelerated by a Krylov subspace method like GMRES. The corresponding preconditioner is in a form of a Kronecker product structure and requires at each iteration the solution of a set of discrete one-dimensional fractional diffusion equations. We use structure preserving approximations to the discrete one-dimensional fractional diffusion operators in the action of the preconditioning matrix. Numerical examples are presented to illustrate the effectiveness of this approach.

A mathematical model of the structure and evolution of small scale discrete auroral arcs

NASA Technical Reports Server (NTRS)

Seyler, C. E.

1990-01-01

A three dimensional fluid model which includes the dispersive effect of electron inertia is used to study the nonlinear macroscopic plasma dynamics of small scale discrete auroral arcs within the auroral acceleration zone and ionosphere. The motion of the Alfven wave source relative to the magnetospheric and ionospheric plasma forms an oblique Alfven wave which is reflected from the topside ionosphere by the negative density gradient. The superposition of the incident and reflected wave can be described by a steady state analytical solution of the model equations with the appropriate boundary conditions. This two dimensional discrete auroral arc equilibrium provides a simple explanation of auroral acceleration associated with the parallel electric field. Three dimensional fully nonlinear numerical simulations indicate that the equilibrium arc configuration evolves three dimensionally through collisionless tearing and reconnection of the current layer. The interaction of the perturbed flow and the transverse magnetic field produces complex transverse structure that may be the origin of the folds and curls observed to be associated with small scale discrete arcs.

A network of discrete events for the representation and analysis of diffusion dynamics.

PubMed

Pintus, Alberto M; Pazzona, Federico G; Demontis, Pierfranco; Suffritti, Giuseppe B

2015-11-14

We developed a coarse-grained description of the phenomenology of diffusive processes, in terms of a space of discrete events and its representation as a network. Once a proper classification of the discrete events underlying the diffusive process is carried out, their transition matrix is calculated on the basis of molecular dynamics data. This matrix can be represented as a directed, weighted network where nodes represent discrete events, and the weight of edges is given by the probability that one follows the other. The structure of this network reflects dynamical properties of the process of interest in such features as its modularity and the entropy rate of nodes. As an example of the applicability of this conceptual framework, we discuss here the physics of diffusion of small non-polar molecules in a microporous material, in terms of the structure of the corresponding network of events, and explain on this basis the diffusivity trends observed. A quantitative account of these trends is obtained by considering the contribution of the various events to the displacement autocorrelation function.

Geometry Of Discrete Sets With Applications To Pattern Recognition

NASA Astrophysics Data System (ADS)

Sinha, Divyendu

1990-03-01

In this paper we present a new framework for discrete black and white images that employs only integer arithmetic. This framework is shown to retain the essential characteristics of the framework for Euclidean images. We propose two norms and based on them, the permissible geometric operations on images are defined. The basic invariants of our geometry are line images, structure of image and the corresponding local property of strong attachment of pixels. The permissible operations also preserve the 3x3 neighborhoods, area, and perpendicularity. The structure, patterns, and the inter-pattern gaps in a discrete image are shown to be conserved by the magnification and contraction process. Our notions of approximate congruence, similarity and symmetry are similar, in character, to the corresponding notions, for Euclidean images [1]. We mention two discrete pattern recognition algorithms that work purely with integers, and which fit into our framework. Their performance has been shown to be at par with the performance of traditional geometric schemes. Also, all the undesired effects of finite length registers in fixed point arithmetic that plague traditional algorithms, are non-existent in this family of algorithms.

Higher-order adaptive finite-element methods for Kohn–Sham density functional theory

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

Motamarri, P.; Nowak, M.R.; Leiter, K.

2013-11-15

We present an efficient computational approach to perform real-space electronic structure calculations using an adaptive higher-order finite-element discretization of Kohn–Sham density-functional theory (DFT). To this end, we develop an a priori mesh-adaption technique to construct a close to optimal finite-element discretization of the problem. We further propose an efficient solution strategy for solving the discrete eigenvalue problem by using spectral finite-elements in conjunction with Gauss–Lobatto quadrature, and a Chebyshev acceleration technique for computing the occupied eigenspace. The proposed approach has been observed to provide a staggering 100–200-fold computational advantage over the solution of a generalized eigenvalue problem. Using the proposedmore » solution procedure, we investigate the computational efficiency afforded by higher-order finite-element discretizations of the Kohn–Sham DFT problem. Our studies suggest that staggering computational savings—of the order of 1000-fold—relative to linear finite-elements can be realized, for both all-electron and local pseudopotential calculations, by using higher-order finite-element discretizations. On all the benchmark systems studied, we observe diminishing returns in computational savings beyond the sixth-order for accuracies commensurate with chemical accuracy, suggesting that the hexic spectral-element may be an optimal choice for the finite-element discretization of the Kohn–Sham DFT problem. A comparative study of the computational efficiency of the proposed higher-order finite-element discretizations suggests that the performance of finite-element basis is competing with the plane-wave discretization for non-periodic local pseudopotential calculations, and compares to the Gaussian basis for all-electron calculations to within an order of magnitude. Further, we demonstrate the capability of the proposed approach to compute the electronic structure of a metallic system containing 1688 atoms using modest computational resources, and good scalability of the present implementation up to 192 processors.« less

Neural mechanisms of hypnosis and meditation.

PubMed

De Benedittis, Giuseppe

2015-12-01

Hypnosis has been an elusive concept for science for a long time. However, the explosive advances in neuroscience in the last few decades have provided a "bridge of understanding" between classical neurophysiological studies and psychophysiological studies. These studies have shed new light on the neural basis of the hypnotic experience. Furthermore, an ambitious new area of research is focusing on mapping the core processes of psychotherapy and the neurobiology/underlying them. Hypnosis research offers powerful techniques to isolate psychological processes in ways that allow their neural bases to be mapped. The Hypnotic Brain can serve as a way to tap neurocognitive questions and our cognitive assays can in turn shed new light on the neural bases of hypnosis. This cross-talk should enhance research and clinical applications. An increasing body of evidence provides insight in the neural mechanisms of the Meditative Brain. Discrete meditative styles are likely to target different neurodynamic patterns. Recent findings emphasize increased attentional resources activating the attentional and salience networks with coherent perception. Cognitive and emotional equanimity gives rise to an eudaimonic state, made of calm, resilience and stability, readiness to express compassion and empathy, a main goal of Buddhist practices. Structural changes in gray matter of key areas of the brain involved in learning processes suggest that these skills can be learned through practice. Hypnosis and Meditation represent two important, historical and influential landmarks of Western and Eastern civilization and culture respectively. Neuroscience has beginning to provide a better understanding of the mechanisms of both Hypnotic and Meditative Brain, outlining similarities but also differences between the two states and processes. It is important not to view either the Eastern or the Western system as superior to the other. Cross-fertilization of the ancient Eastern meditation techniques presented with Western modern clinical hypnosis will hopefully result in each enriching the other. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cortical spreading depression: An enigma

NASA Astrophysics Data System (ADS)

Miura, R. M.; Huang, H.; Wylie, J. J.

2007-08-01

The brain is a complex organ with active components composed largely of neurons, glial cells, and blood vessels. There exists an enormous experimental and theoretical literature on the mechanisms involved in the functioning of the brain, but we still do not have a good understanding of how it works on a gross mechanistic level. In general, the brain maintains a homeostatic state with relatively small ion concentration changes, the major ions being sodium, potassium, and chloride. Calcium ions are present in smaller quantities but still play an important role in many phenomena. Cortical spreading depression (CSD for short) was discovered over 60 years ago by A.A.P. Leão, a Brazilian physiologist doing his doctoral research on epilepsy at Harvard University, “Spreading depression of activity in the cerebral cortex," J. Neurophysiol., 7 (1944), pp. 359-390. Cortical spreading depression is characterized by massive changes in ionic concentrations and slow nonlinear chemical waves, with speeds on the order of mm/min, in the cortex of different brain structures in various experimental animals. In humans, CSD is associated with migraine with aura, where a light scintillation in the visual field propagates, then disappears, and is followed by a sustained headache. To date, CSD remains an enigma, and further detailed experimental and theoretical investigations are needed to develop a comprehensive picture of the diverse mechanisms involved in producing CSD. A number of mechanisms have been hypothesized to be important for CSD wave propagation. In this paper, we briefly describe several characteristics of CSD wave propagation, and examine some of the mechanisms that are believed to be important, including ion diffusion, membrane ionic currents, osmotic effects, spatial buffering, neurotransmitter substances, gap junctions, metabolic pumps, and synaptic connections. Continuum models of CSD, consisting of coupled nonlinear diffusion equations for the ion concentrations, and a discrete lattice-Boltzmann method approach will be described. Also, we will describe some open problems and remaining challenges.

Structure of random discrete spacetime

NASA Technical Reports Server (NTRS)

Brightwell, Graham; Gregory, Ruth

1991-01-01

The usual picture of spacetime consists of a continuous manifold, together with a metric of Lorentzian signature which imposes a causal structure on the spacetime. A model, first suggested by Bombelli et al., is considered in which spacetime consists of a discrete set of points taken at random from a manifold, with only the causal structure on this set remaining. This structure constitutes a partially ordered set (or poset). Working from the poset alone, it is shown how to construct a metric on the space which closely approximates the metric on the original spacetime manifold, how to define the effective dimension of the spacetime, and how such quantities may depend on the scale of measurement. Possible desirable features of the model are discussed.

The structure of random discrete spacetime

NASA Technical Reports Server (NTRS)

Brightwell, Graham; Gregory, Ruth

1990-01-01

The usual picture of spacetime consists of a continuous manifold, together with a metric of Lorentzian signature which imposes a causal structure on the spacetime. A model, first suggested by Bombelli et al., is considered in which spacetime consists of a discrete set of points taken at random from a manifold, with only the causal structure on this set remaining. This structure constitutes a partially ordered set (or poset). Working from the poset alone, it is shown how to construct a metric on the space which closely approximates the metric on the original spacetime manifold, how to define the effective dimension of the spacetime, and how such quantities may depend on the scale of measurement. Possible desirable features of the model are discussed.

Analysis and design of numerical schemes for gas dynamics. 2: Artificial diffusion and discrete shock structure

NASA Technical Reports Server (NTRS)

Jameson, Antony

1994-01-01

The effect of artificial diffusion on discrete shock structures is examined for a family of schemes which includes scalar diffusion, convective upwind and split pressure (CUSP) schemes, and upwind schemes with characteristics splitting. The analysis leads to conditions on the diffusive flux such that stationary discrete shocks can contain a single interior point. The simplest formulation which meets these conditions is a CUSP scheme in which the coefficients of the pressure differences is fully determined by the coefficient of convective diffusion. It is also shown how both the characteristic and CUSP schemes can be modified to preserve constant stagnation enthalpy in steady flow, leading to four variants, the E and H-characteristic schemes, and the E and H-CUSP schemes. Numerical results are presented which confirm the properties of these schemes.

Amplifying (Im)perfection: The Impact of Crystallinity in Discrete and Disperse Block Co-oligomers

PubMed Central

2017-01-01

Crystallinity is seldomly utilized as part of the microphase segregation process in ultralow-molecular-weight block copolymers. Here, we show the preparation of two types of discrete, semicrystalline block co-oligomers, comprising an amorphous oligodimethylsiloxane block and a crystalline oligo-l-lactic acid or oligomethylene block. The self-assembly of these discrete materials results in lamellar structures with unforeseen uniformity in the domain spacing. A systematic introduction of dispersity reveals the extreme sensitivity of the microphase segregation process toward chain length dispersity in the crystalline block. PMID:28994585

Mimetic discretization of the Abelian Chern-Simons theory and link invariants

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

Di Bartolo, Cayetano; Grau, Javier; Leal, Lorenzo

A mimetic discretization of the Abelian Chern-Simons theory is presented. The study relies on the formulation of a theory of differential forms in the lattice, including a consistent definition of the Hodge duality operation. Explicit expressions for the Gauss Linking Number in the lattice, which correspond to their continuum counterparts are given. A discussion of the discretization of metric structures in the space of transverse vector densities is presented. The study of these metrics could serve to obtain explicit formulae for knot an link invariants in the lattice.

Mimetic discretization of the Abelian Chern-Simons theory and link invariants

NASA Astrophysics Data System (ADS)

Di Bartolo, Cayetano; Grau, Javier; Leal, Lorenzo

2013-12-01

A mimetic discretization of the Abelian Chern-Simons theory is presented. The study relies on the formulation of a theory of differential forms in the lattice, including a consistent definition of the Hodge duality operation. Explicit expressions for the Gauss Linking Number in the lattice, which correspond to their continuum counterparts are given. A discussion of the discretization of metric structures in the space of transverse vector densities is presented. The study of these metrics could serve to obtain explicit formulae for knot an link invariants in the lattice.

Amplifying (Im)perfection: The Impact of Crystallinity in Discrete and Disperse Block Co-oligomers.

PubMed

van Genabeek, Bas; Lamers, Brigitte A G; de Waal, Bas F M; van Son, Martin H C; Palmans, Anja R A; Meijer, E W

2017-10-25

Crystallinity is seldomly utilized as part of the microphase segregation process in ultralow-molecular-weight block copolymers. Here, we show the preparation of two types of discrete, semicrystalline block co-oligomers, comprising an amorphous oligodimethylsiloxane block and a crystalline oligo-l-lactic acid or oligomethylene block. The self-assembly of these discrete materials results in lamellar structures with unforeseen uniformity in the domain spacing. A systematic introduction of dispersity reveals the extreme sensitivity of the microphase segregation process toward chain length dispersity in the crystalline block.

Current management of the cognitive dysfunction in Parkinson's disease: how far have we come?

PubMed

Vale, Salvador

2008-08-01

Parkinson's disease (PD) clinical features comprise both motor and nonmotor manifestations. Among the nonmotor complications, dementia is the most important. Approximately 40% of PD patients are affected by cognitive impairment. Remarkably, in addition to age, dementia is an independent predictor of mortality, whereas age at onset of PD and severity of neurological symptoms are not. In this review, I summarize the current knowledge of the pathogenesis of the PD cognitive impairment in relation to the therapies presently accessible and those that could become strategic in the near future. It is hypothesized that patients with PD show two components of cognitive dysfunction (CD): a generalized profile of subcortical dementia (PDsCD), and an overlapped pattern suggesting specific prefrontal damage with CD (PDpFCD). PDsCD is associated with structural neocortical/subcortical changes in the brain (in frontal, parietal, limbic, and temporal lobes, as well as in midbrain structures). In PDpFCD cognitive deficits comprise impairments in neuropsychological tests sensitive for frontal lobe function (discrete elements of episodic and working memory for instance), which are considered to be the consequence of dysfunction in neuronal loops connecting the prefrontal cortex and basal ganglia. Drugs reviewed for targeting PDsCD include: cholinesterase inhibitors, agents with mixed cholinergic and dopaminergic properties, antiglutamatergic drugs, mixed antiglutamatergic/dopaminergic agents; antioxidants and enhancers of mitochondrial functions, and anti-COX-2, as well as other anti-inflammatory mediators. Preliminary studies with vehicles that may target PDpFCD include piribedil, tolcapone, amantadine, and farampator. Additional agents (citicoline and neuroimmuniphilines, among others) will be outlined. A brief overview on neuroprotection and promising new biological advances in PD (deep brain stimulation, stem cells, gene therapy) also will be summarized.

Mapping a multidimensional emotion in response to television commercials.

PubMed

Morris, Jon D; Klahr, Nelson J; Shen, Feng; Villegas, Jorge; Wright, Paul; He, Guojun; Liu, Yijun

2009-03-01

Unlike previous emotional studies using functional neuroimaging that have focused on either locating discrete emotions in the brain or linking emotional response to an external behavior, this study investigated brain regions in order to validate a three-dimensional construct--namely pleasure, arousal, and dominance (PAD) of emotion induced by marketing communication. Emotional responses to five television commercials were measured with Advertisement Self-Assessment Manikins (AdSAM) for PAD and with functional magnetic resonance imaging (fMRI) to identify corresponding patterns of brain activation. We found significant differences in the AdSAM scores on the pleasure and arousal rating scales among the stimuli. Using the AdSAM response as a model for the fMRI image analysis, we showed bilateral activations in the inferior frontal gyri and middle temporal gyri associated with the difference on the pleasure dimension, and activations in the right superior temporal gyrus and right middle frontal gyrus associated with the difference on the arousal dimension. These findings suggest a dimensional approach of constructing emotional changes in the brain and provide a better understanding of human behavior in response to advertising stimuli.

Signals from the brainstem sleep/wake centers regulate behavioral timing via the circadian clock.

PubMed

Abbott, Sabra M; Arnold, Jennifer M; Chang, Qing; Miao, Hai; Ota, Nobutoshi; Cecala, Christine; Gold, Paul E; Sweedler, Jonathan V; Gillette, Martha U

2013-01-01

Sleep-wake cycling is controlled by the complex interplay between two brain systems, one which controls vigilance state, regulating the transition between sleep and wake, and the other circadian, which communicates time-of-day. Together, they align sleep appropriately with energetic need and the day-night cycle. Neural circuits connect brain stem sites that regulate vigilance state with the suprachiasmatic nucleus (SCN), the master circadian clock, but the function of these connections has been unknown. Coupling discrete stimulation of pontine nuclei controlling vigilance state with analytical chemical measurements of intra-SCN microdialysates in mouse, we found significant neurotransmitter release at the SCN and, concomitantly, resetting of behavioral circadian rhythms. Depending upon stimulus conditions and time-of-day, SCN acetylcholine and/or glutamate levels were augmented and generated shifts of behavioral rhythms. These results establish modes of neurochemical communication from brain regions controlling vigilance state to the central circadian clock, with behavioral consequences. They suggest a basis for dynamic integration across brain systems that regulate vigilance states, and a potential vulnerability to altered communication in sleep disorders.

Analysis of structure-function network decoupling in the brain systems of spastic diplegic cerebral palsy.

PubMed

Lee, Dongha; Pae, Chongwon; Lee, Jong Doo; Park, Eun Sook; Cho, Sung-Rae; Um, Min-Hee; Lee, Seung-Koo; Oh, Maeng-Keun; Park, Hae-Jeong

2017-10-01

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.

PubMed

Yee, Yohan; Fernandes, Darren J; French, Leon; Ellegood, Jacob; Cahill, Lindsay S; Vousden, Dulcie A; Spencer Noakes, Leigh; Scholz, Jan; van Eede, Matthijs C; Nieman, Brian J; Sled, John G; Lerch, Jason P

2018-05-18

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance. Copyright © 2018. Published by Elsevier Inc.

Discrete mathematics in deaf education: a survey of teachers' knowledge and use.

PubMed

Pagliaro, Claudia M; Kritzer, Karen L

The study documents what deaf education teachers know about discrete mathematics topics and determines if these topics are present in the mathematics curriculum. Survey data were collected from 290 mathematics teachers at center and public school programs serving a minimum of 120 students with hearing loss, grades K-8 or K-12, in the United States. Findings indicate that deaf education teachers are familiar with many discrete mathematics topics but do not include them in instruction because they consider the concepts too complicated for their students. Also, regardless of familiarity level, deaf education teachers are not familiar with discrete mathematics terminology; nor is their mathematics teaching structured to provide opportunities to apply the real-world-oriented activities used in discrete mathematics instruction. Findings emphasize the need for higher expectations of students with hearing loss, and for reform in mathematics curriculum and instruction within deaf education.

A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement.

PubMed

Taylor, Paul G; Small, Michael; Lee, Kwee-Yum; Landeo, Raul; O'Meara, Damien M; Millett, Emma L

2016-10-01

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing.

PubMed

Renthal, William

2018-01-01

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

STITCHER: Dynamic assembly of likely amyloid and prion β-structures from secondary structure predictions

PubMed Central

Bryan, Allen W; O’Donnell, Charles W; Menke, Matthew; Cowen, Lenore J; Lindquist, Susan; Berger, Bonnie

2012-01-01

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete β-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete β-strand pairs into complete amyloid β-structures. The STITCHER algorithm progressively ‘stitches’ strand-pairs into full β-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel β-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer’s amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies. Proteins 2012. © 2011 Wiley Periodicals, Inc. PMID:22095906

STITCHER: Dynamic assembly of likely amyloid and prion β-structures from secondary structure predictions.

PubMed

Bryan, Allen W; O'Donnell, Charles W; Menke, Matthew; Cowen, Lenore J; Lindquist, Susan; Berger, Bonnie

2012-02-01

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete β-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete β-strand pairs into complete amyloid β-structures. The STITCHER algorithm progressively 'stitches' strand-pairs into full β-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel β-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer's amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies. Copyright © 2011 Wiley Periodicals, Inc.

The Pathophysiology of Repetitive Concussive Traumatic Brain Injury in Experimental Models; New Developments and Open Questions

PubMed Central

Brody, David L; Benetatos, Joseph; Bennett, Rachel E; Klemenhagen, Kristen C; Donald, Christine L Mac

2015-01-01

In recent years, there has been an increasing interest in the pathophysiology of repetitive concussive traumatic brain injury (rcTBI) in large part due to the association with dramatic cases of progressive neurological deterioration in professional athletes, military personnel, and others. However, our understanding of the pathophysiology of rcTBI is less advanced than for more severe brain injuries. Most prominently, the mechanisms underlying traumatic axonal injury, microglial activation, amyloid-beta accumulation, and progressive tau pathology are not yet known. In addition, the role of injury to dendritic spine cytoskeletal structures, vascular reactivity impairments, and microthrombi are intriguing and subjects of ongoing inquiry. Methods for quantitative analysis of axonal injury, dendritic injury, and synaptic loss need to be refined for the field to move forward in a rigorous fashion. We and others are attempting to develop translational approaches to assess these specific pathophysiological events in both animals and humans to facilitate clinically relevant pharmacodynamic assessments of candidate therapeutics. In this article, we review and discuss several of the recent experimental results from our lab and others. We include new initial data describing the difficulty in modeling progressive tau pathology in experimental rcTBI, and results demonstrating that sertraline can alleviate social interaction deficits and depressive-like behaviors following experimental rcTBI plus foot shock stress. Furthermore, we propose a discrete set of open, experimentally tractable questions that may serve as a framework for future investigations. In addition, we also raise several important questions that are less experimentally tractable at this time, in hopes that they may stimulate future methodological developments to address them. PMID:25684677

Gene regulatory network analysis reveals differences in site-specific cell fate determination in mammalian brain

PubMed Central

Ertaylan, Gökhan; Okawa, Satoshi; Schwamborn, Jens C.; del Sol, Antonio

2014-01-01

Neurogenesis—the generation of new neurons—is an ongoing process that persists in the adult mammalian brain of several species, including humans. In this work we analyze two discrete brain regions: the subventricular zone (SVZ) lining the walls of the lateral ventricles; and the subgranular zone (SGZ) of the dentate gyrus (DG) of the hippocampus in mice and shed light on the SVZ and SGZ specific neurogenesis. We propose a computational model that relies on the construction and analysis of region specific gene regulatory networks (GRNs) from the publicly available data on these two regions. Using this model a number of putative factors involved in neuronal stem cell (NSC) identity and maintenance were identified. We also demonstrate potential gender and niche-derived differences based on cell surface and nuclear receptors via Ar, Hif1a, and Nr3c1. We have also conducted cell fate determinant analysis for SVZ NSC populations to Olfactory Bulb interneurons and SGZ NSC populations to the granule cells of the Granular Cell Layer. We report 31 candidate cell fate determinant gene pairs, ready to be validated. We focus on Ar—Pax6 in SVZ and Sox2—Ncor1 in SGZ. Both pairs are expressed and localized in the suggested anatomical structures as shown by in situ hybridization and found to physically interact. Finally, we conclude that there are fundamental differences between SGZ and SVZ neurogenesis. We argue that these regulatory mechanisms are linked to the observed differential neurogenic potential of these regions. The presence of nuclear and cell surface receptors in the region specific regulatory circuits indicate the significance of niche derived extracellular factors, hormones and region specific factors such as the oxygen sensitivity, dictating SGZ and SVZ specific neurogenesis. PMID:25565969

Research on the Factors Influencing the Measurement Errors of the Discrete Rogowski Coil †

PubMed Central

Xu, Mengyuan; Yan, Jing; Geng, Yingsan; Zhang, Kun; Sun, Chao

2018-01-01

An innovative array of magnetic coils (the discrete Rogowski coil—RC) with the advantages of flexible structure, miniaturization and mass producibility is investigated. First, the mutual inductance between the discrete RC and circular and rectangular conductors are calculated using the magnetic vector potential (MVP) method. The results are found to be consistent with those calculated using the finite element method, but the MVP method is simpler and more practical. Then, the influence of conductor section parameters, inclination, and eccentricity on the accuracy of the discrete RC is calculated to provide a reference. Studying the influence of an external current on the discrete RC’s interference error reveals optimal values for length, winding density, and position arrangement of the solenoids. It has also found that eccentricity and interference errors decreasing with increasing number of solenoids. Finally, a discrete RC prototype is devised and manufactured. The experimental results show consistent output characteristics, with the calculated sensitivity and mutual inductance of the discrete RC being very close to the experimental results. The influence of an external conductor on the measurement of the discrete RC is analyzed experimentally, and the results show that interference from an external current decreases with increasing distance between the external and measured conductors. PMID:29534006

Research on the Factors Influencing the Measurement Errors of the Discrete Rogowski Coil.

PubMed

Xu, Mengyuan; Yan, Jing; Geng, Yingsan; Zhang, Kun; Sun, Chao

2018-03-13

An innovative array of magnetic coils (the discrete Rogowski coil-RC) with the advantages of flexible structure, miniaturization and mass producibility is investigated. First, the mutual inductance between the discrete RC and circular and rectangular conductors are calculated using the magnetic vector potential (MVP) method. The results are found to be consistent with those calculated using the finite element method, but the MVP method is simpler and more practical. Then, the influence of conductor section parameters, inclination, and eccentricity on the accuracy of the discrete RC is calculated to provide a reference. Studying the influence of an external current on the discrete RC's interference error reveals optimal values for length, winding density, and position arrangement of the solenoids. It has also found that eccentricity and interference errors decreasing with increasing number of solenoids. Finally, a discrete RC prototype is devised and manufactured. The experimental results show consistent output characteristics, with the calculated sensitivity and mutual inductance of the discrete RC being very close to the experimental results. The influence of an external conductor on the measurement of the discrete RC is analyzed experimentally, and the results show that interference from an external current decreases with increasing distance between the external and measured conductors.

Intrinsic energy localization through discrete gap breathers in one-dimensional diatomic granular crystals.

PubMed

Theocharis, G; Boechler, N; Kevrekidis, P G; Job, S; Porter, Mason A; Daraio, C

2010-11-01

We present a systematic study of the existence and stability of discrete breathers that are spatially localized in the bulk of a one-dimensional chain of compressed elastic beads that interact via Hertzian contact. The chain is diatomic, consisting of a periodic arrangement of heavy and light spherical particles. We examine two families of discrete gap breathers: (1) an unstable discrete gap breather that is centered on a heavy particle and characterized by a symmetric spatial energy profile and (2) a potentially stable discrete gap breather that is centered on a light particle and is characterized by an asymmetric spatial energy profile. We investigate their existence, structure, and stability throughout the band gap of the linear spectrum and classify them into four regimes: a regime near the lower optical band edge of the linear spectrum, a moderately discrete regime, a strongly discrete regime that lies deep within the band gap of the linearized version of the system, and a regime near the upper acoustic band edge. We contrast discrete breathers in anharmonic Fermi-Pasta-Ulam (FPU)-type diatomic chains with those in diatomic granular crystals, which have a tensionless interaction potential between adjacent particles, and note that the asymmetric nature of the tensionless interaction potential can lead to hybrid bulk-surface localized solutions.

Intrinsic energy localization through discrete gap breathers in one-dimensional diatomic granular crystals

NASA Astrophysics Data System (ADS)

Theocharis, G.; Boechler, N.; Kevrekidis, P. G.; Job, S.; Porter, Mason A.; Daraio, C.

2010-11-01

We present a systematic study of the existence and stability of discrete breathers that are spatially localized in the bulk of a one-dimensional chain of compressed elastic beads that interact via Hertzian contact. The chain is diatomic, consisting of a periodic arrangement of heavy and light spherical particles. We examine two families of discrete gap breathers: (1) an unstable discrete gap breather that is centered on a heavy particle and characterized by a symmetric spatial energy profile and (2) a potentially stable discrete gap breather that is centered on a light particle and is characterized by an asymmetric spatial energy profile. We investigate their existence, structure, and stability throughout the band gap of the linear spectrum and classify them into four regimes: a regime near the lower optical band edge of the linear spectrum, a moderately discrete regime, a strongly discrete regime that lies deep within the band gap of the linearized version of the system, and a regime near the upper acoustic band edge. We contrast discrete breathers in anharmonic Fermi-Pasta-Ulam (FPU)-type diatomic chains with those in diatomic granular crystals, which have a tensionless interaction potential between adjacent particles, and note that the asymmetric nature of the tensionless interaction potential can lead to hybrid bulk-surface localized solutions.

Discrete-time Markovian stochastic Petri nets

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco

1995-01-01

We revisit and extend the original definition of discrete-time stochastic Petri nets, by allowing the firing times to have a 'defective discrete phase distribution'. We show that this formalism still corresponds to an underlying discrete-time Markov chain. The structure of the state for this process describes both the marking of the Petri net and the phase of the firing time for each transition, resulting in a large state space. We then modify the well-known power method to perform a transient analysis even when the state space is infinite, subject to the condition that only a finite number of states can be reached in a finite amount of time. Since the memory requirements might still be excessive, we suggest a bounding technique based on truncation.

Characterization via atomic force microscopy of discrete plasticity in collagen fibrils from mechanically overloaded tendons: Nano-scale structural changes mimic rope failure.

PubMed

Baldwin, Samuel J; Kreplak, Laurent; Lee, J Michael

2016-07-01

Tendons exposed to tensile overload show a structural alteration at the fibril scale termed discrete plasticity. Serial kinks appear along individual collagen fibrils that are susceptible to enzymatic digestion and are thermally unstable. Using atomic force microscopy we mapped the topography and mechanical properties in dehydrated and hydrated states of 25 control fibrils and 25 fibrils displaying periodic kinks, extracted from overloaded bovine tail tendons. Using the measured modulus of the hydrated fibrils as a probe of molecular density, we observed a non-linear negative correlation between molecular density and kink density of individual fibrils. This is accompanied by an increase in water uptake with kink density and a doubling of the coefficient of variation of the modulus between kinked, and control fibrils. The mechanical property maps of kinked collagen fibrils show radial heterogeneity that can be modeled as a high-density core surrounded by a low-density shell. The core of the fibril contains the kink structures characteristic of discrete plasticity; separated by inter-kink regions, which often retain the D-banding structure. We propose that the shell and kink structures mimic characteristic damage motifs observed in laid rope strands. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improved Displacement Transfer Functions for Structure Deformed Shape Predictions Using Discretely Distributed Surface Strains

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2012-01-01

In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.

Parallel multiscale simulations of a brain aneurysm

PubMed Central

Grinberg, Leopold; Fedosov, Dmitry A.; Karniadakis, George Em

2012-01-01

Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multi-scale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier-Stokes solver εκ αr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers ( εκ αr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future work. PMID:23734066

Parallel multiscale simulations of a brain aneurysm.

PubMed

Grinberg, Leopold; Fedosov, Dmitry A; Karniadakis, George Em

2013-07-01

Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multi-scale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier-Stokes solver εκ αr . The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers ( εκ αr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future work.

Parallel multiscale simulations of a brain aneurysm

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

Grinberg, Leopold; Fedosov, Dmitry A.; Karniadakis, George Em, E-mail: george_karniadakis@brown.edu

2013-07-01

Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm.more » The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future work.« less

Insights into Brain Glycogen Metabolism: THE STRUCTURE OF HUMAN BRAIN GLYCOGEN PHOSPHORYLASE.

PubMed

Mathieu, Cécile; Li de la Sierra-Gallay, Ines; Duval, Romain; Xu, Ximing; Cocaign, Angélique; Léger, Thibaut; Woffendin, Gary; Camadro, Jean-Michel; Etchebest, Catherine; Haouz, Ahmed; Dupret, Jean-Marie; Rodrigues-Lima, Fernando

2016-08-26

Brain glycogen metabolism plays a critical role in major brain functions such as learning or memory consolidation. However, alteration of glycogen metabolism and glycogen accumulation in the brain contributes to neurodegeneration as observed in Lafora disease. Glycogen phosphorylase (GP), a key enzyme in glycogen metabolism, catalyzes the rate-limiting step of glycogen mobilization. Moreover, the allosteric regulation of the three GP isozymes (muscle, liver, and brain) by metabolites and phosphorylation, in response to hormonal signaling, fine-tunes glycogenolysis to fulfill energetic and metabolic requirements. Whereas the structures of muscle and liver GPs have been known for decades, the structure of brain GP (bGP) has remained elusive despite its critical role in brain glycogen metabolism. Here, we report the crystal structure of human bGP in complex with PEG 400 (2.5 Å) and in complex with its allosteric activator AMP (3.4 Å). These structures demonstrate that bGP has a closer structural relationship with muscle GP, which is also activated by AMP, contrary to liver GP, which is not. Importantly, despite the structural similarities between human bGP and the two other mammalian isozymes, the bGP structures reveal molecular features unique to the brain isozyme that provide a deeper understanding of the differences in the activation properties of these allosteric enzymes by the allosteric effector AMP. Overall, our study further supports that the distinct structural and regulatory properties of GP isozymes contribute to the different functions of muscle, liver, and brain glycogen. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Examining the Influence of Campus Climate on Students' Time to Degree: A Multilevel Discrete-Time Survival Analysis

ERIC Educational Resources Information Center

Zhou, Ji; Castellanos, Michelle

2013-01-01

Utilizing longitudinal data of 3477 students from 28 institutions, we examine the effects of structural diversity and quality of interracial relation on students' persistence towards graduation within six years. We utilize multilevel discrete-time survival analysis to account for the longitudinal persistence patterns as well as the nested…

The role of discretion in recreation decision-making by resource professionals in the USDA Forest Service

Treesearch

Teressa Trusty; Lee K. Cerveny

2012-01-01

This paper explores opportunities for administrative discretion in decision-making for natural resource management. We carried out an exploratory study in the USDA Forest Service to understand factors affecting administrative actions related to recreation use in riparian areas. We conducted semi-structured interviews with 27 resource professionals from a national...

Human Brain Modeling with Its Anatomical Structure and Realistic Material Properties for Brain Injury Prediction.

PubMed

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

2018-05-01

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

Brain-mapping projects using the common marmoset.

PubMed

Okano, Hideyuki; Mitra, Partha

2015-04-01

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

Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs.

PubMed

Parisot, Sarah; Wells, William; Chemouny, Stéphane; Duffau, Hugues; Paragios, Nikos

2014-05-01

In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion. The two problems are coupled by relaxing the registration term in the tumor area, corresponding to areas of high classification score and high dissimilarity between volumes. In order to overcome the main shortcomings of discrete approaches regarding appropriate sampling of the solution space as well as important memory requirements, content driven samplings of the discrete displacement set and the sparse grid are considered, based on the local segmentation and registration uncertainties recovered by the min marginal energies. State of the art results on a substantial low-grade glioma database demonstrate the potential of our method, while our proposed approach shows maintained performance and strongly reduced complexity of the model. Copyright © 2014 Elsevier B.V. All rights reserved.

Particle Shape Effect on Macroscopic Behaviour of Underground Structures: Numerical and Experimental Study

NASA Astrophysics Data System (ADS)

Szarf, Krzysztof; Combe, Gael; Villard, Pascal

2015-02-01

The mechanical performance of underground flexible structures such as buried pipes or culverts made of plastics depend not only on the properties of the structure, but also on the material surrounding it. Flexible drains can deflect by 30% with the joints staying tight, or even invert. Large deformations of the structure are difficult to model in the framework of Finite Element Method, but straightforward in Discrete Element Methods. Moreover, Discrete Element approach is able to provide information about the grain-grain and grain-structure interactions at the microscale. This paper presents numerical and experimental investigations of flexible buried pipe behaviour with focus placed on load transfer above the buried structure. Numerical modeling was able to reproduce the experimental results. Load repartition was observed, being affected by a number of factors such as particle shape, pipe friction and pipe stiffness.

Small size yet big action: a simple sulfate anion templated a discrete 78-nuclearity silver sulfur nanocluster with a multishell structure.

PubMed

Cheng, Li-Ping; Wang, Zhi; Wu, Qiao-Yu; Su, Hai-Feng; Peng, Tao; Luo, Geng-Geng; Li, Yan-An; Sun, Di; Zheng, Lan-Sun

2018-03-07

A discrete 78-nucleus silver-sulfur nanocluster with a sulfate-centered multishell structure was isolated and characterized. Its crystal structure revealed 18 and 60 Ag atoms in the inner and outer shell, respectively. The inner shell of 18-nuclearity Ag atoms is a very rare convex polyhedron featuring an elongated triangular orthobicupola. The incorporation of a sulfate anion and multishell arrangement in the nanocluster led to a dramatic decrease in the band gap (E g = 1.40 eV). Our study showed that simple anions can also induce the formation of high-nuclearity silver clusters with excellent optical properties.

Structural correlates of subjective and objective memory performance in multiple sclerosis.

PubMed

Pardini, Matteo; Bergamino, Maurizio; Bommarito, Giulia; Bonzano, Laura; Luigi Mancardi, Gian; Roccatagliata, Luca

2014-04-01

Subjective and objective memory deficits represent a frequent and ill-understood aspect of multiple sclerosis (MS), and a significant cause of disability and quality of life reduction. The aim of the study is to verify the role of hippocampal and temporal associative fibers' damage in MS-related memory complaints. To reach this aim, 25 patients with low disability relapsing-remitting MS and 19 healthy controls were included in the study. All subjects underwent 3D T1 structural imaging and Diffusion Tensor Imaging. Additionally, MS patients underwent neuropsychological evaluation of objective (Selective Reminding Test and Spatial Recall Test) and of subjective (Perceived Deficit Questionnaire, Retrospective and Prospective Memory Subscales) memory deficits. Normalized hippocampal volume (NHV) and mean Fractional Anisotropy (FA) for the uncinate fasciculus (UF) and for the ventral division of the cingulum bundle (VCB) were calculated for all subjects. We showed that, compared to controls, MS subjects presented with reduced right NHV and with reduced mean FA bilaterally in the UF and the VCB. In the MS group, verbal memory scores correlated with left NHV, spatial memory scores correlated with right NHV, while perceived retrospective and prospective memory deficits correlated with left VCB and left UF mean FA respectively. Our data confirm an early involvement of memory-related brain structures in MS patients. Our data suggest that verbal and nonverbal memory as well as perceived retrospective and prospective memory deficits are related to alterations of discrete anatomical structures in the low-disability phase of MS. Copyright © 2013 Wiley Periodicals, Inc.

Cognitive Reserve and Brain Maintenance: Orthogonal Concepts in Theory and Practice.

PubMed

Habeck, C; Razlighi, Q; Gazes, Y; Barulli, D; Steffener, J; Stern, Y

2017-08-01

Cognitive Reserve and Brain Maintenance have traditionally been understood as complementary concepts: Brain Maintenance captures the processes underlying the structural preservation of the brain with age, and might be assessed relative to age-matched peers. Cognitive Reserve, on the other hand, refers to how cognitive processing can be performed regardless of how well brain structure has been maintained. Thus, Brain Maintenance concerns the "hardware," whereas Cognitive Reserve concerns "software," that is, brain functioning explained by factors beyond mere brain structure. We used structural brain data from 368 community-dwelling adults, age 20-80, to derive measures of Brain Maintenance and Cognitive Reserve. We found that Brain Maintenance and Cognitive were uncorrelated such that values on one measure did not imply anything about the other measure. Further, both measures were positively correlated with verbal intelligence and education, hinting at formative influences of the latter to both measures. We performed extensive split-half simulations to check our derived measures' statistical robustness. Our approach enables the out-of-sample quantification of Brain Maintenance and Cognitive Reserve for single subjects on the basis of chronological age, neuropsychological performance and structural brain measures. Future work will investigate the prognostic power of these measures with regard to future cognitive status. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

Determination of the density of surface states at the semiconductor-insulator interface in a metal-insulator-semiconductor structure

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

Gulyamov, G., E-mail: Gulyamov1949@rambler.ru; Sharibaev, N. U.

2011-02-15

The temporal dependence of thermal generation of electrons from occupied surface states at the semiconductor-insulator interface in a metal-insulator-semiconductor structure is studied. It is established that, at low temperatures, the derivative of the probability of depopulation of occupied surface states with respect to energy is represented by the Dirac {delta} function. It is shown that the density of states of a finite number of discrete energy levels under high-temperature measurements manifests itself as a continuous spectrum, whereas this spectrum appears discrete at low temperatures. A method for processing the continuous spectrum of the density of surface states is suggested thatmore » method makes it possible to determine the discrete energy spectrum. The obtained results may be conducive to an increase in resolution of the method of non-stationary spectroscopy of surface states.« less

A new discrete-element approach for the assessment of the seismic resistance of composite reinforced concrete-masonry buildings

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

Calio, I.; Cannizzaro, F.; Marletta, M.

2008-07-08

In the present study a new discrete-element approach for the evaluation of the seismic resistance of composite reinforced concrete-masonry structures is presented. In the proposed model, unreinforced masonry panels are modelled by means of two-dimensional discrete-elements, conceived by the authors for modelling masonry structures, whereas the reinforced concrete elements are modelled by lumped plasticity elements interacting with the masonry panels through nonlinear interface elements. The proposed procedure was adopted for the assessment of the seismic response of a case study confined-masonry building which was conceived to be a typical representative of a wide class of residential buildings designed to themore » requirements of the 1909 issue of the Italian seismic code and widely adopted in the aftermath of the 1908 earthquake for the reconstruction of the cities of Messina and Reggio Calabria.« less

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.

PubMed

Wei, Qinglai; Li, Benkai; Song, Ruizhuo

2018-04-01

In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.

A new discrete-element approach for the assessment of the seismic resistance of composite reinforced concrete-masonry buildings

NASA Astrophysics Data System (ADS)

Caliò, I.; Cannizzaro, F.; D'Amore, E.; Marletta, M.; Pantò, B.

2008-07-01

In the present study a new discrete-element approach for the evaluation of the seismic resistance of composite reinforced concrete-masonry structures is presented. In the proposed model, unreinforced masonry panels are modelled by means of two-dimensional discrete-elements, conceived by the authors for modelling masonry structures, whereas the reinforced concrete elements are modelled by lumped plasticity elements interacting with the masonry panels through nonlinear interface elements. The proposed procedure was adopted for the assessment of the seismic response of a case study confined-masonry building which was conceived to be a typical representative of a wide class of residential buildings designed to the requirements of the 1909 issue of the Italian seismic code and widely adopted in the aftermath of the 1908 earthquake for the reconstruction of the cities of Messina and Reggio Calabria.

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Discontinuous Galerkin method for coupled problems of compressible flow and elastic structures

NASA Astrophysics Data System (ADS)

Kosík, A.; Feistauer, M.; Hadrava, M.; Horáček, J.

2013-10-01

This paper is concerned with the numerical simulation of the interaction of 2D compressible viscous flow and an elastic structure. We consider the model of dynamical linear elasticity. Each individual problem is discretized in space by the discontinuous Galerkin method (DGM). For the time discretization we can use either the BDF (backward difference formula) method or also the DGM. The time dependence of the domain occupied by the fluid is given by the deformation of the elastic structure adjacent to the flow domain. It is treated with the aid of the Arbitrary Lagrangian-Eulerian (ALE) method. The fluid-structure interaction, given by transient conditions, is realized by an iterative process. The developed method is applied to the simulation of the biomechanical problem containing the onset of the voice production.

Ultra-fast analog-to-digital converter based on a nonlinear triplexer and an optical coder with a photonic crystal structure.

PubMed

Mehdizadeh, Farhad; Soroosh, Mohammad; Alipour-Banaei, Hamed; Farshidi, Ebrahim

2017-03-01

In this paper, we propose what we believe is a novel all-optical analog-to-digital converter (ADC) based on photonic crystals. The proposed structure is composed of a nonlinear triplexer and an optical coder. The nonlinear triplexer is for creating discrete levels in the continuous optical input signal, and the optical coder is for generating a 2-bit standard binary code out of the discrete levels coming from the nonlinear triplexer. Controlling the resonant mode of the resonant rings through optical intensity is the main objective and working mechanism of the proposed structure. The maximum delay time obtained for the proposed structure was about 5 ps and the total footprint is about 1520  μm².

TSPO Expression and Brain Structure in the Psychosis Spectrum.

PubMed

Hafizi, Sina; Guma, Elisa; Koppel, Alex; Da Silva, Tania; Kiang, Michael; Houle, Sylvain; Wilson, Alan A; Rusjan, Pablo M; Chakravarty, M Mallar; Mizrahi, Romina

2018-06-12

Psychosis is associated with abnormal structural changes in the brain including decreased regional brain volumes and abnormal brain morphology. However, the underlying causes of these structural abnormalities are less understood. The immune system, including microglial activation, has been implicated in the pathophysiology of psychosis. Although previous studies have suggested a connection between peripheral proinflammatory cytokines and structural brain abnormalities in schizophrenia, no in-vivo studies have investigated whether microglial activation is also linked to brain structure alterations previously observed in schizophrenia and its putative prodrome. In this study, we investigated the link between mitochondrial 18kDa translocator protein (TSPO) and structural brain characteristics (i.e. regional brain volume, cortical thickness, and hippocampal shape) in key brain regions such as dorsolateral prefrontal cortex and hippocampus of a large group of participants (N = 90) including individuals at clinical high risk (CHR) for psychosis, first-episode psychosis (mostly antipsychotic naïve) patients, and healthy volunteers. The participants underwent structural brain MRI scan and [ 18 F]FEPPA positron emission tomography (PET) targeting TSPO. A significant [ 18 F]FEPPA binding-by-group interaction was observed in morphological measures across the left hippocampus. In first-episode psychosis, we observed associations between [ 18 F]FEPPA V T (total volume of distribution) and outward and inward morphological alterations, respectively, in the dorsal and ventro-medial portions of the left hippocampus. These associations were not significant in CHR or healthy volunteers. There was no association between [ 18 F]FEPPA V T and other structural brain characteristics. Our findings suggest a link between TSPO expression and alterations in hippocampal morphology in first-episode psychosis. Copyright © 2018. Published by Elsevier Inc.

Discrete space charge affected field emission: Flat and hemisphere emitters

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

Jensen, Kevin L., E-mail: kevin.jensen@nrl.navy.mil; Shiffler, Donald A.; Tang, Wilkin

Models of space-charge affected thermal-field emission from protrusions, able to incorporate the effects of both surface roughness and elongated field emitter structures in beam optics codes, are desirable but difficult. The models proposed here treat the meso-scale diode region separate from the micro-scale regions characteristic of the emission sites. The consequences of discrete emission events are given for both one-dimensional (sheets of charge) and three dimensional (rings of charge) models: in the former, results converge to steady state conditions found by theory (e.g., Rokhlenko et al. [J. Appl. Phys. 107, 014904 (2010)]) but show oscillatory structure as they do. Surfacemore » roughness or geometric features are handled using a ring of charge model, from which the image charges are found and used to modify the apex field and emitted current. The roughness model is shown to have additional constraints related to the discrete nature of electron charge. The ability of a unit cell model to treat field emitter structures and incorporate surface roughness effects inside a beam optics code is assessed.« less

Non-local currents and the structure of eigenstates in planar discrete systems with local symmetries

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

Röntgen, M., E-mail: mroentge@physnet.uni-hamburg.de; Morfonios, C.V., E-mail: christian.morfonios@physnet.uni-hamburg.de; Diakonos, F.K., E-mail: fdiakono@phys.uoa.gr

Local symmetries are spatial symmetries present in a subdomain of a complex system. By using and extending a framework of so-called non-local currents that has been established recently, we show that one can gain knowledge about the structure of eigenstates in locally symmetric setups through a Kirchhoff-type law for the non-local currents. The framework is applicable to all discrete planar Schrödinger setups, including those with non-uniform connectivity. Conditions for spatially constant non-local currents are derived and we explore two types of locally symmetric subsystems in detail, closed-loops and one-dimensional open ended chains. We find these systems to support locally similarmore » or even locally symmetric eigenstates. - Highlights: • We extend the framework of non-local currents to discrete planar systems. • Structural information about the eigenstates is gained. • Conditions for the constancy of non-local currents are derived. • We use the framework to design two types of example systems featuring locally symmetric eigenstates.« less

Transcripts with in silico predicted RNA structure are enriched everywhere in the mouse brain

PubMed Central

2012-01-01

Background Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts. Results By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3’ UTR structures and correlated expression patterns. Conclusions Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function. PMID:22651826

Structural Design Methodology Based on Concepts of Uncertainty

NASA Technical Reports Server (NTRS)

Lin, K. Y.; Du, Jiaji; Rusk, David

2000-01-01

In this report, an approach to damage-tolerant aircraft structural design is proposed based on the concept of an equivalent "Level of Safety" that incorporates past service experience in the design of new structures. The discrete "Level of Safety" for a single inspection event is defined as the compliment of the probability that a single flaw size larger than the critical flaw size for residual strength of the structure exists, and that the flaw will not be detected. The cumulative "Level of Safety" for the entire structure is the product of the discrete "Level of Safety" values for each flaw of each damage type present at each location in the structure. Based on the definition of "Level of Safety", a design procedure was identified and demonstrated on a composite sandwich panel for various damage types, with results showing the sensitivity of the structural sizing parameters to the relative safety of the design. The "Level of Safety" approach has broad potential application to damage-tolerant aircraft structural design with uncertainty.

DSSPcont: continuous secondary structure assignments for proteins

PubMed Central

Carter, Phil; Andersen, Claus A. F.; Rost, Burkhard

2003-01-01

The DSSP program automatically assigns the secondary structure for each residue from the three-dimensional co-ordinates of a protein structure to one of eight states. However, discrete assignments are incomplete in that they cannot capture the continuum of thermal fluctuations. Therefore, DSSPcont (http://cubic.bioc.columbia.edu/services/DSSPcont) introduces a continuous assignment of secondary structure that replaces ‘static’ by ‘dynamic’ states. Technically, the continuum results from calculating weighted averages over 10 discrete DSSP assignments with different hydrogen bond thresholds. A DSSPcont assignment for a particular residue is a percentage likelihood of eight secondary structure states, derived from a weighted average of the ten DSSP assignments. The continuous assignments have two important features: (i) they reflect the structural variations due to thermal fluctuations as detected by NMR spectroscopy; and (ii) they reproduce the structural variation between many NMR models from one single model. Therefore, functionally important variation can be extracted from a single X-ray structure using the continuous assignment procedure. PMID:12824310

Brain Structure and Executive Functions in Children with Cerebral Palsy: A Systematic Review

ERIC Educational Resources Information Center

Weierink, Lonneke; Vermeulen, R. Jeroen; Boyd, Roslyn N.

2013-01-01

This systematic review aimed to establish the current knowledge about brain structure and executive function (EF) in children with cerebral palsy (CP). Five databases were searched (up till July 2012). Six articles met the inclusion criteria, all included structural brain imaging though no functional brain imaging. Study quality was assessed using…

Total Intravenous Anesthesia Including Ketamine versus Volatile Gas Anesthesia for Combat-related Operative Traumatic Brain Injury

DTIC Science & Technology

2008-07-01

receiving VGA with regard to Injury Severity Score, Glasgow Coma Scale score, base deficit, Head Abbreviated Injury Score, and craniectomy or craniotomy ...1, 2, or 3. Craniectomy or craniotomy was performed at the discretion of the neurosurgeon based on type of skull injury, severity of injury, and...perfectly on GCS ( 8, 8), base deficit ( 6, 6), Head Abbreviated Injury Score ( 3, 3) and craniectomy versus craniotomy . From these, subsets

Incorporation of monodisperse oligoethyleneglycol amino acids into anticonvulsant analogues of galanin and neuropeptide y provides peripherally acting analgesics.

PubMed

Zhang, Liuyin; Klein, Brian D; Metcalf, Cameron S; Smith, Misty D; McDougle, Daniel R; Lee, Hee-Kyoung; White, H Steve; Bulaj, Grzegorz

2013-02-04

Delivery of neuropeptides into the central and/or peripheral nervous systems supports development of novel neurotherapeutics for the treatment of pain, epilepsy and other neurological diseases. Our previous work showed that the combination of lipidization and cationization applied to anticonvulsant neuropeptides galanin (GAL) and neuropeptide Y (NPY) improved their penetration across the blood-brain barrier yielding potent antiepileptic lead compounds, such as Gal-B2 (NAX 5055) or NPY-B2. To dissect peripheral and central actions of anticonvulsant neuropeptides, we rationally designed, synthesized and characterized GAL and NPY analogues containing monodisperse (discrete) oligoethyleneglycol-lysine (dPEG-Lys). The dPEGylated analogues Gal-B2-dPEG(24), Gal-R2-dPEG(24) and NPY-dPEG(24) displayed analgesic activities following systemic administration, while avoiding penetration into the brain. Gal-B2-dPEG(24) was synthesized by a stepwise deprotection of orthogonal 4-methoxytrityl and allyloxycarbonyl groups, and subsequent on-resin conjugations of dPEG(24) and palmitic acids, respectively. All the dPEGylated analogues exhibited substantially decreased hydrophobicity (expressed as logD values), increased in vitro serum stabilities and pronounced analgesia in the formalin and carrageenan inflammatory pain assays following systemic administration, while lacking apparent antiseizure activities. These results suggest that discrete PEGylation of neuropeptides offers an attractive strategy for developing neurotherapeutics with restricted penetration into the central nervous system.

Insights into Brain Glycogen Metabolism

PubMed Central

Mathieu, Cécile; de la Sierra-Gallay, Ines Li; Duval, Romain; Xu, Ximing; Cocaign, Angélique; Léger, Thibaut; Woffendin, Gary; Camadro, Jean-Michel; Etchebest, Catherine; Haouz, Ahmed; Dupret, Jean-Marie; Rodrigues-Lima, Fernando

2016-01-01

Brain glycogen metabolism plays a critical role in major brain functions such as learning or memory consolidation. However, alteration of glycogen metabolism and glycogen accumulation in the brain contributes to neurodegeneration as observed in Lafora disease. Glycogen phosphorylase (GP), a key enzyme in glycogen metabolism, catalyzes the rate-limiting step of glycogen mobilization. Moreover, the allosteric regulation of the three GP isozymes (muscle, liver, and brain) by metabolites and phosphorylation, in response to hormonal signaling, fine-tunes glycogenolysis to fulfill energetic and metabolic requirements. Whereas the structures of muscle and liver GPs have been known for decades, the structure of brain GP (bGP) has remained elusive despite its critical role in brain glycogen metabolism. Here, we report the crystal structure of human bGP in complex with PEG 400 (2.5 Å) and in complex with its allosteric activator AMP (3.4 Å). These structures demonstrate that bGP has a closer structural relationship with muscle GP, which is also activated by AMP, contrary to liver GP, which is not. Importantly, despite the structural similarities between human bGP and the two other mammalian isozymes, the bGP structures reveal molecular features unique to the brain isozyme that provide a deeper understanding of the differences in the activation properties of these allosteric enzymes by the allosteric effector AMP. Overall, our study further supports that the distinct structural and regulatory properties of GP isozymes contribute to the different functions of muscle, liver, and brain glycogen. PMID:27402852

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

PubMed

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

2013-01-01

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

Segmentation of brain structures in presence of a space-occupying lesion.

PubMed

Pollo, Claudio; Cuadra, Meritxell Bach; Cuisenaire, Olivier; Villemure, Jean-Guy; Thiran, Jean-Philippe

2005-02-15

Brain deformations induced by space-occupying lesions may result in unpredictable position and shape of functionally important brain structures. The aim of this study is to propose a method for segmentation of brain structures by deformation of a segmented brain atlas in presence of a space-occupying lesion. Our approach is based on an a priori model of lesion growth (MLG) that assumes radial expansion from a seeding point and involves three steps: first, an affine registration bringing the atlas and the patient into global correspondence; then, the seeding of a synthetic tumor into the brain atlas providing a template for the lesion; finally, the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. The method was applied on two meningiomas inducing a pure displacement of the underlying brain structures, and segmentation accuracy of ventricles and basal ganglia was assessed. Results show that the segmented structures were consistent with the patient's anatomy and that the deformation accuracy of surrounding brain structures was highly dependent on the accurate placement of the tumor seeding point. Further improvements of the method will optimize the segmentation accuracy. Visualization of brain structures provides useful information for therapeutic consideration of space-occupying lesions, including surgical, radiosurgical, and radiotherapeutic planning, in order to increase treatment efficiency and prevent neurological damage.

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?

A Bell-Curved Based Algorithm for Mixed Continuous and Discrete Structural Optimization

NASA Technical Reports Server (NTRS)

Kincaid, Rex K.; Weber, Michael; Sobieszczanski-Sobieski, Jaroslaw

2001-01-01

An evolutionary based strategy utilizing two normal distributions to generate children is developed to solve mixed integer nonlinear programming problems. This Bell-Curve Based (BCB) evolutionary algorithm is similar in spirit to (mu + mu) evolutionary strategies and evolutionary programs but with fewer parameters to adjust and no mechanism for self adaptation. First, a new version of BCB to solve purely discrete optimization problems is described and its performance tested against a tabu search code for an actuator placement problem. Next, the performance of a combined version of discrete and continuous BCB is tested on 2-dimensional shape problems and on a minimum weight hub design problem. In the latter case the discrete portion is the choice of the underlying beam shape (I, triangular, circular, rectangular, or U).

Stabilisation of discrete-time polynomial fuzzy systems via a polynomial lyapunov approach

NASA Astrophysics Data System (ADS)

Nasiri, Alireza; Nguang, Sing Kiong; Swain, Akshya; Almakhles, Dhafer

2018-02-01

This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control design methods for discrete-time fuzzy polynomial systems cannot guarantee their Lyapunov function to be a radially unbounded polynomial function, hence the global stability cannot be assured. The proposed control design in this paper guarantees a radially unbounded polynomial Lyapunov functions which ensures global stability. In the proposed design, state feedback structure is considered and non-convexity problem is solved by incorporating an integrator into the controller. Sufficient conditions of stability are derived in terms of polynomial matrix inequalities which are solved via SOSTOOLS in MATLAB. A numerical example is presented to illustrate the effectiveness of the proposed controller.

A structure-preserving split finite element discretization of the split 1D linear shallow-water equations

NASA Astrophysics Data System (ADS)

Bauer, Werner; Behrens, Jörn

2017-04-01

We present a locally conservative, low-order finite element (FE) discretization of the covariant 1D linear shallow-water equations written in split form (cf. tet{[1]}). The introduction of additional differential forms (DF) that build pairs with the original ones permits a splitting of these equations into topological momentum and continuity equations and metric-dependent closure equations that apply the Hodge-star. Our novel discretization framework conserves this geometrical structure, in particular it provides for all DFs proper FE spaces such that the differential operators (here gradient and divergence) hold in strong form. The discrete topological equations simply follow by trivial projections onto piecewise constant FE spaces without need to partially integrate. The discrete Hodge-stars operators, representing the discretized metric equations, are realized by nontrivial Galerkin projections (GP). Here they follow by projections onto either a piecewise constant (GP0) or a piecewise linear (GP1) space. Our framework thus provides essentially three different schemes with significantly different behavior. The split scheme using twice GP1 is unstable and shares the same discrete dispersion relation and similar second-order convergence rates as the conventional P1-P1 FE scheme that approximates both velocity and height variables by piecewise linear spaces. The split scheme that applies both GP1 and GP0 is stable and shares the dispersion relation of the conventional P1-P0 FE scheme that approximates the velocity by a piecewise linear and the height by a piecewise constant space with corresponding second- and first-order convergence rates. Exhibiting for both velocity and height fields second-order convergence rates, we might consider the split GP1-GP0 scheme though as stable versions of the conventional P1-P1 FE scheme. For the split scheme applying twice GP0, we are not aware of a corresponding conventional formulation to compare with. Though exhibiting larger absolute error values, it shows similar convergence rates as the other split schemes, but does not provide a satisfactory approximation of the dispersion relation as short waves are propagated much to fast. Despite this, the finding of this new scheme illustrates the potential of our discretization framework as a toolbox to find and to study new FE schemes based on new combinations of FE spaces. [1] Bauer, W. [2016], A new hierarchically-structured n-dimensional covariant form of rotating equations of geophysical fluid dynamics, GEM - International Journal on Geomathematics, 7(1), 31-101.

Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items

ERIC Educational Resources Information Center

Lu, Irene R. R.; Thomas, D. Roland

2008-01-01

This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…

Discrete-time infinity control problem with measurement feedback

NASA Technical Reports Server (NTRS)

Stoorvogel, A. A.; Saberi, A.; Chen, B. M.

1992-01-01

The paper is concerned with the discrete-time H(sub infinity) control problem with measurement feedback. The authors extend previous results by having weaker assumptions on the system parameters. The authors also show explicitly the structure of H(sub infinity) controllers. Finally, they show that it is in certain cases possible, without loss of performance, to reduce the dynamical order of the controllers.

47 CFR 25.252 - Special requirements for ancillary terrestrial components operating in the 2000-2020 MHz/2180...

Code of Federal Regulations, 2011 CFR

2011-10-01

... MHz. (3) Exceed an EIRP toward the physical horizon (not to include man-made structures) of 25.5 dBW... active transmission interval, of discrete out-of-band emissions of less than 700 Hz bandwidth from such... EIRP, measured over any two-millisecond active transmission interval, of discrete out-of-band emissions...

47 CFR 25.252 - Special requirements for ancillary terrestrial components operating in the 2000-2020 MHz/2180...

Code of Federal Regulations, 2010 CFR

2010-10-01

... MHz. (3) Exceed an EIRP toward the physical horizon (not to include man-made structures) of 25.5 dBW... active transmission interval, of discrete out-of-band emissions of less than 700 Hz bandwidth from such... EIRP, measured over any two-millisecond active transmission interval, of discrete out-of-band emissions...

47 CFR 25.252 - Special requirements for ancillary terrestrial components operating in the 2000-2020 MHz/2180...

Code of Federal Regulations, 2012 CFR

2012-10-01

... MHz. (3) Exceed an EIRP toward the physical horizon (not to include man-made structures) of 25.5 dBW... active transmission interval, of discrete out-of-band emissions of less than 700 Hz bandwidth from such... EIRP, measured over any two-millisecond active transmission interval, of discrete out-of-band emissions...

Why language really is not a communication system: a cognitive view of language evolution

PubMed Central

Reboul, Anne C.

2015-01-01

While most evolutionary scenarios for language see it as a communication system with consequences on the language-ready brain, there are major difficulties for such a view. First, language has a core combination of features—semanticity, discrete infinity, and decoupling—that makes it unique among communication systems and that raise deep problems for the view that it evolved for communication. Second, extant models of communication systems—the code model of communication (Millikan, 2005) and the ostensive model of communication (Scott-Phillips, 2015) cannot account for language evolution. I propose an alternative view, according to which language first evolved as a cognitive tool, following Fodor’s (1975, 2008) Language of Thought Hypothesis, and was then exapted (externalized) for communication. On this view, a language-ready brain is a brain profoundly reorganized in terms of connectivity, allowing the human conceptual system to emerge, triggering the emergence of syntax. Language as used in communication inherited its core combination of features from the Language of Thought. PMID:26441802

Assessment of Cognitive Function in the Water Maze Task: Maximizing Data Collection and Analysis in Animal Models of Brain Injury.

PubMed

Whiting, Mark D; Kokiko-Cochran, Olga N

2016-01-01

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

Microglial brain region-dependent diversity and selective regional sensitivities to ageing

PubMed Central

Grabert, Kathleen; Michoel, Tom; Karavolos, Michail H; Clohisey, Sara; Baillie, J Kenneth; Stevens, Mark P; Freeman, Tom C; Summers, Kim M; McColl, Barry W

2015-01-01

Microglia play critical roles in neural development, homeostasis and neuroinflammation and are increasingly implicated in age-related neurological dysfunction. Neurodegeneration often occurs in disease-specific spatially-restricted patterns, the origins of which are unknown. We performed the first genome-wide analysis of microglia from discrete brain regions across the adult lifespan of the mouse and reveal that microglia have distinct region-dependent transcriptional identities and age in a regionally variable manner. In the young adult brain, differences in bioenergetic and immunoregulatory pathways were the major sources of heterogeneity and suggested that cerebellar and hippocampal microglia exist in a more immune vigilant state. Immune function correlated with regional transcriptional patterns. Augmentation of the distinct cerebellar immunophenotype and a contrasting loss in distinction of the hippocampal phenotype among forebrain regions were key features during ageing. Microglial diversity may enable regionally localised homeostatic functions but could also underlie region-specific sensitivities to microglial dysregulation and involvement in age-related neurodegeneration. PMID:26780511

Enzyme-linked DNA dendrimer nanosensors for acetylcholine

PubMed Central

Walsh, Ryan; Morales, Jennifer M.; Skipwith, Christopher G.; Ruckh, Timothy T.; Clark, Heather A.

2015-01-01

It is currently difficult to measure small dynamics of molecules in the brain with high spatial and temporal resolution while connecting them to the bigger picture of brain function. A step towards understanding the underlying neural networks of the brain is the ability to sense discrete changes of acetylcholine within a synapse. Here we show an efficient method for generating acetylcholine-detecting nanosensors based on DNA dendrimer scaffolds that incorporate butyrylcholinesterase and fluorescein in a nanoscale arrangement. These nanosensors are selective for acetylcholine and reversibly respond to levels of acetylcholine in the neurophysiological range. This DNA dendrimer architecture has the potential to overcome current obstacles to sensing in the synaptic environment, including the nanoscale size constraints of the synapse and the ability to quantify the spatio-temporal fluctuations of neurotransmitter release. By combining the control of nanosensor architecture with the strategic placement of fluorescent reporters and enzymes, this novel nanosensor platform can facilitate the development of new selective imaging tools for neuroscience. PMID:26442999

Enzyme-linked DNA dendrimer nanosensors for acetylcholine.

PubMed

Walsh, Ryan; Morales, Jennifer M; Skipwith, Christopher G; Ruckh, Timothy T; Clark, Heather A

2015-10-07

It is currently difficult to measure small dynamics of molecules in the brain with high spatial and temporal resolution while connecting them to the bigger picture of brain function. A step towards understanding the underlying neural networks of the brain is the ability to sense discrete changes of acetylcholine within a synapse. Here we show an efficient method for generating acetylcholine-detecting nanosensors based on DNA dendrimer scaffolds that incorporate butyrylcholinesterase and fluorescein in a nanoscale arrangement. These nanosensors are selective for acetylcholine and reversibly respond to levels of acetylcholine in the neurophysiological range. This DNA dendrimer architecture has the potential to overcome current obstacles to sensing in the synaptic environment, including the nanoscale size constraints of the synapse and the ability to quantify the spatio-temporal fluctuations of neurotransmitter release. By combining the control of nanosensor architecture with the strategic placement of fluorescent reporters and enzymes, this novel nanosensor platform can facilitate the development of new selective imaging tools for neuroscience.

Enzyme-linked DNA dendrimer nanosensors for acetylcholine

NASA Astrophysics Data System (ADS)

Walsh, Ryan; Morales, Jennifer M.; Skipwith, Christopher G.; Ruckh, Timothy T.; Clark, Heather A.

2015-10-01

It is currently difficult to measure small dynamics of molecules in the brain with high spatial and temporal resolution while connecting them to the bigger picture of brain function. A step towards understanding the underlying neural networks of the brain is the ability to sense discrete changes of acetylcholine within a synapse. Here we show an efficient method for generating acetylcholine-detecting nanosensors based on DNA dendrimer scaffolds that incorporate butyrylcholinesterase and fluorescein in a nanoscale arrangement. These nanosensors are selective for acetylcholine and reversibly respond to levels of acetylcholine in the neurophysiological range. This DNA dendrimer architecture has the potential to overcome current obstacles to sensing in the synaptic environment, including the nanoscale size constraints of the synapse and the ability to quantify the spatio-temporal fluctuations of neurotransmitter release. By combining the control of nanosensor architecture with the strategic placement of fluorescent reporters and enzymes, this novel nanosensor platform can facilitate the development of new selective imaging tools for neuroscience.

Hierarchical nonlinear dynamics of human attention.

PubMed

Rabinovich, Mikhail I; Tristan, Irma; Varona, Pablo

2015-08-01

Attention is the process of focusing mental resources on a specific cognitive/behavioral task. Such brain dynamics involves different partially overlapping brain functional networks whose interconnections change in time according to the performance stage, and can be stimulus-driven or induced by an intrinsically generated goal. The corresponding activity can be described by different families of spatiotemporal discrete patterns or sequential dynamic modes. Since mental resources are finite, attention modalities compete with each other at all levels of the hierarchy, from perception to decision making and behavior. Cognitive activity is a dynamical process and attention possesses some universal dynamical characteristics. Thus, it is time to apply nonlinear dynamical theory for the description and prediction of hierarchical attentional tasks. Such theory has to include the analyses of attentional control stability, the time cost of attention switching, the finite capacity of informational resources in the brain, and the normal and pathological bifurcations of attention sequential dynamics. In this paper we have integrated today's knowledge, models and results in these directions. Copyright © 2015 Elsevier Ltd. All rights reserved.

A case of the corpus callosum and alien hand syndrome from a discrete paracallosal lesion.

PubMed

Faber, Raymond; Azad, Alvi; Reinsvold, Richard

2010-08-01

Here we present a patient with an isolated paracallosal brain lesion who exhibited behavioral changes associated with the corpus callosum syndrome (CCS) including features of the alien hand syndrome (AHS). The CCS is also known as the split-brain syndrome, the syndrome of hemisphere disconnection, the syndrome of brain bisection and the syndrome of the cerebral commissures. Because most reported cases of CCS were caused by tumors which extended beyond the corpus callosum (CC) and did not always induce a complete disconnection, there was much controversy about the role of the CC and the existence of a specific CCS. Aside from surgically based cases, the full complement of the CCS is infrequently clinically encountered. The patient described has a classic CCS from natural causes. This case report is unique in exhibiting a complete CCS with AHS secondary to an ischemic event affecting the left pericallosal region. To our knowledge this is the first case report of such a combination.

Early life linguistic ability, late life cognitive function, and neuropathology: findings from the Nun Study.

PubMed

Riley, Kathryn P; Snowdon, David A; Desrosiers, Mark F; Markesbery, William R

2005-03-01

The relationships between early life variables, cognitive function, and neuropathology were examined in participants in the Nun Study who were between the ages of 75 and 95. Our early life variable was idea density, which is a measure of linguistic ability, derived from autobiographies written at a mean age of 22 years. Six discrete categories of cognitive function, including mild cognitive impairments, were evaluated, using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery of cognitive tests. Neuropathologic data included Braak staging, neurofibrillary tangle and senile plaque counts, brain weight, degree of cerebral atrophy, severity of atherosclerosis, and the presence of brain infarcts. Early-life idea density was significantly related to the categories of late-life cognitive function, including mild cognitive impairments: low idea density was associated with greater impairment. Low idea density also was significantly associated with lower brain weight, higher degree of cerebral atrophy, more severe neurofibrillary pathology, and the likelihood of meeting neuropathologic criteria for Alzheimer's disease.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

PubMed

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Functional brain networks reconstruction using group sparsity-regularized learning.

PubMed

Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming

2018-06-01

Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.

Biophysical Characterisation of Neuroglobin of the Icefish, a Natural Knockout for Hemoglobin and Myoglobin. Comparison with Human Neuroglobin

PubMed Central

Giordano, Daniela; Boron, Ignacio; Abbruzzetti, Stefania; Van Leuven, Wendy; Nicoletti, Francesco P.; Forti, Flavio; Bruno, Stefano; Cheng, C-H. Christina; Moens, Luc; di Prisco, Guido; Nadra, Alejandro D.; Estrin, Darío; Smulevich, Giulietta; Dewilde, Sylvia; Viappiani, Cristiano; Verde, Cinzia

2012-01-01

The Antarctic icefish Chaenocephalus aceratus lacks the globins common to most vertebrates, hemoglobin and myoglobin, but has retained neuroglobin in the brain. This conserved globin has been cloned, over-expressed and purified. To highlight similarities and differences, the structural features of the neuroglobin of this colourless-blooded fish were compared with those of the well characterised human neuroglobin as well as with the neuroglobin from the retina of the red blooded, hemoglobin and myoglobin-containing, closely related Antarctic notothenioid Dissostichus mawsoni. A detailed structural and functional analysis of the two Antarctic fish neuroglobins was carried out by UV-visible and Resonance Raman spectroscopies, molecular dynamics simulations and laser-flash photolysis. Similar to the human protein, Antarctic fish neuroglobins can reversibly bind oxygen and CO in the Fe2+ form, and show six-coordination by distal His in the absence of exogenous ligands. A very large and structured internal cavity, with discrete docking sites, was identified in the modelled three-dimensional structures of the Antarctic neuroglobins. Estimate of the free-energy barriers from laser-flash photolysis and Implicit Ligand Sampling showed that the cavities are accessible from the solvent in both proteins. Comparison of structural and functional properties suggests that the two Antarctic fish neuroglobins most likely preserved and possibly improved the function recently proposed for human neuroglobin in ligand multichemistry. Despite subtle differences, the adaptation of Antarctic fish neuroglobins does not seem to parallel the dramatic adaptation of the oxygen carrying globins, hemoglobin and myoglobin, in the same organisms. PMID:23226490

Beyond sex differences: new approaches for thinking about variation in brain structure and function

PubMed Central

Joel, Daphna; Fausto-Sterling, Anne

2016-01-01

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. PMID:26833844

MR Anatomy of Deep Brain Nuclei with Special Reference to Specific Diseases and Deep Brain Stimulation Localization

PubMed Central

Telford, Ryan; Vattoth, Surjith

2014-01-01

Summary Diseases affecting the basal ganglia and deep brain structures vary widely in etiology and include metabolic, infectious, ischemic, and neurodegenerative conditions. Some neurologic diseases, such as Wernicke encephalopathy or pseudohypoparathyroidism, require specific treatments, which if unrecognized could lead to further complications. Other pathologies, such as hypertrophic olivary degeneration, if not properly diagnosed may be mistaken for a primary medullary neoplasm and create unnecessary concern. The deep brain structures are complex and can be difficult to distinguish on routine imaging. It is imperative that radiologists first understand the intrinsic anatomic relationships between the different basal ganglia nuclei and deep brain structures with magnetic resonance (MR) imaging. It is important to understand the "normal" MR signal characteristics, locations, and appearances of these structures. This is essential to recognizing diseases affecting the basal ganglia and deep brain structures, especially since most of these diseases result in symmetrical, and therefore less noticeable, abnormalities. It is also crucial that neurosurgeons correctly identify the deep brain nuclei presurgically for positioning deep brain stimulator leads, the most important being the subthalamic nucleus for Parkinson syndromes and the thalamic ventral intermediate nucleus for essential tremor. Radiologists will be able to better assist clinicians in diagnosis and treatment once they are able to accurately localize specific deep brain structures. PMID:24571832

A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback

NASA Technical Reports Server (NTRS)

Gwaltney, David A.; Dutton, Kenneth

2005-01-01

The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described.

Cerebral localization, then and now.

PubMed

Marshall, John C; Fink, Gereon R

2003-11-01

We review some of the progress made in understanding the nature of functional specialization in the human brain, beginning with the anatomical claim that all mental faculties have their own distinct material substrate in different regions of the brain and the psychological claim that each mental faculty is characterized by the content domain with which it deals. This conceptual framework led behavioral neurologists to show how discrete brain lesions provoked different types of language, praxic, gnostic, spatial, and memory disorders. The simplest way of interpreting these anatomoclinical associations was to conjecture that the normal function (now impaired by brain damage) was localized within that lesioned region. It was also realized that cognitive impairments could arise from lesions that spared the functional centers themselves but disconnected them from other centers. Nonetheless, many neuroscientists remained skeptical of the entire paradigm. Accordingly, in the late 19th century functional localization began to be studied in the intact human brain by such techniques as measuring the temperature of different brain regions when different cognitive tasks were performed. During the 20th century these crude techniques gave way to positron emission tomography, functional magnetic resonance imaging, and magnetoencephalography. The relatively precise spatial and temporal resolution of modern methods now raises a crucial question: Do the functional localizations obtained by the anatomoclinical method converge with those implied by the functional neuroimaging of cognition in healthy volunteers? We then conclude with some recent suggestions that functional specialization is not such a fixed property of brain regions as previously supposed.

Comparison of histamine and hyperosmotic arabinose infusion on brain capillary permeability to hydrophilic solutes

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

Lucchesi, K.J.

1986-03-01

The effect of bilateral intracarotid infusion of histamine (HA) on capillary permeability-surface area products (PS) of two metabolically inert tracers was determined and compared to that of L(+)arabinose (ARAB) in rat brain. Ringer's solution alone, or with 1 mg/kg HA diphosphate or 1.6M ARAB added, was infused (0.9 ml over 0.5 min) into each external carotid artery (CA). Five minutes later, a bolus of /sup 14/C-sucrose and /sup 3/H-L-glucose was injected i.v. Estimates of PS for both tracers were computed by the method of Ohno et al after brain concentration was corrected for tracer within cerebral blood vessels. Brain bloodmore » volume, based on the /sup 14/C-dextran space, was the same (.016 ml/g) in discrete cortical and midbrain regions of all rats except those treated with ARAB. The latter yielded .033 ml/g, presumably due to dextran extravasation. Infusion of ARAB, HA and Ringer's increased the PS's of sucrose and L-glucose by 10x, 8x, and 3x in brain regions perfused by the internal CA's. The ratio, PS-sucrose/PS-L-glucose was unchanged by any treatment. Both ARAB and HA caused transient falls in arterial pressure, but only ARAB caused deaths (3 of 9 rats). While as effective as ARAB in opening the blood-brain barrier, HA may be safer than hyperosmotic shock to enhance delivery of chemotherapeutic agents to brain tumors.« less

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

14 CFR 29.573 - Damage Tolerance and Fatigue Evaluation of Composite Rotorcraft Structures.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Composite Rotorcraft Structures. 29.573 Section 29.573 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Structures. (a) Each applicant must evaluate the composite rotorcraft structure under the damage tolerance..., types, and sizes of damage, considering fatigue, environmental effects, intrinsic and discrete flaws...

14 CFR 27.573 - Damage Tolerance and Fatigue Evaluation of Composite Rotorcraft Structures.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Composite Rotorcraft Structures. 27.573 Section 27.573 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Structures. (a) Each applicant must evaluate the composite rotorcraft structure under the damage tolerance..., types, and sizes of damage, considering fatigue, environmental effects, intrinsic and discrete flaws...

14 CFR 27.573 - Damage Tolerance and Fatigue Evaluation of Composite Rotorcraft Structures.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Composite Rotorcraft Structures. 27.573 Section 27.573 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Structures. (a) Each applicant must evaluate the composite rotorcraft structure under the damage tolerance..., types, and sizes of damage, considering fatigue, environmental effects, intrinsic and discrete flaws...

14 CFR 29.573 - Damage Tolerance and Fatigue Evaluation of Composite Rotorcraft Structures.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Composite Rotorcraft Structures. 29.573 Section 29.573 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Structures. (a) Each applicant must evaluate the composite rotorcraft structure under the damage tolerance..., types, and sizes of damage, considering fatigue, environmental effects, intrinsic and discrete flaws...

14 CFR 27.573 - Damage Tolerance and Fatigue Evaluation of Composite Rotorcraft Structures.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Composite Rotorcraft Structures. 27.573 Section 27.573 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Structures. (a) Each applicant must evaluate the composite rotorcraft structure under the damage tolerance..., types, and sizes of damage, considering fatigue, environmental effects, intrinsic and discrete flaws...

14 CFR 29.573 - Damage Tolerance and Fatigue Evaluation of Composite Rotorcraft Structures.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Composite Rotorcraft Structures. 29.573 Section 29.573 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... Structures. (a) Each applicant must evaluate the composite rotorcraft structure under the damage tolerance..., types, and sizes of damage, considering fatigue, environmental effects, intrinsic and discrete flaws...

Effect of chronic exposure to aspartame on oxidative stress in the brain of albino rats.

PubMed

Iyyaswamy, Ashok; Rathinasamy, Sheeladevi

2012-09-01

This study was aimed at investigating the chronic effect of the artificial sweetener aspartame on oxidative stress in brain regions of Wistar strain albino rats. Many controversial reports are available on the use of aspartame as it releases methanol as one of its metabolite during metabolism. The present study proposed to investigate whether chronic aspartame (75 mg/kg) administration could release methanol and induce oxidative stress in the rat brain. To mimic the human methanol metabolism, methotrexate (MTX)-treated rats were included to study the aspartame effects. Wistar strain male albino rats were administered with aspartame orally and studied along with controls and MTX-treated controls. The blood methanol level was estimated, the animal was sacrificed and the free radical changes were observed in brain discrete regions by assessing the scavenging enzymes, reduced glutathione, lipid peroxidation (LPO) and protein thiol levels. It was observed that there was a significant increase in LPO levels, superoxide dismutase (SOD) activity, GPx levels and CAT activity with a significant decrease in GSH and protein thiol. Moreover, the increases in some of these enzymes were region specific. Chronic exposure of aspartame resulted in detectable methanol in blood. Methanol per se and its metabolites may be responsible for the generation of oxidative stress in brain regions.

O-GlcNAc modification of radial glial vimentin filaments in the developing chick brain.

PubMed

Farach, Andrew M; Galileo, Deni S

2008-12-01

We examined the post-translational modification of intracellular proteins by beta-O-linked N-acetylglucosamine (O-GlcNAc) with regard to neurofilament phosphorylation in the developing chick optic tectum. A regulated developmental pattern of O-GlcNAcylation was discovered in the developing brain. Most notably, discernible staining occurs along radial glial filaments but not along neuronal filaments in vivo. Immunohistochemical analyses in sections of progressive stages of development suggest upregulation of O-GlcNAc in the ependyma, tectofugal neuron bodies, and radial glial processes, but not in axons. In contrast, double-label immunostaining of monolayer cultures made from dissociated embryonic day (E) 7 optic tecta revealed O-GlcNAcylation of most axons. Labeling of brain sections together with Western blot analyses showed O-GlcNAc modification of a few discrete proteins throughout development, and suggested vimentin as the protein in radial glia. Immunoprecipitation of vimentin from E9 whole brain lysates confirmed O-GlcNAcylation of vimentin in development. These results indicate a regulated pattern of O-GlcNAc modification of vimentin filaments, which in turn suggests a role for O-GlcNAc-modified intermediate filaments in radial glia, but not in neurons during brain development. The control mechanisms that regulate this pattern in vivo, however, are disrupted when cells are placed in vitro.

Structural and Machine Design Using Piezoceramic Materials: A Guide for Structural Design Engineers

NASA Technical Reports Server (NTRS)

Inman, Daniel J.; Cudney, Harley H.

2000-01-01

Using piezoceramic materials is one way the design engineer can create structures which have an ability to both sense and respond to their environment. Piezoceramic materials can be used to create structural sensors and structural actuators. Because piezoceramic materials have transduction as a material property, their sensing or actuation functions are a result of what happens to the material. This is different than discrete devices we might attach to the structure. For example, attaching an accelerometer to a structure will yield an electrical signal proportional to the acceleration at the attachment point on the structure. Using a electromagnetic shaker as an actuator will create an applied force at the attachment point. Active material elements in a structural design are not easily modeled as providing transduction at a point, but rather they change the physics of the structure in the areas where they are used. Hence, a designer must not think of adding discrete devices to a structure to obtain an effect, but rather must design a structural system which accounts for the physical principles of all the elements in the structure. The purpose of this manual is to provide practicing engineers the information necessary to incorporate piezoelectric materials in structural design and machine design. First, we will review the solid-state physics of piezoelectric materials. Then we will discuss the physical characteristics of the electrical-active material-structural system. We will present the elements of this system which must be considered as part of the design task for a structural engineer. We will cover simple modeling techniques and review the features and capabilities of commercial design tools that are available. We will then cover practical how-to elements of working with piezoceramic materials. We will review sources of piezoceramic materials and built-up devices, and their characteristics. Finally, we will provide two design examples using piezoceramic materials, first as discrete actuators for vibration isolation, and second as structurally-distributed sensor/actuators for active acoustic control.

Reliability-based design optimization of reinforced concrete structures including soil-structure interaction using a discrete gravitational search algorithm and a proposed metamodel

NASA Astrophysics Data System (ADS)

Khatibinia, M.; Salajegheh, E.; Salajegheh, J.; Fadaee, M. J.

2013-10-01

A new discrete gravitational search algorithm (DGSA) and a metamodelling framework are introduced for reliability-based design optimization (RBDO) of reinforced concrete structures. The RBDO of structures with soil-structure interaction (SSI) effects is investigated in accordance with performance-based design. The proposed DGSA is based on the standard gravitational search algorithm (GSA) to optimize the structural cost under deterministic and probabilistic constraints. The Monte-Carlo simulation (MCS) method is considered as the most reliable method for estimating the probabilities of reliability. In order to reduce the computational time of MCS, the proposed metamodelling framework is employed to predict the responses of the SSI system in the RBDO procedure. The metamodel consists of a weighted least squares support vector machine (WLS-SVM) and a wavelet kernel function, which is called WWLS-SVM. Numerical results demonstrate the efficiency and computational advantages of DGSA and the proposed metamodel for RBDO of reinforced concrete structures.

An evaluation of overnight fixation to facilitate neuropathological examination in Coroner's autopsies: our experience of over 200 cases.

PubMed

Scott, Ian Stuart; MacDonald, Alastair Wray

2013-01-01

Following recent changes in Coroner's Rules, there has been a desire to examine brains at the time of autopsy, rather than after a prolonged period of immersion fixation. Examination of the fresh brain at postmortem can yield unsatisfactory results where detailed histological examination is required. We aim to provide a compromise, where detailed examination of the brain is possible, without the requirement for prolonged fixation, interference with funeral arrangements and delay in the Coronial process. A retrospective audit of over 200 neuropathology cases requested by HM Coroner for the East Riding of Yorkshire between 2007 and 2010 was performed. The cases consisted of full neuropathology autopsies (n=212) and brains referred by general pathology colleagues (n=26). Of the 238 brains examined, approximately half (n=109) of the brains were sectioned fresh in the mortuary. The remaining brains (n=129) were immersion fixed overnight in 20% formalin prior to cutting and sampling for histology (n=127). The median time for reporting was 31 days (range 1-167; n=101) for brains requiring histology. This equates to a median turnaround time of 1 month for a neuropathological autopsy requiring detailed histology. In all cases, the report was prepared and available to HM Coroner in advance of the Inquest. This method provides reliable histological diagnoses in neuropathological autopsies and does not interfere with funeral arrangements for bereaved families following deaths falling under Coronial jurisdiction. In all cases, the body could be released to relatives, at Coroner's discretion, within two working days of the autopsy.

Discrete-Layer Piezoelectric Plate and Shell Models for Active Tip-Clearance Control

NASA Technical Reports Server (NTRS)

Heyliger, P. R.; Ramirez, G.; Pei, K. C.

1994-01-01

The objectives of this work were to develop computational tools for the analysis of active-sensory composite structures with added or embedded piezoelectric layers. The targeted application for this class of smart composite laminates and the analytical development is the accomplishment of active tip-clearance control in turbomachinery components. Two distinct theories and analytical models were developed and explored under this contract: (1) a discrete-layer plate theory and corresponding computational models, and (2) a three dimensional general discrete-layer element generated in curvilinear coordinates for modeling laminated composite piezoelectric shells. Both models were developed from the complete electromechanical constitutive relations of piezoelectric materials, and incorporate both displacements and potentials as state variables. This report describes the development and results of these models. The discrete-layer theories imply that the displacement field and electrostatic potential through-the-thickness of the laminate are described over an individual layer rather than as a smeared function over the thickness of the entire plate or shell thickness. This is especially crucial for composites with embedded piezoelectric layers, as the actuating and sensing elements within these layers are poorly represented by effective or smeared properties. Linear Lagrange interpolation polynomials were used to describe the through-thickness laminate behavior. Both analytic and finite element approximations were used in the plane or surface of the structure. In this context, theoretical developments are presented for the discrete-layer plate theory, the discrete-layer shell theory, and the formulation of an exact solution for simply-supported piezoelectric plates. Finally, evaluations and results from a number of separate examples are presented for the static and dynamic analysis of the plate geometry. Comparisons between the different approaches are provided when possible, and initial conclusions regarding the accuracy and limitations of these models are given.

Risk and protective factors for structural brain ageing in the eighth decade of life.

PubMed

Ritchie, Stuart J; Tucker-Drob, Elliot M; Cox, Simon R; Dickie, David Alexander; Del C Valdés Hernández, Maria; Corley, Janie; Royle, Natalie A; Redmond, Paul; Muñoz Maniega, Susana; Pattie, Alison; Aribisala, Benjamin S; Taylor, Adele M; Clarke, Toni-Kim; Gow, Alan J; Starr, John M; Bastin, Mark E; Wardlaw, Joanna M; Deary, Ian J

2017-11-01

Individuals differ markedly in brain structure, and in how this structure degenerates during ageing. In a large sample of human participants (baseline n = 731 at age 73 years; follow-up n = 488 at age 76 years), we estimated the magnitude of mean change and variability in changes in MRI measures of brain macrostructure (grey matter, white matter, and white matter hyperintensity volumes) and microstructure (fractional anisotropy and mean diffusivity from diffusion tensor MRI). All indices showed significant average change with age, with considerable heterogeneity in those changes. We then tested eleven socioeconomic, physical, health, cognitive, allostatic (inflammatory and metabolic), and genetic variables for their value in predicting these differences in changes. Many of these variables were significantly correlated with baseline brain structure, but few could account for significant portions of the heterogeneity in subsequent brain change. Physical fitness was an exception, being correlated both with brain level and changes. The results suggest that only a subset of correlates of brain structure are also predictive of differences in brain ageing.

Human Fetal Brain Connectome: Structural Network Development from Middle Fetal Stage to Birth

PubMed Central

Song, Limei; Mishra, Virendra; Ouyang, Minhui; Peng, Qinmu; Slinger, Michelle; Liu, Shuwei; Huang, Hao

2017-01-01

Complicated molecular and cellular processes take place in a spatiotemporally heterogeneous and precisely regulated pattern in the human fetal brain, yielding not only dramatic morphological and microstructural changes, but also macroscale connectomic transitions. As the underlying substrate of the fetal brain structural network, both dynamic neuronal migration pathways and rapid developing fetal white matter (WM) fibers could fundamentally reshape early fetal brain connectome. Quantifying structural connectome development can not only shed light on the brain reconfiguration in this critical yet rarely studied developmental period, but also reveal alterations of the connectome under neuropathological conditions. However, transition of the structural connectome from the mid-fetal stage to birth is not yet known. The contribution of different types of neural fibers to the structural network in the mid-fetal brain is not known, either. In this study, diffusion tensor magnetic resonance imaging (DT-MRI or DTI) of 10 fetal brain specimens at the age of 20 postmenstrual weeks (PMW), 12 in vivo brains at 35 PMW, and 12 in vivo brains at term (40 PMW) were acquired. The structural connectome of each brain was established with evenly parcellated cortical regions as network nodes and traced fiber pathways based on DTI tractography as network edges. Two groups of fibers were categorized based on the fiber terminal locations in the cerebral wall in the 20 PMW fetal brains. We found that fetal brain networks become stronger and more efficient during 20–40 PMW. Furthermore, network strength and global efficiency increase more rapidly during 20–35 PMW than during 35–40 PMW. Visualization of the whole brain fiber distribution by the lengths suggested that the network reconfiguration in this developmental period could be associated with a significant increase of major long association WM fibers. In addition, non-WM neural fibers could be a major contributor to the structural network configuration at 20 PMW and small-world network organization could exist as early as 20 PMW. These findings offer a preliminary record of the fetal brain structural connectome maturation from the middle fetal stage to birth and reveal the critical role of non-WM neural fibers in structural network configuration in the middle fetal stage. PMID:29081731

Analyzing neuronal networks using discrete-time dynamics

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Smith, Brian H.; Borisyuk, Alla; Terman, David

2010-05-01

We develop mathematical techniques for analyzing detailed Hodgkin-Huxley like models for excitatory-inhibitory neuronal networks. Our strategy for studying a given network is to first reduce it to a discrete-time dynamical system. The discrete model is considerably easier to analyze, both mathematically and computationally, and parameters in the discrete model correspond directly to parameters in the original system of differential equations. While these networks arise in many important applications, a primary focus of this paper is to better understand mechanisms that underlie temporally dynamic responses in early processing of olfactory sensory information. The models presented here exhibit several properties that have been described for olfactory codes in an insect’s Antennal Lobe. These include transient patterns of synchronization and decorrelation of sensory inputs. By reducing the model to a discrete system, we are able to systematically study how properties of the dynamics, including the complex structure of the transients and attractors, depend on factors related to connectivity and the intrinsic and synaptic properties of cells within the network.

GEMPIC: geometric electromagnetic particle-in-cell methods

NASA Astrophysics Data System (ADS)

Kraus, Michael; Kormann, Katharina; Morrison, Philip J.; Sonnendrücker, Eric

2017-08-01

We present a novel framework for finite element particle-in-cell methods based on the discretization of the underlying Hamiltonian structure of the Vlasov-Maxwell system. We derive a semi-discrete Poisson bracket, which retains the defining properties of a bracket, anti-symmetry and the Jacobi identity, as well as conservation of its Casimir invariants, implying that the semi-discrete system is still a Hamiltonian system. In order to obtain a fully discrete Poisson integrator, the semi-discrete bracket is used in conjunction with Hamiltonian splitting methods for integration in time. Techniques from finite element exterior calculus ensure conservation of the divergence of the magnetic field and Gauss' law as well as stability of the field solver. The resulting methods are gauge invariant, feature exact charge conservation and show excellent long-time energy and momentum behaviour. Due to the generality of our framework, these conservation properties are guaranteed independently of a particular choice of the finite element basis, as long as the corresponding finite element spaces satisfy certain compatibility conditions.

Black holes in loop quantum gravity.

PubMed

Perez, Alejandro

2017-12-01

This is a review of results on black hole physics in the context of loop quantum gravity. The key feature underlying these results is the discreteness of geometric quantities at the Planck scale predicted by this approach to quantum gravity. Quantum discreteness follows directly from the canonical quantization prescription when applied to the action of general relativity that is suitable for the coupling of gravity with gauge fields, and especially with fermions. Planckian discreteness and causal considerations provide the basic structure for the understanding of the thermal properties of black holes close to equilibrium. Discreteness also provides a fresh new look at more (at the moment) speculative issues, such as those concerning the fate of information in black hole evaporation. The hypothesis of discreteness leads, also, to interesting phenomenology with possible observational consequences. The theory of loop quantum gravity is a developing program; this review reports its achievements and open questions in a pedagogical manner, with an emphasis on quantum aspects of black hole physics.

Efficient Relaxation of Protein-Protein Interfaces by Discrete Molecular Dynamics Simulations.

PubMed

Emperador, Agusti; Solernou, Albert; Sfriso, Pedro; Pons, Carles; Gelpi, Josep Lluis; Fernandez-Recio, Juan; Orozco, Modesto

2013-02-12

Protein-protein interactions are responsible for the transfer of information inside the cell and represent one of the most interesting research fields in structural biology. Unfortunately, after decades of intense research, experimental approaches still have difficulties in providing 3D structures for the hundreds of thousands of interactions formed between the different proteins in a living organism. The use of theoretical approaches like docking aims to complement experimental efforts to represent the structure of the protein interactome. However, we cannot ignore that current methods have limitations due to problems of sampling of the protein-protein conformational space and the lack of accuracy of available force fields. Cases that are especially difficult for prediction are those in which complex formation implies a non-negligible change in the conformation of the interacting proteins, i.e., those cases where protein flexibility plays a key role in protein-protein docking. In this work, we present a new approach to treat flexibility in docking by global structural relaxation based on ultrafast discrete molecular dynamics. On a standard benchmark of protein complexes, the method provides a general improvement over the results obtained by rigid docking. The method is especially efficient in cases with large conformational changes upon binding, in which structure relaxation with discrete molecular dynamics leads to a predictive success rate double that obtained with state-of-the-art rigid-body docking.