WorldWideScience

Sample records for neural structures involved

  1. Proteus mirabilis abscess involving the entire neural axis.

    Science.gov (United States)

    Kamat, A S; Thango, N S; Husein, M Ben

    2016-08-01

    Intramedullary spinal cord abscesses are rare and potentially devastating lesions usually associated with other infective processes such as bacterial endocarditis, or pulmonary or urogenital infection. We describe a 2-year-old girl who presented with an infected dermal sinus leading to an intraspinal abscess. This abscess eventually spread and involved the entire neural axis leaving her quadriparetic. Drainage of the abscess resulted in recovery and the child regained normal function of her limbs. To our knowledge this is the first documented case of an intramedullary abscess involving the entire neural axis. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    Bohr, Henrik

    1998-01-01

    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

  3. A Topological Perspective of Neural Network Structure

    Science.gov (United States)

    Sizemore, Ann; Giusti, Chad; Cieslak, Matthew; Grafton, Scott; Bassett, Danielle

    The wiring patterns of white matter tracts between brain regions inform functional capabilities of the neural network. Indeed, densely connected and cyclically arranged cognitive systems may communicate and thus perform distinctly. However, previously employed graph theoretical statistics are local in nature and thus insensitive to such global structure. Here we present an investigation of the structural neural network in eight healthy individuals using persistent homology. An extension of homology to weighted networks, persistent homology records both circuits and cliques (all-to-all connected subgraphs) through a repetitive thresholding process, thus perceiving structural motifs. We report structural features found across patients and discuss brain regions responsible for these patterns, finally considering the implications of such motifs in relation to cognitive function.

  4. Neural Correlates of Verb Argument Structure Processing

    OpenAIRE

    Thompson, Cynthia K.; Bonakdarpour, Borna; Fix, Stephen C.; Blumenfeld, Henrike K.; Parrish, Todd B.; Gitelman, Darren R.; Mesulam, M.-Marsel

    2007-01-01

    Neuroimaging and lesion studies suggest that processing of word classes, such as verbs and nouns, is associated with distinct neural mechanisms. Such studies also suggest that subcategories within these broad word class categories are differentially processed in the brain. Within the class of verbs, argument structure provides one linguistic dimension that distinguishes among verb exemplars, with some requiring more complex argument structure entries than others. This study examined the neura...

  5. Neural correlates of verb argument structure processing.

    Science.gov (United States)

    Thompson, Cynthia K; Bonakdarpour, Borna; Fix, Stephen C; Blumenfeld, Henrike K; Parrish, Todd B; Gitelman, Darren R; Mesulam, M-Marsel

    2007-11-01

    Neuroimaging and lesion studies suggest that processing of word classes, such as verbs and nouns, is associated with distinct neural mechanisms. Such studies also suggest that subcategories within these broad word class categories are differentially processed in the brain. Within the class of verbs, argument structure provides one linguistic dimension that distinguishes among verb exemplars, with some requiring more complex argument structure entries than others. This study examined the neural instantiation of verbs by argument structure complexity: one-, two-, and three-argument verbs. Stimuli of each type, along with nouns and pseudowords, were presented for lexical decision using an event-related functional magnetic resonance imaging design. Results for 14 young normal participants indicated largely overlapping activation maps for verbs and nouns, with no areas of significant activation for verbs compared to nouns, or vice versa. Pseudowords also engaged neural tissue overlapping with that for both word classes, with more widespread activation noted in visual, motor, and peri-sylvian regions. Examination of verbs by argument structure revealed activation of the supramarginal and angular gyri, limited to the left hemisphere only when verbs with two obligatory arguments were compared to verbs with a single argument. However, bilateral activation was noted when both two- and three-argument verbs were compared to one-argument verbs. These findings suggest that posterior peri-sylvian regions are engaged for processing argument structure information associated with verbs, with increasing neural tissue in the inferior parietal region associated with increasing argument structure complexity. These findings are consistent with processing accounts, which suggest that these regions are crucial for semantic integration.

  6. CHD7, the gene mutated in CHARGE syndrome, regulates genes involved in neural crest cell guidance.

    Science.gov (United States)

    Schulz, Yvonne; Wehner, Peter; Opitz, Lennart; Salinas-Riester, Gabriela; Bongers, Ernie M H F; van Ravenswaaij-Arts, Conny M A; Wincent, Josephine; Schoumans, Jacqueline; Kohlhase, Jürgen; Borchers, Annette; Pauli, Silke

    2014-08-01

    Heterozygous loss of function mutations in CHD7 (chromodomain helicase DNA-binding protein 7) lead to CHARGE syndrome, a complex developmental disorder affecting craniofacial structures, cranial nerves and several organ systems. Recently, it was demonstrated that CHD7 is essential for the formation of multipotent migratory neural crest cells, which migrate from the neural tube to many regions of the embryo, where they differentiate into various tissues including craniofacial and heart structures. So far, only few CHD7 target genes involved in neural crest cell development have been identified and the role of CHD7 in neural crest cell guidance and the regulation of mesenchymal-epithelial transition are unknown. Therefore, we undertook a genome-wide microarray expression analysis on wild-type and CHD7 deficient (Chd7 (Whi/+) and Chd7 (Whi/Whi)) mouse embryos at day 9.5, a time point of neural crest cell migration. We identified 98 differentially expressed genes between wild-type and Chd7 (Whi/Whi) embryos. Interestingly, many misregulated genes are involved in neural crest cell and axon guidance such as semaphorins and ephrin receptors. By performing knockdown experiments for Chd7 in Xenopus laevis embryos, we found abnormalities in the expression pattern of Sema3a, a protein involved in the pathogenesis of Kallmann syndrome, in vivo. In addition, we detected non-synonymous SEMA3A variations in 3 out of 45 CHD7-negative CHARGE patients. In summary, we discovered for the first time that Chd7 regulates genes involved in neural crest cell guidance, demonstrating a new aspect in the pathogenesis of CHARGE syndrome. Furthermore, we showed for Sema3a a conserved regulatory mechanism across different species, highlighting its significance during development. Although we postulated that the non-synonymous SEMA3A variants which we found in CHD7-negative CHARGE patients alone are not sufficient to produce the phenotype, we suggest an important modifier role for SEMA3A in the

  7. Hierarchical Neural Network Structures for Phoneme Recognition

    CERN Document Server

    Vasquez, Daniel; Minker, Wolfgang

    2013-01-01

    In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a  Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach.

  8. Structural and functional neural correlates of music perception.

    Science.gov (United States)

    Limb, Charles J

    2006-04-01

    This review article highlights state-of-the-art functional neuroimaging studies and demonstrates the novel use of music as a tool for the study of human auditory brain structure and function. Music is a unique auditory stimulus with properties that make it a compelling tool with which to study both human behavior and, more specifically, the neural elements involved in the processing of sound. Functional neuroimaging techniques represent a modern and powerful method of investigation into neural structure and functional correlates in the living organism. These methods have demonstrated a close relationship between the neural processing of music and language, both syntactically and semantically. Greater neural activity and increased volume of gray matter in Heschl's gyrus has been associated with musical aptitude. Activation of Broca's area, a region traditionally considered to subserve language, is important in interpreting whether a note is on or off key. The planum temporale shows asymmetries that are associated with the phenomenon of perfect pitch. Functional imaging studies have also demonstrated activation of primitive emotional centers such as ventral striatum, midbrain, amygdala, orbitofrontal cortex, and ventral medial prefrontal cortex in listeners of moving musical passages. In addition, studies of melody and rhythm perception have elucidated mechanisms of hemispheric specialization. These studies show the power of music and functional neuroimaging to provide singularly useful tools for the study of brain structure and function.

  9. Identification of Non-Linear Structures using Recurrent Neural Networks

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Nielsen, Søren R. K.; Hansen, H. I.

    1995-01-01

    Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure.......Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure....

  10. Identification of Non-Linear Structures using Recurrent Neural Networks

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Nielsen, Søren R. K.; Hansen, H. I.

    Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure.......Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure....

  11. Aspects of randomness in neural graph structures

    CERN Document Server

    Rudolph-Lilith, Michelle

    2013-01-01

    In the past two decades, significant advances have been made in understanding the structural and functional properties of biological networks, via graph-theoretic analysis. In general, most graph-theoretic studies are conducted in the presence of serious uncertainties, such as major undersampling of the experimental data. In the specific case of neural systems, however, a few moderately robust experimental reconstructions do exist, and these have long served as fundamental prototypes for studying connectivity patterns in the nervous system. In this paper, we provide a comparative analysis of these "historical" graphs, both in (unmodified) directed and (often symmetrized) undirected forms, and focus on simple structural characterizations of their connectivity. We find that in most measures the networks studied are captured by simple random graph models; in a few key measures, however, we observe a marked departure from the random graph prediction. Our results suggest that the mechanism of graph formation in th...

  12. Reassessing the causal structure of enduring involvement

    Science.gov (United States)

    Jinhee Jun; Gerard T. Kyle; James D. Absher; William E. Hammitt

    2009-01-01

    Guided by tenets of identity theory, we hypothesized a causal structure of enduring involvement suggesting that self-relevant components precede the other dimensions. We used Kyle et al.'s (2004a) Modified Involvement Scale, in which leisure involvement is conceptualized as a multidimensional construct consisting of identity affirmation, identity expression,...

  13. The structural neural substrate of subjective happiness.

    Science.gov (United States)

    Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Kubota, Yasutaka; Sawada, Reiko; Yoshimura, Sayaka; Toichi, Motomi

    2015-11-20

    Happiness is a subjective experience that is an ultimate goal for humans. Psychological studies have shown that subjective happiness can be measured reliably and consists of emotional and cognitive components. However, the neural substrates of subjective happiness remain unclear. To investigate this issue, we used structural magnetic resonance imaging and questionnaires that assessed subjective happiness, the intensity of positive and negative emotional experiences, and purpose in life. We found a positive relationship between the subjective happiness score and gray matter volume in the right precuneus. Moreover, the same region showed an association with the combined positive and negative emotional intensity and purpose in life scores. Our findings suggest that the precuneus mediates subjective happiness by integrating the emotional and cognitive components of happiness.

  14. The structural neural substrate of subjective happiness

    Science.gov (United States)

    Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Kubota, Yasutaka; Sawada, Reiko; Yoshimura, Sayaka; Toichi, Motomi

    2015-01-01

    Happiness is a subjective experience that is an ultimate goal for humans. Psychological studies have shown that subjective happiness can be measured reliably and consists of emotional and cognitive components. However, the neural substrates of subjective happiness remain unclear. To investigate this issue, we used structural magnetic resonance imaging and questionnaires that assessed subjective happiness, the intensity of positive and negative emotional experiences, and purpose in life. We found a positive relationship between the subjective happiness score and gray matter volume in the right precuneus. Moreover, the same region showed an association with the combined positive and negative emotional intensity and purpose in life scores. Our findings suggest that the precuneus mediates subjective happiness by integrating the emotional and cognitive components of happiness. PMID:26586449

  15. Neural Schematics as a unified formal graphical representation of large-scale Neural Network Structures

    Directory of Open Access Journals (Sweden)

    Matthias eEhrlich

    2013-10-01

    Full Text Available One of the major outcomes of neuroscientific research are models of Neural Network Structures. Descriptions of these models usually consist of a non-standardized mixture of text, figures, and other means of visual information communication in print media. However, as neuroscience is an interdisciplinary domain by nature, a standardized way of consistently representing models of Neural Network Structures is required. While generic descriptions of such models in textual form have recently been developed, a formalized way of schematically expressing them does not exist to date. Hence, in this paper we present Neural Schematics as a concept inspired by similar approaches from other disciplines for a generic two dimensional representation of said structures. After introducing Neural Network Structures in general, a set of current visualizations of models of Neural Network Structures is reviewed and analyzed for what information they convey and how their elements are rendered. This analysis then allows for the definition of general items and symbols to consistently represent these models as Neural Schematics on a two dimensional plane. We will illustrate the possibilities an agreed upon standard can yield on sampled diagrams transformed into Neural Schematics and an example application for the design and modeling of large-scale Neural Network Structures.

  16. Automated Modeling of Microwave Structures by Enhanced Neural Networks

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2006-12-01

    Full Text Available The paper describes the methodology of the automated creation of neural models of microwave structures. During the creation process, artificial neural networks are trained using the combination of the particle swarm optimization and the quasi-Newton method to avoid critical training problems of the conventional neural nets. In the paper, neural networks are used to approximate the behavior of a planar microwave filter (moment method, Zeland IE3D. In order to evaluate the efficiency of neural modeling, global optimizations are performed using numerical models and neural ones. Both approaches are compared from the viewpoint of CPU-time demands and the accuracy. Considering conclusions, methodological recommendations for including neural networks to the microwave design are formulated.

  17. Involvement of Atm and Trp53 in neural cell loss due to Terf2 inactivation during mouse brain development.

    Science.gov (United States)

    Kim, Jusik; Choi, Inseo; Lee, Youngsoo

    2017-11-01

    Maintenance of genomic integrity is one of the critical features for proper neurodevelopment and inhibition of neurological diseases. The signals from both ATM and ATR to TP53 are well-known mechanisms to remove neural cells with DNA damage during neurogenesis. Here we examined the involvement of Atm and Atr in genomic instability due to Terf2 inactivation during mouse brain development. Selective inactivation of Terf2 in neural progenitors induced apoptosis, resulting in a complete loss of the brain structure. This neural loss was rescued partially in both Atm and Trp53 deficiency, but not in an Atr-deficient background in the mouse. Atm inactivation resulted in incomplete brain structures, whereas p53 deficiency led to the formation of multinucleated giant neural cells and the disruption of the brain structure. These giant neural cells disappeared in Lig4 deficiency. These data demonstrate ATM and TP53 are important for the maintenance of telomere homeostasis and the surveillance of telomere dysfunction during neurogenesis.

  18. Combining neural networks for protein secondary structure prediction

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1995-01-01

    In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...... by using a priori knowledge of the mapping between protein building blocks and the secondary structure and by using weight sharing. Since none of the individual networks have more than 600 adjustable weights over-fitting is avoided. When ensembles of specialized experts are combined the performance...

  19. Modeling Broadband Microwave Structures by Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    V. Otevrel

    2004-06-01

    Full Text Available The paper describes the exploitation of feed-forward neural networksand recurrent neural networks for replacing full-wave numerical modelsof microwave structures in complex microwave design tools. Building aneural model, attention is turned to the modeling accuracy and to theefficiency of building a model. Dealing with the accuracy, we describea method of increasing it by successive completing a training set.Neural models are mutually compared in order to highlight theiradvantages and disadvantages. As a reference model for comparisons,approximations based on standard cubic splines are used. Neural modelsare used to replace both the time-domain numeric models and thefrequency-domain ones.

  20. Neural networks for harmonic structure in music perception and action

    OpenAIRE

    Bianco, R.; Novembre, G.; Keller, P. E.; Kim, S G; Scharf, F.; Friederici, A. D.; Villringer, A; Sammler, D.

    2016-01-01

    The ability to predict upcoming structured events based on long-term knowledge and contextual priors is a fundamental principle of human cognition. Tonal music triggers predictive processes based on structural properties of harmony, i.e., regularities defining the arrangement of chords into well-formed musical sequences. While the neural architecture of structure-based predictions during music perception is well described, little is known about the neural networks for analogous predictions in...

  1. Neural circuits involved in the renewal of extinguished fear.

    Science.gov (United States)

    Chen, Weihai; Wang, Yan; Wang, Xiaqing; Li, Hong

    2017-07-01

    The last 10 years have witnessed a substantial progress in understanding the neural mechanisms for the renewal of the extinguished fear memory. Based on the theory of fear extinction, exposure therapy has been developed as a typical cognitive behavioral therapy for posttraumatic stress disorder. Although the fear memory can be extinguished by repeated presentation of conditioned stimulus without unconditioned stimulus, the fear memory is not erased and tends to relapse outside of extinction context, which is referred to as renewal. Therefore, the renewal is regarded as a great obstruction interfering with the effect of exposure therapy. In recent years, there has been a great deal of studies in understanding the neurobiological underpinnings of fear renewal. These offer a foundation upon which novel therapeutic interventions for the renewal may be built. This review focuses on behavioral, anatomical and electrophysiological studies that interpret roles of the hippocampus, prelimbic cortex and amygdala as well as the connections between them for the renewal of the extinguished fear. Additionally, this review suggests the possible pathways for the renewal: (1) the prelimbic cortex may integrate contextual information from hippocampal inputs and project to the basolateral amygdala to mediate the renewal of extinguished fear memory; the ventral hippocampus may innervate the activities of the basolateral amygdala or the central amygdala directly for the renewal. © 2017 IUBMB Life, 69(7):470-478, 2017. © 2017 International Union of Biochemistry and Molecular Biology.

  2. Structuring a multi-nodal neural network in vitro within a novel design microfluidic chip.

    Science.gov (United States)

    van de Wijdeven, Rosanne; Ramstad, Ola Huse; Bauer, Ulrich Stefan; Halaas, Øyvind; Sandvig, Axel; Sandvig, Ioanna

    2018-01-02

    Neural network formation is a complex process involving axon outgrowth and guidance. Axon guidance is facilitated by structural and molecular cues from the surrounding microenvironment. Micro-fabrication techniques can be employed to produce microfluidic chips with a highly controlled microenvironment for neural cells enabling longitudinal studies of complex processes associated with network formation. In this work, we demonstrate a novel open microfluidic chip design that encompasses a freely variable number of nodes interconnected by axon-permissible tunnels, enabling structuring of multi-nodal neural networks in vitro. The chip employs a partially open design to allow high level of control and reproducibility of cell seeding, while reducing shear stress on the cells. We show that by culturing dorsal root ganglion cells (DRGs) in our microfluidic chip, we were able to structure a neural network in vitro. These neurons were compartmentalized within six nodes interconnected through axon growth tunnels. Furthermore, we demonstrate the additional benefit of open top design by establishing a 3D neural culture in matrigel and a neuronal aggregate 3D culture within the chips. In conclusion, our results demonstrate a novel microfluidic chip design applicable to structuring complex neural networks in vitro, thus providing a versatile, highly relevant platform for the study of neural network dynamics applicable to developmental and regenerative neuroscience.

  3. Linking neural and symbolic representation and processing of conceptual structures

    NARCIS (Netherlands)

    van der Velde, Frank; Forth, Jamie; Nazareth, Deniece S.; Wiggins, Geraint A.

    2017-01-01

    We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual

  4. Neural Network Algorithm for Prediction of Secondary Protein Structure

    National Research Council Canada - National Science Library

    Zikrija Avdagic; Elvir Purisevic; Emir Buza; Zlatan Coralic

    2009-01-01

    .... In this paper we describe the method and results of using CB513 as a dataset suitable for development of artificial neural network algorithms for prediction of secondary protein structure with MATLAB...

  5. Précis of Neural organization: structure, function, and dynamics.

    Science.gov (United States)

    Arbib, M A; Erdi, P

    2000-08-01

    NEURAL ORGANIZATION: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. (1) STRUCTURE: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. (2) FUNCTION: Control of eye movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. (3) DYNAMICS: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and (often synchronized) neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai.

  6. Neural network definitions of highly predictable protein secondary structure classes

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., NM (United States); Steeg, E. [Toronto Univ., ON (Canada). Dept. of Computer Science; Farber, R. [Los Alamos National Lab., NM (United States)

    1994-02-01

    We use two co-evolving neural networks to determine new classes of protein secondary structure which are significantly more predictable from local amino sequence than the conventional secondary structure classification. Accurate prediction of the conventional secondary structure classes: alpha helix, beta strand, and coil, from primary sequence has long been an important problem in computational molecular biology. Neural networks have been a popular method to attempt to predict these conventional secondary structure classes. Accuracy has been disappointingly low. The algorithm presented here uses neural networks to similtaneously examine both sequence and structure data, and to evolve new classes of secondary structure that can be predicted from sequence with significantly higher accuracy than the conventional classes. These new classes have both similarities to, and differences with the conventional alpha helix, beta strand and coil.

  7. Neural mirroring and social interaction: Motor system involvement during action observation relates to early peer cooperation

    Directory of Open Access Journals (Sweden)

    H.M. Endedijk

    2017-04-01

    Full Text Available Whether we hand over objects to someone, play a team sport, or make music together, social interaction often involves interpersonal action coordination, both during instances of cooperation and entrainment. Neural mirroring is thought to play a crucial role in processing other’s actions and is therefore considered important for social interaction. Still, to date, it is unknown whether interindividual differences in neural mirroring play a role in interpersonal coordination during different instances of social interaction. A relation between neural mirroring and interpersonal coordination has particularly relevant implications for early childhood, since successful early interaction with peers is predictive of a more favorable social development. We examined the relation between neural mirroring and children’s interpersonal coordination during peer interaction using EEG and longitudinal behavioral data. Results showed that 4-year-old children with higher levels of motor system involvement during action observation (as indicated by lower beta-power were more successful in early peer cooperation. This is the first evidence for a relation between motor system involvement during action observation and interpersonal coordination during other instances of social interaction. The findings suggest that interindividual differences in neural mirroring are related to interpersonal coordination and thus successful social interaction.

  8. Neural mirroring and social interaction: Motor system involvement during action observation relates to early peer cooperation.

    Science.gov (United States)

    Endedijk, H M; Meyer, M; Bekkering, H; Cillessen, A H N; Hunnius, S

    2017-04-01

    Whether we hand over objects to someone, play a team sport, or make music together, social interaction often involves interpersonal action coordination, both during instances of cooperation and entrainment. Neural mirroring is thought to play a crucial role in processing other's actions and is therefore considered important for social interaction. Still, to date, it is unknown whether interindividual differences in neural mirroring play a role in interpersonal coordination during different instances of social interaction. A relation between neural mirroring and interpersonal coordination has particularly relevant implications for early childhood, since successful early interaction with peers is predictive of a more favorable social development. We examined the relation between neural mirroring and children's interpersonal coordination during peer interaction using EEG and longitudinal behavioral data. Results showed that 4-year-old children with higher levels of motor system involvement during action observation (as indicated by lower beta-power) were more successful in early peer cooperation. This is the first evidence for a relation between motor system involvement during action observation and interpersonal coordination during other instances of social interaction. The findings suggest that interindividual differences in neural mirroring are related to interpersonal coordination and thus successful social interaction. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Linking Neural and Symbolic Representation and Processing of Conceptual Structures

    Directory of Open Access Journals (Sweden)

    Frank van der Velde

    2017-08-01

    Full Text Available We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like structures. First is the Neural Blackboard Architecture (NBA, which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking, which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures.

  10. Puzzle Pieces: Neural Structure and Function in Prader-Willi Syndrome

    Science.gov (United States)

    Manning, Katherine E.; Holland, Anthony J.

    2015-01-01

    Prader-Willi syndrome (PWS) is a neurodevelopmental disorder of genomic imprinting, presenting with a behavioural phenotype encompassing hyperphagia, intellectual disability, social and behavioural difficulties, and propensity to psychiatric illness. Research has tended to focus on the cognitive and behavioural investigation of these features, and, with the exception of eating behaviour, the neural physiology is currently less well understood. A systematic review was undertaken to explore findings relating to neural structure and function in PWS, using search terms designed to encompass all published articles concerning both in vivo and post-mortem studies of neural structure and function in PWS. This supported the general paucity of research in this area, with many articles reporting case studies and qualitative descriptions or focusing solely on the overeating behaviour, although a number of systematic investigations were also identified. Research to date implicates a combination of subcortical and higher order structures in PWS, including those involved in processing reward, motivation, affect and higher order cognitive functions, with both anatomical and functional investigations indicating abnormalities. It appears likely that PWS involves aberrant activity across distributed neural networks. The characterisation of neural structure and function warrants both replication and further systematic study. PMID:28943631

  11. Puzzle Pieces: Neural Structure and Function in Prader-Willi Syndrome

    Directory of Open Access Journals (Sweden)

    Katherine E. Manning

    2015-12-01

    Full Text Available Prader-Willi syndrome (PWS is a neurodevelopmental disorder of genomic imprinting, presenting with a behavioural phenotype encompassing hyperphagia, intellectual disability, social and behavioural difficulties, and propensity to psychiatric illness. Research has tended to focus on the cognitive and behavioural investigation of these features, and, with the exception of eating behaviour, the neural physiology is currently less well understood. A systematic review was undertaken to explore findings relating to neural structure and function in PWS, using search terms designed to encompass all published articles concerning both in vivo and post-mortem studies of neural structure and function in PWS. This supported the general paucity of research in this area, with many articles reporting case studies and qualitative descriptions or focusing solely on the overeating behaviour, although a number of systematic investigations were also identified. Research to date implicates a combination of subcortical and higher order structures in PWS, including those involved in processing reward, motivation, affect and higher order cognitive functions, with both anatomical and functional investigations indicating abnormalities. It appears likely that PWS involves aberrant activity across distributed neural networks. The characterisation of neural structure and function warrants both replication and further systematic study.

  12. Neural mirroring and social interaction : Motor system involvement during action observation relates to early peer cooperation

    NARCIS (Netherlands)

    Endedijk, H. M.; Meyer, M.; Bekkering, H.; Cillessen, A. H. N.; Hunnius, Sabine

    2017-01-01

    Whether we hand over objects to someone, play a team sport, or make music together, social interaction often involves interpersonal action coordination, both during instances of cooperation and entrainment. Neural mirroring is thought to play a crucial role in processing other's actions and is

  13. Neural mirroring and social interaction: Motor system involvement during action observation relates to early peer cooperation

    NARCIS (Netherlands)

    Endedijk, H.M.; Meyer, M.; Bekkering, H.; Cillessen, A.H.N.; Hunnius, S.

    2017-01-01

    Whether we hand over objects to someone, play a team sport, or make music together, social interaction often involves interpersonal action coordination, both during instances of cooperation and entrainment. Neural mirroring is thought to play a crucial role in processing other's actions and is

  14. Microscopic neural image registration based on the structure of mitochondria

    Science.gov (United States)

    Cao, Huiwen; Han, Hua; Rao, Qiang; Xiao, Chi; Chen, Xi

    2017-02-01

    Microscopic image registration is a key component of the neural structure reconstruction with serial sections of neural tissue. The goal of microscopic neural image registration is to recover the 3D continuity and geometrical properties of specimen. During image registration, various distortions need to be corrected, including image rotation, translation, tissue deformation et.al, which come from the procedure of sample cutting, staining and imaging. Furthermore, there is only certain similarity between adjacent sections, and the degree of similarity depends on local structure of the tissue and the thickness of the sections. These factors make the microscopic neural image registration a challenging problem. To tackle the difficulty of corresponding landmarks extraction, we introduce a novel image registration method for Scanning Electron Microscopy (SEM) images of serial neural tissue sections based on the structure of mitochondria. The ellipsoidal shape of mitochondria ensures that the same mitochondria has similar shape between adjacent sections, and its characteristic of broad distribution in the neural tissue guarantees that landmarks based on the mitochondria distributed widely in the image. The proposed image registration method contains three parts: landmarks extraction between adjacent sections, corresponding landmarks matching and image deformation based on the correspondences. We demonstrate the performance of our method with SEM images of drosophila brain.

  15. Neural entrainment to the rhythmic structure of music.

    Science.gov (United States)

    Tierney, Adam; Kraus, Nina

    2015-02-01

    The neural resonance theory of musical meter explains musical beat tracking as the result of entrainment of neural oscillations to the beat frequency and its higher harmonics. This theory has gained empirical support from experiments using simple, abstract stimuli. However, to date there has been no empirical evidence for a role of neural entrainment in the perception of the beat of ecologically valid music. Here we presented participants with a single pop song with a superimposed bassoon sound. This stimulus was either lined up with the beat of the music or shifted away from the beat by 25% of the average interbeat interval. Both conditions elicited a neural response at the beat frequency. However, although the on-the-beat condition elicited a clear response at the first harmonic of the beat, this frequency was absent in the neural response to the off-the-beat condition. These results support a role for neural entrainment in tracking the metrical structure of real music and show that neural meter tracking can be disrupted by the presentation of contradictory rhythmic cues.

  16. Neural-Fitted TD-Leaf Learning for Playing Othello With Structured Neural Networks

    NARCIS (Netherlands)

    van den Dries, Sjoerd; Wiering, Marco A.

    2012-01-01

    This paper describes a methodology for quickly learning to play games at a strong level. The methodology consists of a novel combination of three techniques, and a variety of experiments on the game of Othello demonstrates their usefulness. First, structures or topologies in neural network

  17. Neural Plasticity Is Involved in Physiological Sleep, Depressive Sleep Disturbances, and Antidepressant Treatments

    Directory of Open Access Journals (Sweden)

    Meng-Qi Zhang

    2017-01-01

    Full Text Available Depression, which is characterized by a pervasive and persistent low mood and anhedonia, greatly impacts patients, their families, and society. The associated and recurring sleep disturbances further reduce patient’s quality of life. However, therapeutic sleep deprivation has been regarded as a rapid and robust antidepressant treatment for several decades, which suggests a complicated role of sleep in development of depression. Changes in neural plasticity are observed during physiological sleep, therapeutic sleep deprivation, and depression. This correlation might help us to understand better the mechanism underlying development of depression and the role of sleep. In this review, we first introduce the structure of sleep and the facilitated neural plasticity caused by physiological sleep. Then, we introduce sleep disturbances and changes in plasticity in patients with depression. Finally, the effects and mechanisms of antidepressants and therapeutic sleep deprivation on neural plasticity are discussed.

  18. Neural Plasticity Is Involved in Physiological Sleep, Depressive Sleep Disturbances, and Antidepressant Treatments.

    Science.gov (United States)

    Zhang, Meng-Qi; Li, Rui; Wang, Yi-Qun; Huang, Zhi-Li

    2017-01-01

    Depression, which is characterized by a pervasive and persistent low mood and anhedonia, greatly impacts patients, their families, and society. The associated and recurring sleep disturbances further reduce patient's quality of life. However, therapeutic sleep deprivation has been regarded as a rapid and robust antidepressant treatment for several decades, which suggests a complicated role of sleep in development of depression. Changes in neural plasticity are observed during physiological sleep, therapeutic sleep deprivation, and depression. This correlation might help us to understand better the mechanism underlying development of depression and the role of sleep. In this review, we first introduce the structure of sleep and the facilitated neural plasticity caused by physiological sleep. Then, we introduce sleep disturbances and changes in plasticity in patients with depression. Finally, the effects and mechanisms of antidepressants and therapeutic sleep deprivation on neural plasticity are discussed.

  19. Community structure of complex networks based on continuous neural network

    Science.gov (United States)

    Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou

    2017-09-01

    As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.

  20. Combinatorial structures and processing in neural blackboard architectures

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; de Kamps, Marc; Besold, Tarek R.; d'Avila Garcez, Artur; Marcus, Gary F.; Miikkulainen, Risto

    2015-01-01

    We discuss and illustrate Neural Blackboard Architectures (NBAs) as the basis for variable binding and combinatorial processing the brain. We focus on the NBA for sentence structure. NBAs are based on the notion that conceptual representations are in situ, hence cannot be copied or transported.

  1. Discriminative training of self-structuring hidden control neural models

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe; Hunnerup, Preben

    1995-01-01

    This paper presents a new training algorithm for self-structuring hidden control neural (SHC) models. The SHC models were trained non-discriminatively for speech recognition applications. Better recognition performance can generally be achieved, if discriminative training is applied instead. Thus...

  2. Product Cost Management Structures: a review and neural network modelling

    Directory of Open Access Journals (Sweden)

    P. Jha

    2003-11-01

    Full Text Available This paper reviews the growth of approaches in product costing and draws synergies with information management and resource planning systems, to investigate potential application of state of the art modelling techniques of neural networks. Increasing demands on costing systems to serve multiple decision-making objectives, have made it essential to use better techniques for analysis of available data. This need is highlighted in the paper. The approach of neural networks, which have several analogous facets to complement and aid the information demands of modern product costing, Enterprise Resource Planning (ERP structures and the dominant-computing environment (for information management in the object oriented paradigm form the domain for investigation. Simulated data is used in neural network applications across activities that consume resources and deliver products, to generate information for monitoring and control decisions. The results in application for feature extraction and variation detection and their implications are presented in the paper.

  3. Structured learning via convolutional neural networks for vehicle detection

    Science.gov (United States)

    Maqueda, Ana I.; del Blanco, Carlos R.; Jaureguizar, Fernando; García, Narciso

    2017-05-01

    One of the main tasks in a vision-based traffic monitoring system is the detection of vehicles. Recently, deep neural networks have been successfully applied to this end, outperforming previous approaches. However, most of these works generally rely on complex and high-computational region proposal networks. Others employ deep neural networks as a segmentation strategy to achieve a semantic representation of the object of interest, which has to be up-sampled later. In this paper, a new design for a convolutional neural network is applied to vehicle detection in highways for traffic monitoring. This network generates a spatially structured output that encodes the vehicle locations. Promising results have been obtained in the GRAM-RTM dataset.

  4. Neural correlates of artificial syntactic structure classification.

    NARCIS (Netherlands)

    Forkstam, C.H.; Hagoort, P.; Fernandez, G.S.E.; Ingvar, M.; Petersson, K.M.

    2006-01-01

    The human brain supports acquisition mechanisms that extract structural regularities implicitly from experience without the induction of an explicit model. It has been argued that the capacity to generalize to new input is based on the acquisition of abstract representations, which reflect

  5. Neural correlates of artificial syntactic structure classification

    NARCIS (Netherlands)

    Forkstam, C.H.; Hagoort, P.; Fernandez, G.S.E.; Ingvar, M.; Petersson, K.M.

    2006-01-01

    The human brain supports acquisition mechanisms that extract structural regularities implicitly from experience without the induction of an explicit model. It has been argued that the capacity to generalize to new input is based on the acquisition of abstract representations, which reflect

  6. Supervised neural networks for the classification of structures.

    Science.gov (United States)

    Sperduti, A; Starita, A

    1997-01-01

    Standard neural networks and statistical methods are usually believed to be inadequate when dealing with complex structures because of their feature-based approach. In fact, feature-based approaches usually fail to give satisfactory solutions because of the sensitivity of the approach to the a priori selection of the features, and the incapacity to represent any specific information on the relationships among the components of the structures. However, we show that neural networks can, in fact, represent and classify structured patterns. The key idea underpinning our approach is the use of the so called "generalized recursive neuron", which is essentially a generalization to structures of a recurrent neuron. By using generalized recursive neurons, all the supervised networks developed for the classification of sequences, such as backpropagation through time networks, real-time recurrent networks, simple recurrent networks, recurrent cascade correlation networks, and neural trees can, on the whole, be generalized to structures. The results obtained by some of the above networks (with generalized recursive neurons) on the classification of logic terms are presented.

  7. Reassessing the structure of enduring leisure involvement

    Science.gov (United States)

    Jinhee Jun; Gerard T. Kyle; Symeon P. Vlachopoulos; Nicholas D. Theodorakis; James D. Absher; William E. Hammitt

    2012-01-01

    Using data collected from U.S. and Greek respondents, we tested an alternate conceptualization of enduring leisure involvement where identity was considered a key driver of other affective and conative outcomes. Rather than existing on the same temporal plane, as has been the tradition in the leisure literature, we observed that identity was an antecedent of the other...

  8. Neural coding of sound envelope structure in songbirds.

    Science.gov (United States)

    Boari, Santiago; Amador, Ana

    2017-12-12

    Songbirds are a well-established animal model to study the neural basis of learning, perception and production of complex vocalizations. In this system, telencephalic neurons in HVC present a state-dependent, highly selective response to auditory presentations of the bird's own song (BOS). This property provides an opportunity to study the neural code behind a complex motor behavior. In this work, we explore whether changes in the temporal structure of the sound envelope can drive changes in the neural responses of highly selective HVC units. We generated an envelope-modified BOS (MOD) by reversing each syllable's envelope but leaving the overall temporal structure of syllable spectra unchanged, which resulted in a subtle modification for each song syllable. We conducted in vivo electrophysiological recordings of HVC neurons in anaesthetized zebra finches (Taeniopygia guttata). Units analyzed presented a high BOS selectivity and lower response to MOD, but preserved the profile response shape. These results show that the temporal evolution of the sound envelope is being sensed by the avian song system and suggest that the biomechanical properties of the vocal apparatus could play a role in enhancing subtle sound differences.

  9. Neural Mechanisms Involved in Hypersensitive Hearing: Helping Children with ASD Who Are Overly Sensitive to Sounds.

    Science.gov (United States)

    Lucker, Jay R; Doman, Alex

    2015-01-01

    Professionals working with children diagnosed with autism spectrum disorder (ASD) may find that these children are overly sensitive to sounds. These professionals are often concerned as to why children may have auditory hypersensitivities. This review article discusses the neural mechanisms identified underlying hypersensitive hearing in people. The authors focus on brain research to support the idea of the nonclassical auditory pathways being involved in connecting the auditory system with the emotional system of the brain. The authors also discuss brain mechanisms felt to be involved in auditory hypersensitivity. The authors conclude with a discussion of some treatments for hypersensitive hearing. These treatments include desensitization training and the use of listening therapies such as The Listening Program.

  10. Neural Mechanisms Involved in Hypersensitive Hearing: Helping Children with ASD Who Are Overly Sensitive to Sounds

    Directory of Open Access Journals (Sweden)

    Jay R. Lucker

    2015-01-01

    Full Text Available Professionals working with children diagnosed with autism spectrum disorder (ASD may find that these children are overly sensitive to sounds. These professionals are often concerned as to why children may have auditory hypersensitivities. This review article discusses the neural mechanisms identified underlying hypersensitive hearing in people. The authors focus on brain research to support the idea of the nonclassical auditory pathways being involved in connecting the auditory system with the emotional system of the brain. The authors also discuss brain mechanisms felt to be involved in auditory hypersensitivity. The authors conclude with a discussion of some treatments for hypersensitive hearing. These treatments include desensitization training and the use of listening therapies such as The Listening Program.

  11. Neural network structure for navigation using potential fields

    Science.gov (United States)

    Plumer, Edward S.

    1992-01-01

    A hybrid-network method for obstacle avoidance in the truck-backing system of D. Nguyen and B. Widrow (1989) is presented. A neural network technique for vehicle navigation and control in the presence of obstacles has been developed. A potential function which peaks at the surface of obstacles and has its minimum at the proper vehicle destination is computed using a network structure. The field is guaranteed not to have spurious local minima and does not have the property of flattening-out far from the goal. A feedforward neural network is used to control the steering of the vehicle using local field information. The network is trained in an obstacle-free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.

  12. Structure Learning for Deep Neural Networks Based on Multiobjective Optimization.

    Science.gov (United States)

    Liu, Jia; Gong, Maoguo; Miao, Qiguang; Wang, Xiaogang; Li, Hao

    2017-05-05

    This paper focuses on the connecting structure of deep neural networks and proposes a layerwise structure learning method based on multiobjective optimization. A model with better generalization can be obtained by reducing the connecting parameters in deep networks. The aim is to find the optimal structure with high representation ability and better generalization for each layer. Then, the visible data are modeled with respect to structure based on the products of experts. In order to mitigate the difficulty of estimating the denominator in PoE, the denominator is simplified and taken as another objective, i.e., the connecting sparsity. Moreover, for the consideration of the contradictory nature between the representation ability and the network connecting sparsity, the multiobjective model is established. An improved multiobjective evolutionary algorithm is used to solve this model. Two tricks are designed to decrease the computational cost according to the properties of input data. The experiments on single-layer level, hierarchical level, and application level demonstrate the effectiveness of the proposed algorithm, and the learned structures can improve the performance of deep neural networks.

  13. Training verb argument structure production in agrammatic aphasia: behavioral and neural recovery patterns.

    Science.gov (United States)

    Thompson, Cynthia K; Riley, Ellyn A; den Ouden, Dirk-Bart; Meltzer-Asscher, Aya; Lukic, Sladjana

    2013-10-01

    Neuroimaging and lesion studies indicate a left hemisphere network for verb and verb argument structure processing, involving both frontal and temporoparietal brain regions. Although their verb comprehension is generally unimpaired, it is well known that individuals with agrammatic aphasia often present with verb production deficits, characterized by an argument structure complexity hierarchy, indicating faulty access to argument structure representations for production and integration into syntactic contexts. Recovery of verb processing in agrammatism, however, has received little attention and no studies have examined the neural mechanisms associated with improved verb and argument structure processing. In the present study we trained agrammatic individuals on verbs with complex argument structure in sentence contexts and examined generalization to verbs with less complex argument structure. The neural substrates of improved verb production were examined using functional magnetic resonance imaging (fMRI). Eight individuals with chronic agrammatic aphasia participated in the study (four experimental and four control participants). Production of three-argument verbs in active sentences was trained using a sentence generation task emphasizing the verb's argument structure and the thematic roles of sentential noun phrases. Before and after training, production of trained and untrained verbs was tested in naming and sentence production and fMRI scans were obtained, using an action naming task. Significant pre- to post-training improvement in trained and untrained (one- and two-argument) verbs was found for treated, but not control, participants, with between-group differences found for verb naming, production of verbs in sentences, and production of argument structure. fMRI activation derived from post-treatment compared to pre-treatment scans revealed upregulation in cortical regions implicated for verb and argument structure processing in healthy controls. Training

  14. Involvement of intraocular structures in disseminated histoplasmosis.

    Science.gov (United States)

    Ala-Kauhaluoma, Marianne; Aho, Inka; Ristola, Matti; Karma, Anni

    2010-06-01

    To describe ocular involvement and response to treatment in a patient with human immunodeficiency virus (HIV) infection with severe progressive disseminated histoplasmosis (PDH). We report a 35-year-old HIV-infected patient seen in our clinics over a period of 4 years. During antiretroviral treatment (ART), the HIV load became undetectable at 3 months; however, CD4 T-cell count increased slowly and rose to 100 cells/microl. Histoplasma capsulatum was cultured from skin pustules, cerebrospinal fluid (CF) and aqueous humour. The patient developed central nervous system (CNS) involvement 2 months and panuveitis in both eyes 4 months after the initiation of ART. With intravenous liposomal amphotericin B followed by oral voricanozole, the chorioretinal lesions of the right eye (RE) became inactivated and magnetic resonance imaging (MRI) lesions of CNS disappeared. Relapse of the inflammation in the anterior segment of the left eye (LE) resulted in a total closure of the chamber angle and severe glaucoma. Despite medical therapy, two cyclophotocoagulations, total vitrectomy and repeated intravitreal amphotericin B injections, LE became blind. Histoplasma capsulatum was cultured from the aqueous humour after antifungal therapy of 16 months' duration. PDH with intraocular and CNS manifestations was probably manifested by an enhanced immune response against a previous subclinical disseminated infection. It seems difficult to eradicate H. capsulatum from the anterior segment of the eye in an immunocompromised patient.

  15. Deep Convolutional Neural Networks: Structure, Feature Extraction and Training

    Directory of Open Access Journals (Sweden)

    Namatēvs Ivars

    2017-12-01

    Full Text Available Deep convolutional neural networks (CNNs are aimed at processing data that have a known network like topology. They are widely used to recognise objects in images and diagnose patterns in time series data as well as in sensor data classification. The aim of the paper is to present theoretical and practical aspects of deep CNNs in terms of convolution operation, typical layers and basic methods to be used for training and learning. Some practical applications are included for signal and image classification. Finally, the present paper describes the proposed block structure of CNN for classifying crucial features from 3D sensor data.

  16. Structural neural substrates of reading the mind in the eyes

    Directory of Open Access Journals (Sweden)

    Wataru eSato

    2016-04-01

    Full Text Available The ability to read the minds of others in their eyes plays an important role in human adaptation to social environments. Behavioral studies have resulted in the development of a test to measure this ability (Reading the Mind in the Eyes Test, revised version; Eyes Test, and have demonstrated that this ability is consistent over time. Although functional neuroimaging studies revealed brain activation while performing the Eyes Test, the structural neural substrates supporting consistent performance on the Eyes Test remain unclear. In this study we assessed the Eyes Test and analyzed structural magnetic resonance images using voxel-based morphometry in healthy participants. Test performance was positively associated with the gray matter volumes of the dorsomedial prefrontal cortex, inferior parietal lobule (temporoparietal junction, and precuneus in the left hemisphere. These results suggest that the fronto-temporoparietal network structures support the consistent ability to read the mind in the eyes.

  17. Self-organization in neural networks - Applications in structural optimization

    Science.gov (United States)

    Hajela, Prabhat; Fu, B.; Berke, Laszlo

    1993-01-01

    The present paper discusses the applicability of ART (Adaptive Resonance Theory) networks, and the Hopfield and Elastic networks, in problems of structural analysis and design. A characteristic of these network architectures is the ability to classify patterns presented as inputs into specific categories. The categories may themselves represent distinct procedural solution strategies. The paper shows how this property can be adapted in the structural analysis and design problem. A second application is the use of Hopfield and Elastic networks in optimization problems. Of particular interest are problems characterized by the presence of discrete and integer design variables. The parallel computing architecture that is typical of neural networks is shown to be effective in such problems. Results of preliminary implementations in structural design problems are also included in the paper.

  18. Understanding the neural mechanisms involved in sensory control of voice production.

    Science.gov (United States)

    Parkinson, Amy L; Flagmeier, Sabina G; Manes, Jordan L; Larson, Charles R; Rogers, Bill; Robin, Donald A

    2012-05-15

    Auditory feedback is important for the control of voice fundamental frequency (F0). In the present study we used neuroimaging to identify regions of the brain responsible for sensory control of the voice. We used a pitch-shift paradigm where subjects respond to an alteration, or shift, of voice pitch auditory feedback with a reflexive change in F0. To determine the neural substrates involved in these audio-vocal responses, subjects underwent fMRI scanning while vocalizing with or without pitch-shifted feedback. The comparison of shifted and unshifted vocalization revealed activation bilaterally in the superior temporal gyrus (STG) in response to the pitch shifted feedback. We hypothesize that the STG activity is related to error detection by auditory error cells located in the superior temporal cortex and efference copy mechanisms whereby this region is responsible for the coding of a mismatch between actual and predicted voice F0. Published by Elsevier Inc.

  19. Is Artificial Neural Network Suitable for Damage Level Determination of Rc- Structures?

    OpenAIRE

    Baltacıoğlu, A. K.; Öztürk, B.; Civalek, Ö.; Akgöz, B.

    2010-01-01

    In the present study, an artificial neural network (ANN) application is introduced for estimation of damage level of reinforced concrete structures. Back-propagation learning algorithm is adopted. A typical neural network architecture is proposed and some conclusions are presented. Applicability of artificial neural network (ANN) for the assessment of earthquake related damage is investigated

  20. Some structural determinants of Pavlovian conditioning in artificial neural networks.

    Science.gov (United States)

    Sánchez, José M; Galeazzi, Juan M; Burgos, José E

    2010-05-01

    This paper investigates the possible role of neuroanatomical features in Pavlovian conditioning, via computer simulations with layered, feedforward artificial neural networks. The networks' structure and functioning are described by a strongly bottom-up model that takes into account the roles of hippocampal and dopaminergic systems in conditioning. Neuroanatomical features were simulated as generic structural or architectural features of neural networks. We focused on the number of units per hidden layer and connectivity. The effect of the number of units per hidden layer was investigated through simulations of resistance to extinction in fully connected networks. Large networks were more resistant to extinction than small networks, a stochastic effect of the asynchronous random procedure used in the simulator to update activations and weights. These networks did not simulate second-order conditioning because weight competition prevented conditioning to a stimulus after conditioning to another. Partially connected networks simulated second-order conditioning and devaluation of the second-order stimulus after extinction of a similar first-order stimulus. Similar stimuli were simulated as nonorthogonal input-vectors. Copyright (c) 2009 Elsevier B.V. All rights reserved.

  1. Anatomical study of lumbar vertebral pedicle and adjacent neural structures

    Directory of Open Access Journals (Sweden)

    Matuoka Cláudia Maria

    2002-01-01

    Full Text Available For the evaluation of the Lumbar pedicle morphometry and its relation to the neural structures, 14 male adult cadavers were dissected, and the size of the lumbar pedicle was assessed by measuring its sagittal and transversal diameter. It was found that the size of the pedicle increases from L2 to L5, both in the sagittal and transversal diameter, the first bigger. The relation of the lumbar pedicle to the neural structures was evaluated by measuring the distance between dura-mater and the pedicle medial area, the distance between the most distal area of the pedicle and the nerve root that appears under it, and , to obtain in an indirect way, the distance between the pedicle apex and the nerve root that appears over it. The acquired results showed that the distance between the most distal area of the pedicle and the nerve root that appears under it, and the distance between the pedicle medial area and dura-mater, do not increase from L2 to L5, and they are in average 1,98 and 3,02 respectively. The distance between the pedicle apex and the nerve root that appears over it, increases from L2 to L5, varying from 13,64 in L2 to 21,62 in L5. The location of the spinal ganglion in relation to the pedicle has also been found, and 87% of the spinal ganglions are located in the foraminal zone.

  2. Structures of Neural Correlation and How They Favor Coding

    Science.gov (United States)

    Franke, Felix; Fiscella, Michele; Sevelev, Maksim; Roska, Botond; Hierlemann, Andreas; da Silveira, Rava Azeredo

    2017-01-01

    Summary The neural representation of information suffers from “noise”—the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using simultaneous recordings from a population of direction-selective retinal ganglion cells, we demonstrate that coding benefits from noise correlations. The effect is appreciable already in small populations, yet it is a collective phenomenon. Furthermore, the stimulus-dependent structure of correlation is key. We develop simple functional models that capture the stimulus-dependent statistics. We then use them to quantify the performance of population coding, which depends upon interplays of feature sensitivities and noise correlations in the population. Because favorable structures of correlation emerge robustly in circuits with noisy, nonlinear elements, they will arise and benefit coding beyond the confines of retina. PMID:26796692

  3. Crystal Structure Representation for Neural Networks using Topological Approach.

    Science.gov (United States)

    Fedorov, Aleksandr V; Shamanaev, Ivan V

    2017-08-01

    In the present work we describe a new approach, which uses topology of crystals for physicochemical properties prediction using artificial neural networks (ANN). The topologies of 268 crystal structures were determined using ToposPro software. Quotient graphs were used to identify topological centers and their neighbors. The topological approach was illustrated by training ANN to predict molar heat capacity, standard molar entropy and lattice energy of 268 crystals with different compositions and structures (metals, inorganic salts, oxides, etc.). ANN was trained using Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Mean absolute percentage error of predicted properties was ≤8 %. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Simulation of morphologically structured photo-thermal neural stimulation

    Science.gov (United States)

    Weissler, Y.; Farah, N.; Shoham, S.

    2017-10-01

    Objective. Rational design of next-generation techniques for photo-thermal excitation requires the development of tools capable of modeling the effects of spatially- and temporally-dependent temperature distribution on cellular neuronal structures. Approach. We present a new computer simulation tool for predicting the effects of arbitrary spatiotemporally-structured photo-thermal stimulation on 3D, morphologically realistic neurons. The new simulation tool is based on interfacing two generic platforms, NEURON and MATLAB and is therefore suited for capturing different kinds of stimuli and neural models. Main results. Simulation results are validated using photo-absorber induced neuro-thermal stimulation (PAINTS) empirical results, and advanced features are explored. Significance. The new simulation tool could have an important role in understanding and investigating complex optical stimulation at the single-cell and network levels.

  5. Perfusion imaging in Pusher syndrome to investigate the neural substrates involved in controlling upright body position.

    Directory of Open Access Journals (Sweden)

    Luca Francesco Ticini

    Full Text Available Brain damage may induce a dysfunction of upright body position termed "pusher syndrome". Patients with such disorder suffer from an alteration of their sense of body verticality. They experience their body as oriented upright when actually tilted nearly 20 degrees to the ipsilesional side. Pusher syndrome typically is associated with posterior thalamic stroke; less frequently with extra-thalamic lesions. This argued for a fundamental role of these structures in our control of upright body posture. Here we investigated whether such patients may show additional functional or metabolic abnormalities outside the areas of brain lesion. We investigated 19 stroke patients with thalamic or with extra-thalamic lesions showing versus not showing misperception of body orientation. We measured fluid-attenuated inversion-recovery (FLAIR imaging, diffusion-weighted imaging (DWI, and perfusion-weighted imaging (PWI. This allowed us to determine the structural damage as well as to identify the malperfused but structural intact tissue. Pusher patients with thalamic lesions did not show dysfunctional brain areas in addition to the ones found to be structurally damaged. In the pusher patients with extra-thalamic lesions, the thalamus was neither structurally damaged nor malperfused. Rather, these patients showed small regions of abnormal perfusion in the structurally intact inferior frontal gyrus, middle temporal gyrus, inferior parietal lobule, and parietal white matter. The results indicate that these extra-thalamic brain areas contribute to the network controlling upright body posture. The data also suggest that damage of the neural tissue in the posterior thalamus itself rather than additional malperfusion in distant cortical areas is associated with pusher syndrome. Hence, it seems as if the normal functioning of both extra-thalamic as well as posterior thalamic structures is integral to perceiving gravity and controlling upright body orientation in humans.

  6. Neural networks for harmonic structure in music perception and action.

    Science.gov (United States)

    Bianco, R; Novembre, G; Keller, P E; Kim, Seung-Goo; Scharf, F; Friederici, A D; Villringer, A; Sammler, D

    2016-11-15

    The ability to predict upcoming structured events based on long-term knowledge and contextual priors is a fundamental principle of human cognition. Tonal music triggers predictive processes based on structural properties of harmony, i.e., regularities defining the arrangement of chords into well-formed musical sequences. While the neural architecture of structure-based predictions during music perception is well described, little is known about the neural networks for analogous predictions in musical actions and how they relate to auditory perception. To fill this gap, expert pianists were presented with harmonically congruent or incongruent chord progressions, either as musical actions (photos of a hand playing chords) that they were required to watch and imitate without sound, or in an auditory format that they listened to without playing. By combining task-based functional magnetic resonance imaging (fMRI) with functional connectivity at rest, we identified distinct sub-regions in right inferior frontal gyrus (rIFG) interconnected with parietal and temporal areas for processing action and audio sequences, respectively. We argue that the differential contribution of parietal and temporal areas is tied to motoric and auditory long-term representations of harmonic regularities that dynamically interact with computations in rIFG. Parsing of the structural dependencies in rIFG is co-determined by both stimulus- or task-demands. In line with contemporary models of prefrontal cortex organization and dual stream models of visual-spatial and auditory processing, we show that the processing of musical harmony is a network capacity with dissociated dorsal and ventral motor and auditory circuits, which both provide the infrastructure for predictive mechanisms optimising action and perception performance. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Neural Network Enhanced Structure Determination of Osteoporosis, Immune System, and Radiation Repair Proteins Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed innovation will utilize self learning neural network technology to determine the structure of osteoporosis, immune system disease, and excess radiation...

  8. Artificial neural networks aided conceptual stage design of water harvesting structures

    Directory of Open Access Journals (Sweden)

    Vinay Chandwani

    2016-09-01

    Full Text Available The paper presents artificial neural networks (ANNs based methodology for ascertaining the structural parameters of water harvesting structures (WHS at the conceptual stage of design. The ANN is trained using exemplar patterns generated using an in-house MSExcel based design program, to draw a functional relationship between the five inputs design parameters namely, peak flood discharge, safe bearing capacity of strata, length of structure, height of structure and silt factor and four outputs namely, top width, bottom width, foundation depth and flood lift representing the structural parameters of WHS. The results of the study show that, the structural parameters of the WHS predicted using ANN model are in close agreement with the actual field parameters. The versatility of ANN to map complex or complex unknown relationships has been proven in the study. A parametric sensitivity study is also performed to assess the most significant design parameter. The study holistically presents a neural network based decision support tool that can be used to accurately estimate the major design parameters of the WHS at the conceptual stage of design in quick time, aiding the engineer-in-charge to conveniently forecast the budget requirements and minimize the labor involved during the subsequent phases of analysis and design.

  9. Neural Correlates of Successful and Unsuccessful Strategical Mechanisms Involved in Uncertain Decision-Making.

    Directory of Open Access Journals (Sweden)

    Julie Giustiniani

    Full Text Available The ability to develop successful long-term strategies in uncertain situations relies on complex neural mechanisms. Although lesion studies have shown some of the mechanisms involved, it is still unknown why some healthy subjects are able to make the right decision whereas others are not. The aim of our study was to investigate neurophysiological differences underlying this ability to develop a successful strategy in a group of healthy subjects playing a monetary card game called the Iowa Gambling Task (IGT. In this task, subjects have to win and earn money by choosing between four decks of cards, two were advantageous in the long term and two disadvantageous. Twenty healthy right-handed subjects performed the IGT while their cerebral activity was recorded by electroencephalography. Based on their behavioral performances, two groups of subjects could clearly be distinguished: one who selected the good decks and thus succeeded in developing a Favorable strategy (9 subjects and one who remained Undecided (11 subjects. No neural difference was found between each group before the selection of a deck, but in both groups a greater negativity was found emerging from the right superior frontal gyrus 600 ms before a disadvantageous selection. During the processing of the feedback, an attenuation of the P200 and P300 waveforms was found for the Undecided group, and a P300 originating from the medial frontal gyrus was found in response to a loss only in the Favorable group. Our results suggest that undecided subjects are hyposensitive to the valence of the cards during gambling, which affects the feedback processing.

  10. Neural Correlates of Successful and Unsuccessful Strategical Mechanisms Involved in Uncertain Decision-Making.

    Science.gov (United States)

    Giustiniani, Julie; Gabriel, Damien; Nicolier, Magali; Monnin, Julie; Haffen, Emmanuel

    2015-01-01

    The ability to develop successful long-term strategies in uncertain situations relies on complex neural mechanisms. Although lesion studies have shown some of the mechanisms involved, it is still unknown why some healthy subjects are able to make the right decision whereas others are not. The aim of our study was to investigate neurophysiological differences underlying this ability to develop a successful strategy in a group of healthy subjects playing a monetary card game called the Iowa Gambling Task (IGT). In this task, subjects have to win and earn money by choosing between four decks of cards, two were advantageous in the long term and two disadvantageous. Twenty healthy right-handed subjects performed the IGT while their cerebral activity was recorded by electroencephalography. Based on their behavioral performances, two groups of subjects could clearly be distinguished: one who selected the good decks and thus succeeded in developing a Favorable strategy (9 subjects) and one who remained Undecided (11 subjects). No neural difference was found between each group before the selection of a deck, but in both groups a greater negativity was found emerging from the right superior frontal gyrus 600 ms before a disadvantageous selection. During the processing of the feedback, an attenuation of the P200 and P300 waveforms was found for the Undecided group, and a P300 originating from the medial frontal gyrus was found in response to a loss only in the Favorable group. Our results suggest that undecided subjects are hyposensitive to the valence of the cards during gambling, which affects the feedback processing.

  11. Successful dieters have increased neural activity in cortical areas involved in the control of behavior.

    Science.gov (United States)

    DelParigi, A; Chen, K; Salbe, A D; Hill, J O; Wing, R R; Reiman, E M; Tataranni, P A

    2007-03-01

    To investigate whether dietary restraint, a landmark of successful dieting, is associated with specific patterns of brain responses to the sensory experience of food and meal consumption. Cross-sectional study of the brain's response to the sensory experience of food and meal consumption in nine successful dieters (age: 38+/-7 years, body fat (%): 28+/-3) and 20 non-dieters (age: 31+/-9 years, body fat (%): 33+/-9), all women. Changes in brain activity in response to the sensory experience of food and meal consumption were assessed by using positron emission tomography and (15)O water as a radiotracer. Body fatness was assessed by dual X-ray absorptiometry. Subjective ratings of hunger and fullness were measured by visual analogue scale. Dietary restraint, disinhibition and hunger were assessed by the Three Factor Eating Questionnaire. Successful dieters had a significantly higher level of dietary restraint compared to non-dieters. In response to meal consumption, successful dieters had a greater activation in the dorsal prefrontal cortex (DPFC), dorsal striatum and anterior cerebellar lobe as compared to non-dieters. In response to the same stimulation, the orbitofrontal cortex (OFC) was significantly more activated in non-dieters as compared to successful dieters. Dietary restraint was positively correlated with the response in the DPFC and negatively with the response in the OFC. The responses in the DPFC and OFC were negatively intercorrelated. Cortical areas involved in controlling inappropriate behavioral responses, such as the DPFC, are particularly activated in successful dieters in response to meal consumption. The association between the degree of dietary restraint and the coordinated neural changes in the DPFC and OFC raises the possibility that cognitive control of food intake is achieved by modulating neural circuits controlling food reward.

  12. Neural systems supporting linguistic structure, linguistic experience, and symbolic communication in sign language and gesture.

    Science.gov (United States)

    Newman, Aaron J; Supalla, Ted; Fernandez, Nina; Newport, Elissa L; Bavelier, Daphne

    2015-09-15

    Sign languages used by deaf communities around the world possess the same structural and organizational properties as spoken languages: In particular, they are richly expressive and also tightly grammatically constrained. They therefore offer the opportunity to investigate the extent to which the neural organization for language is modality independent, as well as to identify ways in which modality influences this organization. The fact that sign languages share the visual-manual modality with a nonlinguistic symbolic communicative system-gesture-further allows us to investigate where the boundaries lie between language and symbolic communication more generally. In the present study, we had three goals: to investigate the neural processing of linguistic structure in American Sign Language (using verbs of motion classifier constructions, which may lie at the boundary between language and gesture); to determine whether we could dissociate the brain systems involved in deriving meaning from symbolic communication (including both language and gesture) from those specifically engaged by linguistically structured content (sign language); and to assess whether sign language experience influences the neural systems used for understanding nonlinguistic gesture. The results demonstrated that even sign language constructions that appear on the surface to be similar to gesture are processed within the left-lateralized frontal-temporal network used for spoken languages-supporting claims that these constructions are linguistically structured. Moreover, although nonsigners engage regions involved in human action perception to process communicative, symbolic gestures, signers instead engage parts of the language-processing network-demonstrating an influence of experience on the perception of nonlinguistic stimuli.

  13. Fuzzy stochastic neural network model for structural system identification

    Science.gov (United States)

    Jiang, Xiaomo; Mahadevan, Sankaran; Yuan, Yong

    2017-01-01

    This paper presents a dynamic fuzzy stochastic neural network model for nonparametric system identification using ambient vibration data. The model is developed to handle two types of imprecision in the sensed data: fuzzy information and measurement uncertainties. The dimension of the input vector is determined by using the false nearest neighbor approach. A Bayesian information criterion is applied to obtain the optimum number of stochastic neurons in the model. A fuzzy C-means clustering algorithm is employed as a data mining tool to divide the sensed data into clusters with common features. The fuzzy stochastic model is created by combining the fuzzy clusters of input vectors with the radial basis activation functions in the stochastic neural network. A natural gradient method is developed based on the Kullback-Leibler distance criterion for quick convergence of the model training. The model is validated using a power density pseudospectrum approach and a Bayesian hypothesis testing-based metric. The proposed methodology is investigated with numerically simulated data from a Markov Chain model and a two-story planar frame, and experimentally sensed data from ambient vibration data of a benchmark structure.

  14. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Science.gov (United States)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  15. Thalamic Multisensory integration: Creating a neural network map of involved brain areas in music perception, processing and execution

    NARCIS (Netherlands)

    Jaschke, A.C.; Scherder, E.J.A.

    2013-01-01

    Music activates a wide array of neural areas involved in different functions besides the perception, processing and execution of music itself. Understanding musical processes in the brain has had multiple implications in the neuro- and health sciences. Engaging the brain with a multisensory stimulus

  16. Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

    Science.gov (United States)

    Nitta, Tohru

    2017-10-01

    We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

  17. Let7a involves in neural stem cell differentiation relating with TLX level

    Energy Technology Data Exchange (ETDEWEB)

    Song, Juhyun [Department of Anatomy, Yonsei University College of Medicine, Seoul (Korea, Republic of); Cho, Kyoung Joo; Oh, Yumi [Department of Anatomy, Yonsei University College of Medicine, Seoul (Korea, Republic of); BK21 Plus Project for Medical Sciences, and Brain Research Institute, Yonsei University College of Medicine, Seoul (Korea, Republic of); Lee, Jong Eun, E-mail: jelee@yuhs.ac [Department of Anatomy, Yonsei University College of Medicine, Seoul (Korea, Republic of); BK21 Plus Project for Medical Sciences, and Brain Research Institute, Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2015-07-10

    Neural stem cells (NSCs) have the potential for differentiation into neurons known as a groundbreaking therapeutic solution for central nervous system (CNS) diseases. To resolve the therapeutic efficiency of NSCs, recent researchers have focused on the study on microRNA's role in CNS. Some micro RNAs have been reported significant functions in NSC self-renewal and differentiation through the post-transcriptional regulation of neurogenesis genes. MicroRNA-Let7a (Let7a) has known as the regulator of diverse cellular mechanisms including cell differentiation and proliferation. In present study, we investigated whether Let7a regulates NSC differentiation by targeting the nuclear receptor TLX, which is an essential regulator of NSC self-renewal, proliferation and differentiation. We performed the following experiments: western blot analysis, TaqMan assay, RT-PCR, and immunocytochemistry to confirm the alteration of NSCs. Our data showed that let7a play important roles in controlling NSC fate determination. Thus, manipulating Let-7A and TLX could be a novel strategy to enhance the efficiency of NSC's neuronal differentiation for CNS disorders. - Highlights: • Let7a influences on NSC differentiation and proliferation. • Let7a involves in mainly NSC differentiation rather than proliferation. • Let7a positively regulates the TLX expression.

  18. Nrf2/ARE Pathway Involved in Oxidative Stress Induced by Paraquat in Human Neural Progenitor Cells

    Directory of Open Access Journals (Sweden)

    Tingting Dou

    2016-01-01

    Full Text Available Compelling evidences have shown that diverse environmental insults arising during early life can either directly lead to a reduction in the number of dopaminergic neurons or cause an increased susceptibility to neurons degeneration with subsequent environmental insults or with aging alone. Oxidative stress is considered the main effect of neurotoxins exposure. In this study, we investigated the oxidative stress effect of Paraquat (PQ on immortalized human embryonic neural progenitor cells by treating them with various concentrations of PQ. We show that PQ can decrease the activity of SOD and CAT but increase MDA and LDH level. Furthermore, the activities of Cyc and caspase-9 were found increased significantly at 10 μM of PQ treatment. The cytoplasmic Nrf2 protein expressions were upregulated at 10 μM but fell back at 100 μM. The nuclear Nrf2 protein expressions were upregulated as well as the downstream mRNA expressions of HO-1 and NQO1 in a dose-dependent manner. In addition, the proteins expression of PKC and CKII was also increased significantly even at 1 μM. The results suggested that Nrf2/ARE pathway is involved in mild to moderate PQ-induced oxidative stress which is evident from dampened Nrf2 activity and low expression of antioxidant genes in PQ induced oxidative damage.

  19. Learning Orthographic Structure With Sequential Generative Neural Networks.

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-04-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

  20. Z(2) gauge neural network and its phase structure

    Science.gov (United States)

    Takafuji, Yusuke; Nakano, Yuki; Matsui, Tetsuo

    2012-11-01

    We study general phase structures of neural-network models that have Z(2) local gauge symmetry. The Z(2) spin variable Si=±1 on the i-th site describes a neuron state as in the Hopfield model, and the Z(2) gauge variable J=±1 describes a state of the synaptic connection between j-th and i-th neurons. The gauge symmetry allows for a self-coupling energy among J’s such as JJJ, which describes reverberation of signals. Explicitly, we consider the three models; (I) an annealed model with full and partial connections of J, (II) a quenched model with full connections where J is treated as a slow quenched variable, and (III) a quenched three-dimensional lattice model with the nearest-neighbor connections. By numerical simulations, we examine their phase structures paying attention to the effect of the reverberation term, and compare them with each other and with the annealed 3D lattice model which has been studied beforehand. By noting the dependence of thermodynamic quantities upon the total number of sites and the connectivity among sites, we obtain a coherent interpretation to understand these results. Among other things, we find that the Higgs phase of the annealed model is separated into two stable spin-glass phases in the quenched models (II) and (III).

  1. Cognitive processes involved in smooth pursuit eye movements: behavioral evidence, neural substrate and clinical correlation

    Directory of Open Access Journals (Sweden)

    Kikuro eFukushima

    2013-03-01

    Full Text Available Smooth-pursuit eye movements allow primates to track moving objects. Efficient pursuit requires appropriate target selection and predictive compensation for inherent processing delays. Prediction depends on expectation of future object motion, storage of motion information and use of extra-retinal mechanisms in addition to visual feedback. We present behavioural evidence of how cognitive processes are involved in predictive pursuit in normal humans and then describe neuronal responses in monkeys and behavioural responses in patients using a new technique to test these cognitive controls. The new technique examines the neural substrate of working memory and movement preparation for predictive pursuit by using a memory-based task in macaque monkeys trained to pursue (go or not pursue (no-go according to a go/no-go cue, in a direction based on memory of a previously presented visual motion display. Single-unit task-related neuronal activity was examined in medial superior temporal cortex (MST, supplementary eye fields (SEF, caudal frontal eye fields (FEF, cerebellar dorsal vermis lobules VI-VII, caudal fastigial nuclei (cFN, and floccular region. Neuronal activity reflecting working memory of visual motion direction and go/no-go selection was found predominantly in SEF, cerebellar dorsal vermis and cFN, whereas movement preparation related signals were found predominantly in caudal FEF and the same cerebellar areas. Chemical inactivation produced effects consistent with differences in signals represented in each area. When applied to patients with Parkinson's disease, the task revealed deficits in movement preparation but not working memory. In contrast, patients with frontal cortical or cerebellar dysfunction had high error rates, suggesting impaired working memory. We show how neuronal activity may be explained by models of retinal and extra-retinal interaction in target selection and predictive control and thus aid understanding of underlying

  2. Cognitive processes involved in smooth pursuit eye movements: behavioral evidence, neural substrate and clinical correlation.

    Science.gov (United States)

    Fukushima, Kikuro; Fukushima, Junko; Warabi, Tateo; Barnes, Graham R

    2013-01-01

    Smooth-pursuit eye movements allow primates to track moving objects. Efficient pursuit requires appropriate target selection and predictive compensation for inherent processing delays. Prediction depends on expectation of future object motion, storage of motion information and use of extra-retinal mechanisms in addition to visual feedback. We present behavioral evidence of how cognitive processes are involved in predictive pursuit in normal humans and then describe neuronal responses in monkeys and behavioral responses in patients using a new technique to test these cognitive controls. The new technique examines the neural substrate of working memory and movement preparation for predictive pursuit by using a memory-based task in macaque monkeys trained to pursue (go) or not pursue (no-go) according to a go/no-go cue, in a direction based on memory of a previously presented visual motion display. Single-unit task-related neuronal activity was examined in medial superior temporal cortex (MST), supplementary eye fields (SEF), caudal frontal eye fields (FEF), cerebellar dorsal vermis lobules VI-VII, caudal fastigial nuclei (cFN), and floccular region. Neuronal activity reflecting working memory of visual motion direction and go/no-go selection was found predominantly in SEF, cerebellar dorsal vermis and cFN, whereas movement preparation related signals were found predominantly in caudal FEF and the same cerebellar areas. Chemical inactivation produced effects consistent with differences in signals represented in each area. When applied to patients with Parkinson's disease (PD), the task revealed deficits in movement preparation but not working memory. In contrast, patients with frontal cortical or cerebellar dysfunction had high error rates, suggesting impaired working memory. We show how neuronal activity may be explained by models of retinal and extra-retinal interaction in target selection and predictive control and thus aid understanding of underlying

  3. Cognitive processes involved in smooth pursuit eye movements: behavioral evidence, neural substrate and clinical correlation

    Science.gov (United States)

    Fukushima, Kikuro; Fukushima, Junko; Warabi, Tateo; Barnes, Graham R.

    2013-01-01

    Smooth-pursuit eye movements allow primates to track moving objects. Efficient pursuit requires appropriate target selection and predictive compensation for inherent processing delays. Prediction depends on expectation of future object motion, storage of motion information and use of extra-retinal mechanisms in addition to visual feedback. We present behavioral evidence of how cognitive processes are involved in predictive pursuit in normal humans and then describe neuronal responses in monkeys and behavioral responses in patients using a new technique to test these cognitive controls. The new technique examines the neural substrate of working memory and movement preparation for predictive pursuit by using a memory-based task in macaque monkeys trained to pursue (go) or not pursue (no-go) according to a go/no-go cue, in a direction based on memory of a previously presented visual motion display. Single-unit task-related neuronal activity was examined in medial superior temporal cortex (MST), supplementary eye fields (SEF), caudal frontal eye fields (FEF), cerebellar dorsal vermis lobules VI–VII, caudal fastigial nuclei (cFN), and floccular region. Neuronal activity reflecting working memory of visual motion direction and go/no-go selection was found predominantly in SEF, cerebellar dorsal vermis and cFN, whereas movement preparation related signals were found predominantly in caudal FEF and the same cerebellar areas. Chemical inactivation produced effects consistent with differences in signals represented in each area. When applied to patients with Parkinson's disease (PD), the task revealed deficits in movement preparation but not working memory. In contrast, patients with frontal cortical or cerebellar dysfunction had high error rates, suggesting impaired working memory. We show how neuronal activity may be explained by models of retinal and extra-retinal interaction in target selection and predictive control and thus aid understanding of underlying

  4. Classification of crystal structure using a convolutional neural network.

    Science.gov (United States)

    Park, Woon Bae; Chung, Jiyong; Jung, Jaeyoung; Sohn, Keemin; Singh, Satendra Pal; Pyo, Myoungho; Shin, Namsoo; Sohn, Kee-Sun

    2017-07-01

    A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN architecture was obtained that allowed determination of the crystal system, extinction group and space group. In sharp contrast with the traditional use of powder XRD pattern analysis, the CNN never treats powder XRD patterns as a deconvoluted and discrete peak position or as intensity data, but instead the XRD patterns are regarded as nothing but a pattern similar to a picture. The CNN interprets features that humans cannot recognize in a powder XRD pattern. As a result, accuracy levels of 81.14, 83.83 and 94.99% were achieved for the space-group, extinction-group and crystal-system classifications, respectively. The well trained CNN was then used for symmetry identification of unknown novel inorganic compounds.

  5. The relevance of network micro-structure for neural dynamics

    Directory of Open Access Journals (Sweden)

    Volker ePernice

    2013-06-01

    Full Text Available The activity of cortical neurons is determined by the input they receive from presynaptic neurons. Many previousstudies have investigated how specific aspects of the statistics of the input affect the spike trains of single neurons and neuronsin recurrent networks. However, typically very simple random network models are considered in such studies. Here weuse a recently developed algorithm to construct networks based on a quasi-fractal probability measure which are much morevariable than commonly used network models, and which therefore promise to sample the space of recurrent networks ina more exhaustive fashion than previously possible. We use the generated graphs as the underlying network topology insimulations of networks of integrate-and-fire neurons in an asynchronous and irregular state. Based on an extensive datasetof networks and neuronal simulations we assess statistical relations between features of the network structure and the spikingactivity. Our results highlight the strong influence that some details of the network structure have on the activity dynamics ofboth single neurons and populations, even if some global network parameters are kept fixed. We observe specific and consistentrelations between activity characteristics like spike-train irregularity or correlations and network properties, for example thedistributions of the numbers of in- and outgoing connections or clustering. Exploiting these relations, we demonstrate that itis possible to estimate structural characteristics of the network from activity data. We also assess higher order correlationsof spiking activity in the various networks considered here, and find that their occurrence strongly depends on the networkstructure. These results provide directions for further theoretical studies on recurrent networks, as well as new ways to interpretspike train recordings from neural circuits.

  6. Structuring User Involvement in Panel-Based Living Labs

    Directory of Open Access Journals (Sweden)

    Lieven De Marez

    2012-09-01

    Full Text Available A shift towards open innovation approaches with systematic user involvement has occurred within media and ICT. One of the emerging frameworks structuring these initiatives is the "living lab" approach. Despite the growing evidence of the beneficial nature of customer involvement in product development, research into specific user characteristics for innovation is still scarce, particularly in living labs, with the notable exception of literature on lead users. Especially within the context of living labs for ICT and media innovation, an application of the lead-user framework looks promising as a way to structure and facilitate user involvement. This article is based on the experiences of three Flemish living lab initiatives with a panel-based approach and provides a customer characteristics framework that guides user involvement in living labs.

  7. Involvement of Neptune in induction of the hatching gland and neural crest in the Xenopus embryo.

    Science.gov (United States)

    Kurauchi, Takayuki; Izutsu, Yumi; Maéno, Mitsugu

    2010-01-01

    Neptune, a Krüppel-like transcription factor, is expressed in various regions of the developing Xenopus embryo and it has multiple functions in the process of development in various organs. In situ hybridization analysis showed that Neptune is expressed in the boundary region between neural and non-neural tissues at the neurula stage, but little is known about the function of Neptune in this region. Here, we examined the expression and function of Neptune in the neural plate border (NPB) in the Xenopus embryo. Depletion of Neptune protein in developing embryos by using antisense MO caused loss of the hatching gland and otic vesicle as well as malformation of neural crest-derived cranial cartilages and melanocytes. Neptune MO also suppressed the expression of hatching gland and neural crest markers such as he, snail2, sox9 and msx1 at the neurula stage. Subsequent experiments showed that Neptune is necessary and sufficient for the differentiation of hatching gland cells and that it is located downstream of pax3 in the signal regulating the differentiation of these cells. Thus, Neptune is a new member of hatching gland specifier and plays a physiological role in determination and specification of multiple lineages derived from the NPB region.

  8. Involvement of crosstalk between Oct4 and Meis1a in neural cell fate decision.

    Directory of Open Access Journals (Sweden)

    Takeyuki Yamada

    Full Text Available Oct4 plays a critical role both in maintaining pluripotency and the cell fate decision of embryonic stem (ES cells. Nonetheless, in the determination of the neuroectoderm (NE from ES cells, the detailed regulation mechanism of the Oct4 gene expression is poorly understood. Here, we report that crosstalk between Oct4 and Meis1a, a Pbx-related homeobox protein, is required for neural differentiation of mouse P19 embryonic carcinoma (EC cells induced by retinoic acid (RA. During neural differentiation, Oct4 expression was transiently enhanced during 6-12 h of RA addition and subsequently disappeared within 48 h. Coinciding with up-regulation of Oct4 expression, the induction of Meis1a expression was initiated and reached a plateau at 48 h, suggesting that transiently induced Oct4 activates Meis1a expression and the up-regulated Meis1a then suppresses Oct4 expression. Chromatin immunoprecipitation (ChIP and luciferase reporter analysis showed that Oct4 enhanced Meis1a expression via direct binding to the Meis1 promoter accompanying histone H3 acetylation and appearance of 5-hydoxymethylcytosine (5hmC, while Meis1a suppressed Oct4 expression via direct association with the Oct4 promoter together with histone deacetylase 1 (HDAC1. Furthermore, ectopic Meis1a expression promoted neural differentiation via formation of large neurospheres that expressed Nestin, GLAST, BLBP and Sox1 as neural stem cell (NSC/neural progenitor markers, whereas its down-regulation generated small neurospheres and repressed neural differentiation. Thus, these results imply that crosstalk between Oct4 and Meis1a on mutual gene expressions is essential for the determination of NE from EC cells.

  9. Interactive extraction of neural structures with user-guided morphological diffusion

    KAUST Repository

    Yong Wan,

    2012-10-01

    Extracting neural structures with their fine details from confocal volumes is essential to quantitative analysis in neurobiology research. Despite the abundance of various segmentation methods and tools, for complex neural structures, both manual and semi-automatic methods are ine ective either in full 3D or when user interactions are restricted to 2D slices. Novel interaction techniques and fast algorithms are demanded by neurobiologists to interactively and intuitively extract neural structures from confocal data. In this paper, we present such an algorithm-technique combination, which lets users interactively select desired structures from visualization results instead of 2D slices. By integrating the segmentation functions with a confocal visualization tool neurobiologists can easily extract complex neural structures within their typical visualization workflow.

  10. Effect of a structured course involving goal management training

    NARCIS (Netherlands)

    Van Hooren, Susan; Valentijn, Susanne; Bosma, Hans; Ponds, Rudolf; Van Boxtel, Martin; Levine, Brian; Robertson, Ian; Jolles, Jelle

    2010-01-01

    Objective: The objective of this study was to investigate the effects of a structured 6-week neuropsychological course on the executive functioning of older adults with cognitive complaints. Methods: A randomised controlled design was used involving 69 community dwelling individuals aged 55 years

  11. STAT3 signal that mediates the neural plasticity is involved in willed-movement training in focal ischemic rats.

    Science.gov (United States)

    Tang, Qing-Ping; Shen, Qin; Wu, Li-Xiang; Feng, Xiang-Ling; Liu, Hui; Wu, Bei; Huang, Xiao-Song; Wang, Gai-Qing; Li, Zhong-Hao; Liu, Zun-Jing

    2016-07-01

    Willed-movement training has been demonstrated to be a promising approach to increase motor performance and neural plasticity in ischemic rats. However, little is known regarding the molecular signals that are involved in neural plasticity following willed-movement training. To investigate the potential signals related to neural plasticity following willed-movement training, littermate rats were randomly assigned into three groups: middle cerebral artery occlusion, environmental modification, and willed-movement training. The infarct volume was measured 18 d after occlusion of the right middle cerebral artery. Reverse transcription-polymerase chain reaction (PCR) and immunofluorescence staining were used to detect the changes in the signal transducer and activator of transcription 3 (STAT3) mRNA and protein, respectively. A chromatin immunoprecipitation was used to investigate whether STAT3 bound to plasticity-related genes, such as brain-derived neurotrophic factor (BDNF), synaptophysin, and protein interacting with C kinase 1 (PICK1). In this study, we demonstrated that STAT3 mRNA and protein were markedly increased following 15-d willed-movement training in the ischemic hemispheres of the treated rats. STAT3 bound to BDNF, PICK1, and synaptophysin promoters in the neocortical cells of rats. These data suggest that the increased STAT3 levels after willed-movement training might play critical roles in the neural plasticity by directly regulating plasticity-related genes.

  12. Social discounting involves modulation of neural value signals by temporoparietal junction

    Science.gov (United States)

    Strombach, Tina; Weber, Bernd; Hangebrauk, Zsofia; Kenning, Peter; Karipidis, Iliana I.; Tobler, Philippe N.; Kalenscher, Tobias

    2015-01-01

    Most people are generous, but not toward everyone alike: generosity usually declines with social distance between individuals, a phenomenon called social discounting. Despite the pervasiveness of social discounting, social distance between actors has been surprisingly neglected in economic theory and neuroscientific research. We used functional magnetic resonance imaging (fMRI) to study the neural basis of this process to understand the neural underpinnings of social decision making. Participants chose between selfish and generous alternatives, yielding either a large reward for the participant alone, or smaller rewards for the participant and another individual at a particular social distance. We found that generous choices engaged the temporoparietal junction (TPJ). In particular, the TPJ activity was scaled to the social-distance–dependent conflict between selfish and generous motives during prosocial choice, consistent with ideas that the TPJ promotes generosity by facilitating overcoming egoism bias. Based on functional coupling data, we propose and provide evidence for a biologically plausible neural model according to which the TPJ supports social discounting by modulating basic neural value signals in the ventromedial prefrontal cortex to incorporate social-distance–dependent other-regarding preferences into an otherwise exclusively own-reward value representation. PMID:25605887

  13. Differentiation of Neural Stem Cells into Oligodendrocytes : Involvement of the Polycomb Group Protein Ezh2

    NARCIS (Netherlands)

    Sher, Falak; Rossler, Reinhard; Brouwer, Nieske; Balasubramaniyan, Veerakumar; Boddeke, Erik; Copray, Sjef

    2008-01-01

    The mechanisms underlying the regulation of neural stem cell (NSC) renewal and maintenance of their multipotency are still not completely understood. Self-renewal of stem cells in general implies repression of genes that encode for cell lineage differentiation. Enhancer of zeste homolog 2 (Ezh2) is

  14. Jarid1b targets genes regulating development and is involved in neural differentiation

    DEFF Research Database (Denmark)

    Schmitz, Sandra U; Albert, Mareike; Malatesta, Martina

    2011-01-01

    -renewal and differentiation is just starting to emerge. Here, we show that the H3K4me2/3 histone demethylase Jarid1b (Kdm5b/Plu1) is dispensable for ESC self-renewal, but essential for ESC differentiation along the neural lineage. By genome-wide location analysis, we demonstrate that Jarid1b localizes predominantly...

  15. Neural Plasticity Is Involved in Physiological Sleep, Depressive Sleep Disturbances, and Antidepressant Treatments

    OpenAIRE

    Meng-Qi Zhang; Rui Li; Yi-Qun Wang; Zhi-Li Huang

    2017-01-01

    Depression, which is characterized by a pervasive and persistent low mood and anhedonia, greatly impacts patients, their families, and society. The associated and recurring sleep disturbances further reduce patient’s quality of life. However, therapeutic sleep deprivation has been regarded as a rapid and robust antidepressant treatment for several decades, which suggests a complicated role of sleep in development of depression. Changes in neural plasticity are observed during physiological sl...

  16. Neural fuzzy digital filtering: multivariate identifier filters involving multiple inputs and multiple outputs (MIMO

    Directory of Open Access Journals (Sweden)

    Juan Carlos García Infante

    2011-01-01

    Full Text Available  Multivariate identifier filters (multiple inputs and multiple outputs - MIMO are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948. This paper considers the MIMO digital filter model using neuro fuzzy digital filtering to find an adaptive  parameter matrix which is integrated into the Kalman filter by the transition matrix. The filter uses the neural network as back-propagation into the fuzzy mechanism to do this, interpreting its variables and its respective levels and selecting the best values for automatically adjusting transition matrix values. The Matlab simulation describes the neural fuzzy digital filter giving an approximation of exponential convergence seen in functional error. 

  17. Family structure, nonresident father involvement, and adolescent eating patterns.

    Science.gov (United States)

    Stewart, Susan D; Menning, Chadwick L

    2009-08-01

    To examine the relationship between family structure, nonresident father involvement, and adolescent eating patterns. Analyses were performed on data from Waves 1 and 2 of the National Longitudinal Study of Adolescent Health (Wave 1, N = approximately 15,550; Wave 2, N = approximately 11,540), and a subsample of adolescents from each wave who had a nonresident father (Wave 1, N = approximately 3,745; Wave 2, N = 2,358). Multivariate regression provides estimates of the independent effects of family structure and nonresident father involvement on adolescent eating patterns while controlling for potentially confounding sociodemographic characteristics. Compared with children in traditional households (i.e., two biological or adoptive parents), adolescents in nontraditional family households (single parent, step-parent, no parent) were more likely to display unhealthy eating habits such as skipping breakfast and lunch, eating fewer vegetables, consuming more fast food, and had less parental monitoring of meals. Nonresident father involvement was associated with an increased frequency of eating breakfast and lunch and increased consumption of vegetables (Wave 1) but did not affect adolescents' consumption of fast food. Child support was positively associated with the odds that adolescents would consume dinner. Adolescents in living in nontraditional families were more likely than adolescents living with two biological/adoptive parents to display unhealthy eating habits. Nonresident father involvement was generally associated with healthier eating patterns. Health professionals should keep in mind that children's and adolescents' living arrangements can be complex and have the potential to affect what and how they eat.

  18. Ambiguity resolution in a Neural Blackboard Architecture for sentence structure

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; de Kamps, Marc; Besold, Tarek R.; Kühnberger, Kai-Uwe

    2015-01-01

    We simulate two examples of ambiguity resolution found in human language processing in a neural blackboard architecture for sentence representation and processing. The architecture also accounts for a related garden path effect. The architecture represents and processes sentences in terms of

  19. Cognitive Flexibility through Metastable Neural Dynamics Is Disrupted by Damage to the Structural Connectome

    Science.gov (United States)

    Hellyer, Peter J.; Scott, Gregory; Shanahan, Murray; Sharp, David J.

    2015-01-01

    Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome. PMID:26085630

  20. Physiological evidence of neural pathways involved in reflexogenic penile erection in the rat.

    Science.gov (United States)

    Rampin, O; Giuliano, F; Dompeyre, P; Rousseau, J P

    1994-10-24

    To elucidate neural pathways responsible for the occurrence of reflexogenic erections, the response of the corpus cavernosum to electrical stimulation of the dorsal nerve of the penis (DNP) was measured in anesthetized, acutely spinalized rats. Stimulation elicited a dramatic increase in intracavernous pressure (ICP). ICP response was decreased by 70% after sectioning the pelvic nerve homolaterally to the stimulated DNP and abolished after bilateral section. ICP response was not impaired by curarization, but its latency was lengthened. Thus we physiologically evidenced a reflex loop independent from supraspinal centers between DNP and the pelvic nerve supporting penile reflexogenic erection.

  1. Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

    Science.gov (United States)

    Witoonchart, Peerajak; Chongstitvatana, Prabhas

    2017-08-01

    In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Tricyclic antidepressant amitriptyline indirectly increases the proliferation of adult dentate gyrus-derived neural precursors: an involvement of astrocytes.

    Directory of Open Access Journals (Sweden)

    Shuken Boku

    Full Text Available Antidepressants increase the proliferation of neural precursors in adult dentate gyrus (DG, which is considered to be involved in the therapeutic action of antidepressants. However, the mechanism underlying it remains unclear. By using cultured adult rat DG-derived neural precursors (ADP, we have already shown that antidepressants have no direct effects on ADP. Therefore, antidepressants may increase the proliferation of neural precursors in adult DG via unknown indirect mechanism. We have also shown that amitriptyline (AMI, a tricyclic antidepressant, induces the expressions of GDNF, BDNF, FGF2 and VEGF, common neurogenic factors, in primary cultured astrocytes (PCA. These suggest that AMI-induced factors in astrocytes may increase the proliferation of neural precursors in adult DG. To test this hypothesis, we examined the effects of AMI-induced factors and conditioned medium (CM from PCA treated with AMI on ADP proliferation. The effects of CM and factors on ADP proliferation were examined with BrdU immunocytochemistry. AMI had no effect on ADP proliferation, but AMI-treated CM increased it. The receptors of GDNF, BDNF and FGF2, but not VEGF, were expressed in ADP. FGF2 significantly increased ADP proliferation, but not BDNF and GDNF. In addition, both of a specific inhibitor of FGF receptors and anti-FGF2 antibody significantly counteracted the increasing effect of CM on ADP proliferation. In addition, FGF2 in brain is mainly derived from astrocytes that are key components of the neurogenic niches in adult DG. These suggest that AMI may increase ADP proliferation indirectly via PCA and that FGF2 may a potential candidate to mediate such an indirect effect of AMI on ADP proliferation via astrocytes.

  3. An object recognition using structured light and neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Byeong Gab; Kim, Dong Gi; Kang, E Sok [Chungnam National Univ., Taejon (Korea, Republic of); Yoon, Ji Sup [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1997-12-31

    This paper presents a 3D image processing which uses neural networks to combine a 2D vision camera and a laser slit beam. A laser slit beam from laser source is slitted by a set of cylindrical lenses and the line image of the networks allow to get the 3D image parameters such as the size, the position and the orientation from the line image without knowing the camera intrinsic parameters. (author). 7 refs., 3 tabs., 5 figs.

  4. Viewing pictures of a romantic partner reduces experimental pain: involvement of neural reward systems.

    Directory of Open Access Journals (Sweden)

    Jarred Younger

    2010-10-01

    Full Text Available The early stages of a new romantic relationship are characterized by intense feelings of euphoria, well-being, and preoccupation with the romantic partner. Neuroimaging research has linked those feelings to activation of reward systems in the human brain. The results of those studies may be relevant to pain management in humans, as basic animal research has shown that pharmacologic activation of reward systems can substantially reduce pain. Indeed, viewing pictures of a romantic partner was recently demonstrated to reduce experimental thermal pain. We hypothesized that pain relief evoked by viewing pictures of a romantic partner would be associated with neural activations in reward-processing centers. In this functional magnetic resonance imaging (fMRI study, we examined fifteen individuals in the first nine months of a new, romantic relationship. Participants completed three tasks under periods of moderate and high thermal pain: 1 viewing pictures of their romantic partner, 2 viewing pictures of an equally attractive and familiar acquaintance, and 3 a word-association distraction task previously demonstrated to reduce pain. The partner and distraction tasks both significantly reduced self-reported pain, although only the partner task was associated with activation of reward systems. Greater analgesia while viewing pictures of a romantic partner was associated with increased activity in several reward-processing regions, including the caudate head, nucleus accumbens, lateral orbitofrontal cortex, amygdala, and dorsolateral prefrontal cortex--regions not associated with distraction-induced analgesia. The results suggest that the activation of neural reward systems via non-pharmacologic means can reduce the experience of pain.

  5. Tumor suppressor CADM1 is involved in epithelial cell structure.

    Science.gov (United States)

    Sakurai-Yageta, Mika; Masuda, Mari; Tsuboi, Yumi; Ito, Akihiko; Murakami, Yoshinori

    2009-12-18

    The tumor suppressor, CADM1, is involved in cell adhesion and preferentially inactivated in invasive cancer. We have previously reported that CADM1 associates with an actin-binding protein, 4.1B/DAL-1, and a scaffold protein, membrane protein palmitoylated 3 (MPP3)/DLG3. However, underlying mechanism of tumor suppression by CADM1 is not clarified yet. Here, we demonstrate that MPP1/p55 and MPP2/DLG2, as well as MPP3, interact with both CADM1 and 4.1B, forming a tripartite complex. We then examined cell biological roles of CADM1 and its complex in epithelia using HEK293 cells. Among MPP1-3, MPP2 is recruited to the CADM1-4.1B complex in the early process of adhesion in HEK293 cells. By suppression of CADM1 expression using siRNA, HEK293 lose epithelia-like structure and show flat morphology with immature cell adhesion. 4.1B and MPP2, as well as E-cadherin and ZO-1, are mislocalized from the membrane by depletion of CADM1 in HEK293. Mislocalization of MPP2 is also observed in several cancer cells lacking CADM1 expression with the transformed morphology. These findings suggest that CADM1 is involved in the formation of epithelia-like cell structure with 4.1B and MPP2, while loss of its function could cause morphological transformation of cancer cells.

  6. A Neural Network Model of the Structure and Dynamics of Human Personality

    Science.gov (United States)

    Read, Stephen J.; Monroe, Brian M.; Brownstein, Aaron L.; Yang, Yu; Chopra, Gurveen; Miller, Lynn C.

    2010-01-01

    We present a neural network model that aims to bridge the historical gap between dynamic and structural approaches to personality. The model integrates work on the structure of the trait lexicon, the neurobiology of personality, temperament, goal-based models of personality, and an evolutionary analysis of motives. It is organized in terms of two…

  7. The influence of group membership on the neural correlates involved in empathy

    National Research Council Canada - National Science Library

    Eres, Robert; Molenberghs, Pascal

    2013-01-01

    Empathy involves affective, cognitive, and emotion regulative components. The affective component relies on the sharing of emotional states with others and is discussed here in relation to the human Mirror System...

  8. Neural mechanisms underlying stop-and-restart difficulties: involvement of the motor and perceptual systems.

    Directory of Open Access Journals (Sweden)

    Kentaro Yamanaka

    Full Text Available The ability to suddenly stop a planned movement or a movement being performed and restart it after a short interval is an important mechanism that allows appropriate behavior in response to contextual or environmental changes. However, performing such stop-and-restart movements smoothly is difficult at times. We investigated performance (response time of stop-and-restart movements using a go/stop/re-go task and found consistent stop-and-restart difficulties after short (~100 ms stop-to-restart intervals (SRSI, and an increased probability of difficulties after longer (>200 ms SRSIs, suggesting that two different mechanisms underlie stop-and-restart difficulties. Next, we investigated motor evoked potentials (MEPs in a moving muscle induced by transcranial magnetic stimulation during a go/stop/re-go task. In re-go trials with a short SRSI (100 ms, the MEP amplitude continued to decrease after the re-go-signal onset, indicating that stop-and-restart difficulties with short SRSIs might be associated with a neural mechanism in the human motor system, namely, stop-related suppression of corticomotor (CM excitability. Finally, we recorded electroencephalogram (EEG activity during a go/stop/re-go task and performed a single-trial-based EEG power and phase time-frequency analysis. Alpha-band EEG phase locking to re-go-signal, which was only observed in re-go trials with long SRSI (250 ms, weakened in the delayed re-go response trials. These EEG phase dynamics indicate an association between stop-and-restart difficulties with long SRSIs and a neural mechanism in the human perception system, namely, decreased probability of EEG phase locking to visual stimuli. In contrast, smooth stop-and-restart human movement can be achieved in re-go trials with sufficient SRSI (150-200 ms, because release of stop-related suppression and simultaneous counter-activation of CM excitability may occur as a single task without second re-go-signal perception. These results

  9. Neural mechanisms underlying stop-and-restart difficulties: involvement of the motor and perceptual systems.

    Science.gov (United States)

    Yamanaka, Kentaro; Nozaki, Daichi

    2013-01-01

    The ability to suddenly stop a planned movement or a movement being performed and restart it after a short interval is an important mechanism that allows appropriate behavior in response to contextual or environmental changes. However, performing such stop-and-restart movements smoothly is difficult at times. We investigated performance (response time) of stop-and-restart movements using a go/stop/re-go task and found consistent stop-and-restart difficulties after short (~100 ms) stop-to-restart intervals (SRSI), and an increased probability of difficulties after longer (>200 ms) SRSIs, suggesting that two different mechanisms underlie stop-and-restart difficulties. Next, we investigated motor evoked potentials (MEPs) in a moving muscle induced by transcranial magnetic stimulation during a go/stop/re-go task. In re-go trials with a short SRSI (100 ms), the MEP amplitude continued to decrease after the re-go-signal onset, indicating that stop-and-restart difficulties with short SRSIs might be associated with a neural mechanism in the human motor system, namely, stop-related suppression of corticomotor (CM) excitability. Finally, we recorded electroencephalogram (EEG) activity during a go/stop/re-go task and performed a single-trial-based EEG power and phase time-frequency analysis. Alpha-band EEG phase locking to re-go-signal, which was only observed in re-go trials with long SRSI (250 ms), weakened in the delayed re-go response trials. These EEG phase dynamics indicate an association between stop-and-restart difficulties with long SRSIs and a neural mechanism in the human perception system, namely, decreased probability of EEG phase locking to visual stimuli. In contrast, smooth stop-and-restart human movement can be achieved in re-go trials with sufficient SRSI (150-200 ms), because release of stop-related suppression and simultaneous counter-activation of CM excitability may occur as a single task without second re-go-signal perception. These results suggest that

  10. A longitudinal analysis of neural regions involved in reading the mind in the eyes.

    Science.gov (United States)

    Overgaauw, Sandy; van Duijvenvoorde, Anna C K; Gunther Moor, Bregtje; Crone, Eveline A

    2015-05-01

    The ability to perceive social intentions from people's eyes is present from an early age, yet little is known about whether this skill is fully developed in childhood or that subtle changes may still occur across adolescence. This fMRI study investigated the ability to read mental states by using an adapted version of the Reading the Mind in the Eyes task within adolescents (aged 12-19 years) over a 2-year test-retest interval. This longitudinal setup provides the opportunity to study both stability over time as well as age-related changes. The behavioral results showed that participants who performed well in the mental state condition at the first measurement also performed well at the second measurement. fMRI results revealed positive test-retest correlations of neural activity in the right superior temporal sulcus and right inferior frontal gyrus for the contrast mental state > control, suggesting stability within individuals over time. Besides stability of activation, dorsal medial prefrontal cortex showed a dip in mid-adolescence for the mental state > control condition and right inferior frontal gyrus decreased linearly with age for the mental state > control condition. These findings underline changes in the slope of the developmental pattern depending on age, even in the existence of relatively stable activation in the social brain network. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  11. Let7a involves in neural stem cell differentiation relating with TLX level.

    Science.gov (United States)

    Song, Juhyun; Cho, Kyoung Joo; Oh, Yumi; Lee, Jong Eun

    2015-07-10

    Neural stem cells (NSCs) have the potential for differentiation into neurons known as a groundbreaking therapeutic solution for central nervous system (CNS) diseases. To resolve the therapeutic efficiency of NSCs, recent researchers have focused on the study on microRNA's role in CNS. Some micro RNAs have been reported significant functions in NSC self-renewal and differentiation through the post-transcriptional regulation of neurogenesis genes. MicroRNA-Let7a (Let7a) has known as the regulator of diverse cellular mechanisms including cell differentiation and proliferation. In present study, we investigated whether Let7a regulates NSC differentiation by targeting the nuclear receptor TLX, which is an essential regulator of NSC self-renewal, proliferation and differentiation. We performed the following experiments: western blot analysis, TaqMan assay, RT-PCR, and immunocytochemistry to confirm the alteration of NSCs. Our data showed that let7a play important roles in controlling NSC fate determination. Thus, manipulating Let-7A and TLX could be a novel strategy to enhance the efficiency of NSC's neuronal differentiation for CNS disorders. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  12. Structural basis for cholinergic regulation of neural circuits in the mouse olfactory bulb.

    Science.gov (United States)

    Hamamoto, Masakazu; Kiyokage, Emi; Sohn, Jaerin; Hioki, Hiroyuki; Harada, Tamotsu; Toida, Kazunori

    2017-02-15

    Odor information is regulated by olfactory inputs, bulbar interneurons, and centrifugal inputs in the olfactory bulb (OB). Cholinergic neurons projecting from the nucleus of the horizontal limb of the diagonal band of Broca and the magnocellular preoptic nucleus are one of the primary centrifugal inputs to the OB. In this study, we focused on cholinergic regulation of the OB and analyzed neural morphology with a particular emphasis on the projection pathways of cholinergic neurons. Single-cell imaging of a specific neuron within dense fibers is critical to evaluate the structure and function of the neural circuits. We labeled cholinergic neurons by infection with virus vector and then reconstructed them three-dimensionally. We also examined the ultramicrostructure of synapses by electron microscopy tomography. To further clarify the function of cholinergic neurons, we performed confocal laser scanning microscopy to investigate whether other neurotransmitters are present within cholinergic axons in the OB. Our results showed the first visualization of complete cholinergic neurons, including axons projecting to the OB, and also revealed frequent axonal branching within the OB where it innervated multiple glomeruli in different areas. Furthermore, electron tomography demonstrated that cholinergic axons formed asymmetrical synapses with a morphological variety of thicknesses of the postsynaptic density. Although we have not yet detected the presence of other neurotransmitters, the range of synaptic morphology suggests multiple modes of transmission. The present study elucidates the ways that cholinergic neurons could contribute to the elaborate mechanisms involved in olfactory processing in the OB. J. Comp. Neurol. 525:574-591, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  13. Neuromodulatory connectivity defines the structure of a behavioral neural network.

    Science.gov (United States)

    Diao, Feici; Elliott, Amicia D; Diao, Fengqiu; Shah, Sarav; White, Benjamin H

    2017-11-22

    Neural networks are typically defined by their synaptic connectivity, yet synaptic wiring diagrams often provide limited insight into network function. This is due partly to the importance of non-synaptic communication by neuromodulators, which can dynamically reconfigure circuit activity to alter its output. Here, we systematically map the patterns of neuromodulatory connectivity in a network that governs a developmentally critical behavioral sequence in Drosophila. This sequence, which mediates pupal ecdysis, is governed by the serial release of several key factors, which act both somatically as hormones and within the brain as neuromodulators. By identifying and characterizing the functions of the neuronal targets of these factors, we find that they define hierarchically organized layers of the network controlling the pupal ecdysis sequence: a modular input layer, an intermediate central pattern generating layer, and a motor output layer. Mapping neuromodulatory connections in this system thus defines the functional architecture of the network.

  14. A study on the possible involvement of the PAX3 gene in human neural tube defects

    Energy Technology Data Exchange (ETDEWEB)

    Hol, F.A.; Hamel, B.C.J.; Geurds, M.P.A. [University Hospital Nijmegen (Netherlands)] [and others

    1994-09-01

    Neural tube defects (NTD) are congenital malformations of the central nervous system which are generally attributed to a combination of environmental and genetic factors. Recently, the molecular defect responsible for the phenotype of the Splotch mouse, a monogenic model system for NTD, was determined. A mutation disrupts the homeodomain of the gene for Pax3. In humans, mutations in the cognate gene for PAX3 can cause Waardenburg syndrome (WS), which is associated with NTD. Based on these findings, PAX3 can be regarded as a candidate gene for human NTD. To test this hypothesis we have screened the DNA of 39 familial and 70 sporadic NTD patients for mutations in the coding exons and flanking intron sequences of the PAX3 gene. SSC analysis revealed abnormal bands in exon 2, exon 5, exon 6 and exon 7 in different patients. A missense mutation was identified in exon 6 downstream from the homeodomain in several patients resulting in an amino acid substitution (Thr315Lys) in the protein. However, the same substitution was detected in unaffected controls suggesting no biological significance. Above shifts most likely represent polymorphisms that are irrelevant for NTD. A conspicuous SSC-band shift was observed in exon 5 of one familial patient with spina bifida. Sequencing revealed that the patient was heterozygous for a 5 bp deletion upstream of the homeodomain. The deletion causes a frameshift, which leads to premature termination of translation. Mild characteristics of WS were detected in several members of the family including the index patient. DNA analysis showed co-segregation of the mutation with these symptoms. Although PAX3 mutations can increase the penetrance of NTD in families with WS, our results show that their presence is not sufficient to cause NTD.

  15. Universal transition from unstructured to structured neural maps.

    Science.gov (United States)

    Weigand, Marvin; Sartori, Fabio; Cuntz, Hermann

    2017-05-16

    Neurons sharing similar features are often selectively connected with a higher probability and should be located in close vicinity to save wiring. Selective connectivity has, therefore, been proposed to be the cause for spatial organization in cortical maps. Interestingly, orientation preference (OP) maps in the visual cortex are found in carnivores, ungulates, and primates but are not found in rodents, indicating fundamental differences in selective connectivity that seem unexpected for closely related species. Here, we investigate this finding by using multidimensional scaling to predict the locations of neurons based on minimizing wiring costs for any given connectivity. Our model shows a transition from an unstructured salt-and-pepper organization to a pinwheel arrangement when increasing the number of neurons, even without changing the selectivity of the connections. Increasing neuronal numbers also leads to the emergence of layers, retinotopy, or ocular dominance columns for the selective connectivity corresponding to each arrangement. We further show that neuron numbers impact overall interconnectivity as the primary reason for the appearance of neural maps, which we link to a known phase transition in an Ising-like model from statistical mechanics. Finally, we curated biological data from the literature to show that neural maps appear as the number of neurons in visual cortex increases over a wide range of mammalian species. Our results provide a simple explanation for the existence of salt-and-pepper arrangements in rodents and pinwheel arrangements in the visual cortex of primates, carnivores, and ungulates without assuming differences in the general visual cortex architecture and connectivity.

  16. [Progress in activity-dependent structural plasticity of neural circuits in cortex].

    Science.gov (United States)

    Rao, Xiao-Ping; Xu, Zhi-Xiang; Xu, Fu-Qiang

    2012-10-01

    Neural circuits of mammalian cerebral cortex have exhibited amazing abilities of structural and functional plasticity in development, learning and memory, neurological and psychiatric diseases. With the new imaging techniques and the application of molecular biology methods, observation neural circuits' structural dynamics within the cortex in vivo at the cellular and synaptic level was possible, so there were many great progresses in the field of the activity-dependent structural plasticity over the past decade. This paper reviewed some of the aspects of the experimental results, focused on the characteristics of dendritic structural plasticity in individual growth and development, rich environment, sensory deprivation, and pathological conditions, as well as learning and memory, especially the dynamics of dendritic spines on morphology and quantity; after that, we introduced axonal structural plasticity, the molecular and cellular mechanisms of structural plasticity, and proposed some future problems to be solved at last.

  17. Incorporation of iodine into apatite structure: a crystal chemistry approach using Artificial Neural Network

    OpenAIRE

    Jianwei eWang

    2015-01-01

    Materials with apatite crystal structure have a great potential for incorporating the long-lived radioactive iodine isotope (129I) in the form of iodide (I−) from nuclear waste streams. Because of its durability and potentially high iodine content, the apatite waste form can reduce iodine release rate and minimize the waste volume. Crystal structure and composition of apatite (A5(XO4)3Z) was investigated for iodide incorporation into the channel of the structure using Artificial Neural Networ...

  18. Entropy-based generation of supervised neural networks for classification of structured patterns.

    Science.gov (United States)

    Tsai, Hsien-Leing; Lee, Shie-Jue

    2004-03-01

    Sperduti and Starita proposed a new type of neural network which consists of generalized recursive neurons for classification of structures. In this paper, we propose an entropy-based approach for constructing such neural networks for classification of acyclic structured patterns. Given a classification problem, the architecture, i.e., the number of hidden layers and the number of neurons in each hidden layer, and all the values of the link weights associated with the corresponding neural network are automatically determined. Experimental results have shown that the networks constructed by our method can have a better performance, with respect to network size, learning speed, or recognition accuracy, than the networks obtained by other methods.

  19. A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks.

    Science.gov (United States)

    Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias

    2008-12-01

    We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest.

  20. Neural Signatures of the Reading-Writing Connection: Greater Involvement of Writing in Chinese Reading than English Reading.

    Science.gov (United States)

    Cao, Fan; Perfetti, Charles A

    2016-01-01

    Research on cross-linguistic comparisons of the neural correlates of reading has consistently found that the left middle frontal gyrus (MFG) is more involved in Chinese than in English. However, there is a lack of consensus on the interpretation of the language difference. Because this region has been found to be involved in writing, we hypothesize that reading Chinese characters involves this writing region to a greater degree because Chinese speakers learn to read by repeatedly writing the characters. To test this hypothesis, we recruited English L1 learners of Chinese, who performed a reading task and a writing task in each language. The English L1 sample had learned some Chinese characters through character-writing and others through phonological learning, allowing a test of writing-on-reading effect. We found that the left MFG was more activated in Chinese than English regardless of task, and more activated in writing than in reading regardless of language. Furthermore, we found that this region was more activated for reading Chinese characters learned by character-writing than those learned by phonological learning. A major conclusion is that writing regions are also activated in reading, and that this reading-writing connection is modulated by the learning experience. We replicated the main findings in a group of native Chinese speakers, which excluded the possibility that the language differences observed in the English L1 participants were due to different language proficiency level.

  1. Neural Signatures of the Reading-Writing Connection: Greater Involvement of Writing in Chinese Reading than English Reading.

    Directory of Open Access Journals (Sweden)

    Fan Cao

    Full Text Available Research on cross-linguistic comparisons of the neural correlates of reading has consistently found that the left middle frontal gyrus (MFG is more involved in Chinese than in English. However, there is a lack of consensus on the interpretation of the language difference. Because this region has been found to be involved in writing, we hypothesize that reading Chinese characters involves this writing region to a greater degree because Chinese speakers learn to read by repeatedly writing the characters. To test this hypothesis, we recruited English L1 learners of Chinese, who performed a reading task and a writing task in each language. The English L1 sample had learned some Chinese characters through character-writing and others through phonological learning, allowing a test of writing-on-reading effect. We found that the left MFG was more activated in Chinese than English regardless of task, and more activated in writing than in reading regardless of language. Furthermore, we found that this region was more activated for reading Chinese characters learned by character-writing than those learned by phonological learning. A major conclusion is that writing regions are also activated in reading, and that this reading-writing connection is modulated by the learning experience. We replicated the main findings in a group of native Chinese speakers, which excluded the possibility that the language differences observed in the English L1 participants were due to different language proficiency level.

  2. CHD7, the gene mutated in CHARGE syndrome, regulates genes involved in neural crest cell guidance

    NARCIS (Netherlands)

    Schulz, Yvonne; Wehner, Peter; Opitz, Lennart; Salinas-Riester, Gabriela; Bongers, Ernie M. H. F.; van Ravenswaaij-Arts, Conny M. A.; Wincent, Josephine; Schoumans, Jacqueline; Kohlhase, Juergen; Borchers, Annette; Pauli, Silke

    Heterozygous loss of function mutations in CHD7 (chromodomain helicase DNA-binding protein 7) lead to CHARGE syndrome, a complex developmental disorder affecting craniofacial structures, cranial nerves and several organ systems. Recently, it was demonstrated that CHD7 is essential for the formation

  3. The influence of group membership on the neural correlates involved in empathy.

    Directory of Open Access Journals (Sweden)

    Robert eEres

    2013-05-01

    Full Text Available Empathy involves affective, cognitive and emotion regulative components. The affective component relies on the sharing of emotional states with others and is discussed here in relation to the human Mirror System. On the other hand, the cognitive component is related to understanding the mental states of others and draws upon literature surrounding Theory of Mind. The final component, emotion regulation depends on executive function and is responsible for managing the degree to which explicit empathic responses are made. This mini-review provides information on how each of the three components is individually affected by group membership and how this leads to in-group bias.

  4. The influence of group membership on the neural correlates involved in empathy.

    Science.gov (United States)

    Eres, Robert; Molenberghs, Pascal

    2013-01-01

    Empathy involves affective, cognitive, and emotion regulative components. The affective component relies on the sharing of emotional states with others and is discussed here in relation to the human Mirror System. On the other hand, the cognitive component is related to understanding the mental states of others and draws upon literature surrounding Theory of Mind (ToM). The final component, emotion regulation, depends on executive function and is responsible for managing the degree to which explicit empathic responses are made. This mini-review provides information on how each of the three components is individually affected by group membership and how this leads to in-group bias.

  5. Neural bases of recommendations differ according to social network structure.

    Science.gov (United States)

    O'Donnell, Matthew Brook; Bayer, Joseph B; Cascio, Christopher N; Falk, Emily B

    2017-01-01

    Ideas spread across social networks, but not everyone is equally positioned to be a successful recommender. Do individuals with more opportunities to connect otherwise unconnected others-high information brokers-use their brains differently than low information brokers when making recommendations? We test the hypothesis that those with more opportunities for information brokerage may use brain systems implicated in considering the thoughts, perspectives, and mental states of others (i.e. 'mentalizing') more when spreading ideas. We used social network analysis to quantify individuals' opportunities for information brokerage. This served as a predictor of activity within meta-analytically defined neural regions associated with mentalizing (dorsomedial prefrontal cortex, temporal parietal junction, medial prefrontal cortex, /posterior cingulate cortex, middle temporal gyrus) as participants received feedback about peer opinions of mobile game apps. Higher information brokers exhibited more activity in this mentalizing network when receiving divergent peer feedback and updating their recommendation. These data support the idea that those in different network positions may use their brains differently to perform social tasks. Different social network positions might provide more opportunities to engage specific psychological processes. Or those who tend to engage such processes more may place themselves in systematically different network positions. These data highlight the value of integrating levels of analysis, from brain networks to social networks. © The Author (2017). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  6. The necessity of connection structures in neural models of variable binding

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; de Kamps, Marc

    2015-01-01

    In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1–11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other (‘connectivity based’) type uses dedicated connections structures to

  7. Vibration Based Damage Assessment of a Civil Engineering Structures using a Neural Networks

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Rytter, A.

    In this paper the possibility of using a Multilayer Perceptron (MLP) network trained with the Backpropagation Algorith as a non-destructive damage assessment technique to locate and quantify a damage in Civil Engineering structures is investigated. Since artificial neural networks are proving...

  8. The neural substrates of complex argument structure representations: Processing 'alternating transitivity' verbs.

    Science.gov (United States)

    Meltzer-Asscher, Aya; Schuchard, Julia; den Ouden, Dirk-Bart; Thompson, Cynthia K

    This study examines the neural correlates of processing verbal entries with multiple argument structures using fMRI. We compared brain activation in response to 'alternating transitivity' verbs, corresponding to two different verbal alternates - one transitive and one intransitive - and simple verbs, with only one, intransitive, thematic grid. Fourteen young healthy participants performed a lexical decision task with the two verb types. Results showed significantly greater activation in the angular and supramarginal gyri (BAs 39 and 40) extending to the posterior superior and middle temporal gyri bilaterally, for alternating compared to simple verbs. Additional activation was detected in bilateral middle and superior frontal gyri (BAs 8 and 9). The opposite contrast, simple compared to alternating verbs, showed no significant differential activation in any regions of the brain. These findings are consistent with previous studies implicating a posterior network including the superior temporal, supramarginal and angular gyri for processing verbs with multiple thematic roles, as well as with those suggesting involvement of the middle and superior frontal gyri in lexical ambiguity processing. However, because 'alternating transitivity' verbs differ from simple intransitives with regard to both the number of thematic grids (two vs. one) and the number of thematic roles (two vs. one), our findings do not distinguish between activations associated with these two differences.

  9. The neural substrates of complex argument structure representations: Processing ‘alternating transitivity’ verbs

    Science.gov (United States)

    Meltzer-Asscher, Aya; Schuchard, Julia; den Ouden, Dirk-Bart; Thompson, Cynthia K.

    2015-01-01

    This study examines the neural correlates of processing verbal entries with multiple argument structures using fMRI. We compared brain activation in response to ‘alternating transitivity’ verbs, corresponding to two different verbal alternates – one transitive and one intransitive - and simple verbs, with only one, intransitive, thematic grid. Fourteen young healthy participants performed a lexical decision task with the two verb types. Results showed significantly greater activation in the angular and supramarginal gyri (BAs 39 and 40) extending to the posterior superior and middle temporal gyri bilaterally, for alternating compared to simple verbs. Additional activation was detected in bilateral middle and superior frontal gyri (BAs 8 and 9). The opposite contrast, simple compared to alternating verbs, showed no significant differential activation in any regions of the brain. These findings are consistent with previous studies implicating a posterior network including the superior temporal, supramarginal and angular gyri for processing verbs with multiple thematic roles, as well as with those suggesting involvement of the middle and superior frontal gyri in lexical ambiguity processing. However, because ‘alternating transitivity’ verbs differ from simple intransitives with regard to both the number of thematic grids (two vs. one) and the number of thematic roles (two vs. one), our findings do not distinguish between activations associated with these two differences. PMID:26139954

  10. Crystal structures of two eukaryotic nucleases involved in RNA metabolism

    DEFF Research Database (Denmark)

    Jonstrup, Anette Thyssen; Midtgaard, Søren Fuglsang; Van, Lan Bich

    as well as the controlled turnover of these in response to changing surrounding conditions is of vital importance to ensure optimal fitness of a cell. Central to both these processes is the degradation of RNA, either as a means of decreasing the level of particular RNAs or as a way to get rid of aberrant...... form the 3'-end of mRNA, is normally the first and also rate-limiting step in cellular mRNA degradation and therefore a key process in the control of eukaryotic mRNA turnover. Since Ccr4p is believed to be the main deadenylase the precise role of Pop2p in the complex is less clear. Nevertheless, Pop2p....... In the nucleus Rrp6p associates with the exosome and participates in the degradation of improperly processed precursor mRNAs and trimming of stable RNAs. The crystal structure of S. cerevisiae Rrp6p presented here displays a conserved DEDD nuclease core with a flanking HRDC domain believed to be involved in RNA...

  11. Lithium promotes neural precursor cell proliferation: evidence for the involvement of the non-canonical GSK-3β-NF-AT signaling

    Directory of Open Access Journals (Sweden)

    Qu Zhaoxia

    2011-05-01

    Full Text Available Abstract Lithium, a drug that has long been used to treat bipolar disorder and some other human pathogenesis, has recently been shown to stimulate neural precursor growth. However, the involved mechanism is not clear. Here, we show that lithium induces proliferation but not survival of neural precursor cells. Mechanistic studies suggest that the effect of lithium mainly involved activation of the transcription factor NF-AT and specific induction of a subset of proliferation-related genes. While NF-AT inactivation by specific inhibition of its upstream activator calcineurin antagonized the effect of lithium on the proliferation of neural precursor cells, specific inhibition of the NF-AT inhibitor GSK-3β, similar to lithium treatment, promoted neural precursor cell proliferation. One important function of lithium appeared to increase inhibitory phosphorylation of GSK-3β, leading to GSK-3β suppression and subsequent NF-AT activation. Moreover, lithium-induced proliferation of neural precursor cells was independent of its role in inositol depletion. These findings not only provide mechanistic insights into the clinical effects of lithium, but also suggest an alternative therapeutic strategy for bipolar disorder and other neural diseases by targeting the non-canonical GSK-3β-NF-AT signaling.

  12. Delineating Neural Structures of Developmental Human Brains with Diffusion Tensor Imaging

    Directory of Open Access Journals (Sweden)

    Hao Huang

    2010-01-01

    Full Text Available The human brain anatomy is characterized by dramatic structural changes during fetal development. It is extraordinarily complex and yet its origin is a simple tubular structure. Revealing detailed anatomy at different stages of brain development not only aids in understanding this highly ordered process, but also provides clues to detect abnormalities caused by genetic or environmental factors. However, anatomical studies of human brain development during the fetal period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor imaging (DTI measures water diffusion to delineate the underlying neural structures. The high contrasts derived from DTI can be used to establish the brain atlas. With DTI tractography, coherent neural structures, such as white matter tracts, can be three-dimensionally reconstructed. The primary eigenvector of the diffusion tensor can be further explored to characterize microstructures in the cerebral wall of the developmental brains. In this mini-review, the application of DTI in order to reveal the structures of developmental fetal brains has been reviewed in the above-mentioned aspects. The fetal brain DTI provides a unique insight for delineating the neural structures in both macroscopic and microscopic levels. The resultant DTI database will provide structural guidance for the developmental study of human fetal brains in basic neuroscience, and reference standards for diagnostic radiology of premature newborns.

  13. Genetic Architect: Discovering Genomic Structure with Learned Neural Architectures

    OpenAIRE

    Deming, Laura; Targ, Sasha; Sauder, Nate; Almeida, Diogo; Ye, Chun Jimmie

    2016-01-01

    Each human genome is a 3 billion base pair set of encoding instructions. Decoding the genome using deep learning fundamentally differs from most tasks, as we do not know the full structure of the data and therefore cannot design architectures to suit it. As such, architectures that fit the structure of genomics should be learned not prescribed. Here, we develop a novel search algorithm, applicable across domains, that discovers an optimal architecture which simultaneously learns general genom...

  14. Accurate and rapid optical characterization of an anisotropic guided structure based on a neural method.

    Science.gov (United States)

    Robert, Stéphane; Battie, Yann; Jamon, Damien; Royer, Francois

    2007-04-10

    Optimal performances of integrated optical devices are obtained by the use of an accurate and reliable characterization method. The parameters of interest, i.e., optical indices and thickness of the waveguide structure, are calculated from effective indices by means of an inversion procedure. We demonstrate how an artificial neural network can achieve such a process. The artificial neural network used is a multilayer perceptron. The first result concerns a simulated anisotropic waveguide. The accuracy in the determination of optical indices and waveguide thickness is 5 x 10(-5) and 4 nm, respectively. Then an experimental application on a silica-titania thin film is performed. In addition, effective indices are measured by m-lines spectroscopy. Finally, a comparison with a classical optimization algorithm demonstrates the robustness of the neural method.

  15. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

    KAUST Repository

    Zhang, Xuesong

    2011-11-01

    Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework (BNN-PIS) to incorporate the uncertainties associated with parameters, inputs, and structures into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform BNNs that only consider uncertainties associated with parameters and model structures. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters shows that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of and interactions among different uncertainty sources is expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting. © 2011 Elsevier B.V.

  16. Self-awareness in neurodegenerative disease relies on neural structures mediating reward-driven attention

    Science.gov (United States)

    Shany-Ur, Tal; Lin, Nancy; Rosen, Howard J.; Sollberger, Marc; Miller, Bruce L.

    2014-01-01

    Accurate self-awareness is essential for adapting one’s tasks and goals to one’s actual abilities. Patients with neurodegenerative diseases, particularly those with right frontal involvement, often present with poor self-awareness of their functional limitations that may exacerbate their already jeopardized decision-making and behaviour. We studied the structural neuroanatomical basis for impaired self-awareness among patients with neurodegenerative disease and healthy older adults. One hundred and twenty-four participants (78 patients with neurodegenerative diseases including Alzheimer’s disease, behavioural variant frontotemporal dementia, right-temporal frontotemporal dementia, semantic variant and non-fluent variant primary progressive aphasia, and 46 healthy controls) described themselves on the Patient Competency Rating Scale, rating observable functioning across four domains (daily living activities, cognitive, emotional control, interpersonal). All participants underwent structural magnetic resonance imaging. Informants also described subjects’ functioning on the same scale. Self-awareness was measured by comparing self and informant ratings. Group differences in discrepancy scores were analysed using general linear models, controlling for age, sex and disease severity. Compared with controls, patients with behavioural variant frontotemporal dementia overestimated their functioning in all domains, patients with Alzheimer’s disease overestimated cognitive and emotional functioning, patients with right-temporal frontotemporal dementia overestimated interpersonal functioning, and patients with non-fluent aphasia overestimated emotional and interpersonal functioning. Patients with semantic variant aphasia did not overestimate functioning on any domain. To examine the neuroanatomic correlates of impaired self-awareness, discrepancy scores were correlated with brain volume using voxel-based morphometry. To identify the unique neural correlates of

  17. Knowledge base and neural network approach for protein secondary structure prediction.

    Science.gov (United States)

    Patel, Maulika S; Mazumdar, Himanshu S

    2014-11-21

    Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Learning Orthographic Structure with Sequential Generative Neural Networks

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-01-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in…

  19. Wave transmission at low-crested structures using neural networks

    NARCIS (Netherlands)

    Van Oosten, R.P.; Peixó Marco, J.; Van der Meer, J.W.; Van Gent, M.; Verhagen, H.J.

    2006-01-01

    The European Union funded project DELOS was focused on wave transmission and an extensive database on low-crested rubble mound structures was generated. During DELOS, new empirical wave transmission formulae were derived. These formulae still showed a considerable scatter due to a limited number of

  20. Neural networks involved in self-judgement in young and elderly adults.

    Science.gov (United States)

    Feyers, Dorothée; Collette, Fabienne; D'Argembeau, Arnaud; Majerus, Steve; Salmon, Eric

    2010-10-15

    Recent studies have shown that both young and elderly subjects activate the ventromedial prefrontal cortex (VMPFC) when they make self-referential judgements. However, the VMPFC might interact with different brain regions during self-referencing in the two groups. In this study, based on data from Ruby et al. (2009), we have explored this issue using psychophysiological interaction analyses. Young and elderly participants had to judge adjectives describing personality traits in reference to the self versus a close friend or relative (the other), taking either a first-person or a third-person perspective. The physiological factor was the VMPFC activity observed in all participants during self-judgement, and the psychological factor was the self versus other referential process. The main effect of first-person perspective in both groups revealed that the VMPFC was co-activated with the left parahippocampal gyrus and the precuneus for self versus other judgments. The main effect of age showed a stronger correlation between activity in the VMPFC and the lingual gyrus in young compared to elderly subjects. Finally, in the interaction, the VMPFC was specifically co-activated with the orbitofrontal gyrus and the precentral gyrus when elderly subjects took a first-person perspective for self-judgements. No significant result was observed for the interaction in young subjects. These findings show that, although the VMPFC is engaged by both young and older adults when making self-referential judgements, this brain structure interacts differently with other brain regions as a function of age and perspective. These differences might reflect a tendency by older people to engage in more emotional/social processing than younger adults when making self-referential judgements with a first-person perspective. Copyright 2010 Elsevier Inc. All rights reserved.

  1. Neural network based semi-active control strategy for structural vibration mitigation with magnetorheological damper

    DEFF Research Database (Denmark)

    Bhowmik, Subrata

    2011-01-01

    This paper presents a neural network based semi-active control method for a rotary type magnetorheological (MR) damper. The characteristics of the MR damper are described by the classic Bouc-Wen model, and the performance of the proposed control method is evaluated in terms of a base exited shear...... frame structure. As demonstrated in the literature effective damping of flexible structures is obtained by a suitable combination of pure friction and negative damper stiffness. This damper model is rate-independent and fully described by the desired shape of the hysteresis loops or force...... mode of the structure. The neural network control is then developed to reproduce the desired force based on damper displacement and velocity as network input, and it is therefore referred to as an amplitude dependent model reference control method. An inverse model of the MR damper is needed...

  2. Neural networkbased semi-active control strategy for structural vibration mitigation with magnetorheological damper

    DEFF Research Database (Denmark)

    Bhowmik, Subrata

    2011-01-01

    This paper presents a neural network based semi-active control method for a rotary type magnetorheological (MR) damper. The characteristics of the MR damper are described by the classic Bouc-Wen model, and the performance of the proposed control method is evaluated in terms of a base exited shear...... frame structure. As demonstrated in the literature effective damping of flexible structures is obtained by a suitable combination of pure friction and negative damper stiffness. This damper model is rate-independent and fully described by the desired shape of the hysteresis loops or force...... mode of the structure. The neural network control is then developed to reproduce the desired force based on damper displacement and velocity as network input, and it is therefore referred to as an amplitude dependent model reference control method. An inverse model of the MR damper is needed...

  3. Verification of the authenticity of handwritten signature using structure neural-network-type OCON

    Science.gov (United States)

    Molina, M. L.; Arias, N. A.; Gualdron, Oscar

    2004-10-01

    A method in order to carry out the verification of handwritten signatures is described. The method keeps in mind global features and local features that encode the shape and the dynamics of the signatures. Signatures are recorded with a digital tablet that can read the position and pressure of the pen. Input patterns are considered time and space dependent. Before extracting the information of the static features such as total length or height/width ratio, and the dynamic features such as speed or acceleration, the signature is normalized for position, size and orientation using its Fourier Descriptors. The comparison stage is carried out for algorithms of neurals networks. For each one of the sets of features a special two stage Perceptron OCON (one-class-one-network) classification structure has been implemented. In the first stage networks multilayer perceptron with few neurons are used. The classifier combines the decision results of the neural networks and the Euclidean distance obtained using the two feature sets. The results of the first-stage classifier feed a second-stage radial basis function (RBF) neural network structure, which makes the final decision. The entire system was extensively tested, 160 neurals networks has been implemented.

  4. Prediction of Henry's law constants by a quantitative structure property relationship and neural networks.

    Science.gov (United States)

    English, N J; Carroll, D G

    2001-01-01

    Multiple linear regression analysis and neural networks were employed to develop predictive models for Henry's law constants (HLCs) for organic compounds of environmental concern in pure water at 25 degrees C, using a set of quantitative structure property relationship (QSPR)-based descriptors to encode various molecular structural features. Two estimation models were developed from a set of 303 compounds using 10 and 12 descriptors, one of these models using two descriptors to account for hydrogen-bonding characteristics explicitly; these were validated subsequently on an external set of 54 compounds. For each model, a linear regression and neural network version was prepared. The standard errors of the linear regression models for the training data set were 0.262 and 0.488 log(H(cc)) units, while those of the neural network analogues were lower at 0.202 and 0.224, respectively; the linear regression models explained 98.3% and 94.3% of the variance in the development data, respectively, the neural network models giving similar quality results of 99% and 98.3%, respectively. The various descriptors used describe connectivity, charge distribution, charged surface area, hydrogen-bonding characteristics, and group influences on HLC values.

  5. Inferring synaptic structure in presence of neural interaction time scales.

    Directory of Open Access Journals (Sweden)

    Cristiano Capone

    Full Text Available Biological networks display a variety of activity patterns reflecting a web of interactions that is complex both in space and time. Yet inference methods have mainly focused on reconstructing, from the network's activity, the spatial structure, by assuming equilibrium conditions or, more recently, a probabilistic dynamics with a single arbitrary time-step. Here we show that, under this latter assumption, the inference procedure fails to reconstruct the synaptic matrix of a network of integrate-and-fire neurons when the chosen time scale of interaction does not closely match the synaptic delay or when no single time scale for the interaction can be identified; such failure, moreover, exposes a distinctive bias of the inference method that can lead to infer as inhibitory the excitatory synapses with interaction time scales longer than the model's time-step. We therefore introduce a new two-step method, that first infers through cross-correlation profiles the delay-structure of the network and then reconstructs the synaptic matrix, and successfully test it on networks with different topologies and in different activity regimes. Although step one is able to accurately recover the delay-structure of the network, thus getting rid of any a priori guess about the time scales of the interaction, the inference method introduces nonetheless an arbitrary time scale, the time-bin dt used to binarize the spike trains. We therefore analytically and numerically study how the choice of dt affects the inference in our network model, finding that the relationship between the inferred couplings and the real synaptic efficacies, albeit being quadratic in both cases, depends critically on dt for the excitatory synapses only, whilst being basically independent of it for the inhibitory ones.

  6. Optimizing the De-Noise Neural Network Model for GPS Time-Series Monitoring of Structures

    Directory of Open Access Journals (Sweden)

    Mosbeh R. Kaloop

    2015-09-01

    Full Text Available The Global Positioning System (GPS is recently used widely in structures and other applications. Notwithstanding, the GPS accuracy still suffers from the errors afflicting the measurements, particularly the short-period displacement of structural components. Previously, the multi filter method is utilized to remove the displacement errors. This paper aims at using a novel application for the neural network prediction models to improve the GPS monitoring time series data. Four prediction models for the learning algorithms are applied and used with neural network solutions: back-propagation, Cascade-forward back-propagation, adaptive filter and extended Kalman filter, to estimate which model can be recommended. The noise simulation and bridge’s short-period GPS of the monitoring displacement component of one Hz sampling frequency are used to validate the four models and the previous method. The results show that the Adaptive neural networks filter is suggested for de-noising the observations, specifically for the GPS displacement components of structures. Also, this model is expected to have significant influence on the design of structures in the low frequency responses and measurements’ contents.

  7. Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Reza Kamyab Moghadas

    2012-01-01

    Full Text Available The main aim of the present work is to determine the optimal design and maximum deflection of double layer grids spending low computational cost using neural networks. The design variables of the optimization problem are cross-sectional area of the elements as well as the length of the span and height of the structures. In this paper, a number of double layer grids with various random values of length and height are selected and optimized by simultaneous perturbation stochastic approximation algorithm. Then, radial basis function (RBF and generalized regression (GR neural networks are trained to predict the optimal design and maximum deflection of the structures. The numerical results demonstrate the efficiency of the proposed methodology.

  8. Structure and function of enzymes involved in the anaerobic ...

    Indian Academy of Sciences (India)

    In the recent past, extensive structural and biochemical studies have been carried out on these enzymes by various groups. Besides detailed structural and functional insights, these studies have also shown the similarities and differences between the other related enzymes present in the metabolic network. In this paper, we ...

  9. The neural origins of shell structure and pattern in aquatic mollusks.

    Science.gov (United States)

    Boettiger, Alistair; Ermentrout, Bard; Oster, George

    2009-04-21

    We present a model to explain how the neurosecretory system of aquatic mollusks generates their diversity of shell structures and pigmentation patterns. The anatomical and physiological basis of this model sets it apart from other models used to explain shape and pattern. The model reproduces most known shell shapes and patterns and accurately predicts how the pattern alters in response to environmental disruption and subsequent repair. Finally, we connect the model to a larger class of neural models.

  10. Deep neural nets as a method for quantitative structure-activity relationships.

    Science.gov (United States)

    Ma, Junshui; Sheridan, Robert P; Liaw, Andy; Dahl, George E; Svetnik, Vladimir

    2015-02-23

    Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the early 2000s. The last 10 years has witnessed a revival of neural networks in the machine learning community thanks to new methods for preventing overfitting, more efficient training algorithms, and advancements in computer hardware. In particular, deep neural nets (DNNs), i.e. neural nets with more than one hidden layer, have found great successes in many applications, such as computer vision and natural language processing. Here we show that DNNs can routinely make better prospective predictions than RF on a set of large diverse QSAR data sets that are taken from Merck's drug discovery effort. The number of adjustable parameters needed for DNNs is fairly large, but our results show that it is not necessary to optimize them for individual data sets, and a single set of recommended parameters can achieve better performance than RF for most of the data sets we studied. The usefulness of the parameters is demonstrated on additional data sets not used in the calibration. Although training DNNs is still computationally intensive, using graphical processing units (GPUs) can make this issue manageable.

  11. A New Training Method for Analyzable Structured Neural Network and Application of Daily Peak Load Forecasting

    Science.gov (United States)

    Iizaka, Tatsuya; Matsui, Tetsuro; Fukuyama, Yoshikazu

    This paper presents a daily peak load forecasting method using an analyzable structured neural network (ASNN) in order to explain forecasting reasons. In this paper, we propose a new training method for ASNN in order to explain forecasting reason more properly than the conventional training method. ASNN consists of two types of hidden units. One type of hidden units has connecting weights between the hidden units and only one group of related input units. Another one has connecting weights between the hidden units and all input units. The former type of hidden units allows to explain forecasting reasons. The latter type of hidden units ensures the forecasting performance. The proposed training method make the former type of hidden units train only independent relations between the input factors and output, and make the latter type of hidden units train only complicated interactions between input factors. The effectiveness of the proposed neural network is shown using actual daily peak load. ASNN trained by the proposed method can explain forecasting reasons more properly than ASNN trained by the conventional method. Moreover, the proposed neural network can forecast daily peak load more accurately than conventional neural network trained by the back propagation algorithm.

  12. Flexible deep brain neural probes based on a parylene tube structure

    Science.gov (United States)

    Zhao, Zhiguo; Kim, Eric; Luo, Hao; Zhang, Jinsheng; Xu, Yong

    2018-01-01

    Most microfabricated neural probes have limited shank length, which prevents them from reaching many deep brain structures. This paper reports deep brain neural probes with ultra-long penetrating shanks based on a simple but novel parylene tube structure. The mechanical strength of the parylene tube shank is temporarily enhanced during implantation by inserting a metal wire. The metal wire can be removed after implantation, making the implanted probe very flexible and thus minimizing the stress caused by micromotions of brain tissues. Optogenetic stimulation and chemical delivery capabilities can be potentially integrated by taking advantage of the tube structure. Single-shank prototypes with a shank length of 18.2 mm have been developed. The microfabrication process comprises of deep reactive ion etching (DRIE) of silicon, parylene conformal coating/refilling, and XeF2 isotropic silicon etching. In addition to bench-top insertion characterization, the functionality of developed probes has been preliminarily demonstrated by implanting into the amygdala of a rat and recording neural signals.

  13. Neural circuit remodeling and structural plasticity in the cortex during chronic pain.

    Science.gov (United States)

    Kim, Woojin; Kim, Sun Kwang

    2016-01-01

    Damage in the periphery or spinal cord induces maladaptive plastic changes along the somatosensory nervous system from the periphery to the cortex, often leading to chronic pain. Although the role of neural circuit remodeling and structural synaptic plasticity in the 'pain matrix' cortices in chronic pain has been thought as a secondary epiphenomenon to altered nociceptive signaling in the spinal cord, progress in whole brain imaging studies on human patients and animal models has suggested a possibility that plastic changes in cortical neural circuits may actively contribute to chronic pain symptoms. Furthermore, recent development in two-photon microscopy and fluorescence labeling techniques have enabled us to longitudinally trace the structural and functional changes in local circuits, single neurons and even individual synapses in the brain of living animals. These technical advances has started to reveal that cortical structural remodeling following tissue or nerve damage could rapidly occur within days, which are temporally correlated with functional plasticity of cortical circuits as well as the development and maintenance of chronic pain behavior, thereby modifying the previous concept that it takes much longer periods (e.g. months or years). In this review, we discuss the relation of neural circuit plasticity in the 'pain matrix' cortices, such as the anterior cingulate cortex, prefrontal cortex and primary somatosensory cortex, with chronic pain. We also introduce how to apply long-term in vivo two-photon imaging approaches for the study of pathophysiological mechanisms of chronic pain.

  14. Real-Time Structural Damage Assessment Using Artificial Neural Networks and Antiresonant Frequencies

    Directory of Open Access Journals (Sweden)

    V. Meruane

    2014-01-01

    Full Text Available The main problem in damage assessment is the determination of how to ascertain the presence, location, and severity of structural damage given the structure's dynamic characteristics. The most successful applications of vibration-based damage assessment are model updating methods based on global optimization algorithms. However, these algorithms run quite slowly, and the damage assessment process is achieved via a costly and time-consuming inverse process, which presents an obstacle for real-time health monitoring applications. Artificial neural networks (ANN have recently been introduced as an alternative to model updating methods. Once a neural network has been properly trained, it can potentially detect, locate, and quantify structural damage in a short period of time and can therefore be applied for real-time damage assessment. The primary contribution of this research is the development of a real-time damage assessment algorithm using ANN and antiresonant frequencies. Antiresonant frequencies can be identified more easily and more accurately than mode shapes, and they provide the same information. This research addresses the setup of the neural network parameters and provides guidelines for the selection of these parameters in similar damage assessment problems. Two experimental cases validate this approach: an 8-DOF mass-spring system and a beam with multiple damage scenarios.

  15. Musical intervention enhances infants' neural processing of temporal structure in music and speech.

    Science.gov (United States)

    Zhao, T Christina; Kuhl, Patricia K

    2016-05-10

    Individuals with music training in early childhood show enhanced processing of musical sounds, an effect that generalizes to speech processing. However, the conclusions drawn from previous studies are limited due to the possible confounds of predisposition and other factors affecting musicians and nonmusicians. We used a randomized design to test the effects of a laboratory-controlled music intervention on young infants' neural processing of music and speech. Nine-month-old infants were randomly assigned to music (intervention) or play (control) activities for 12 sessions. The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize learning (e.g., multimodal, social, and repetitive experiences). Controls had similar multimodal, social, repetitive play, but without music. Upon completion, infants' neural processing of temporal structure was tested in both music (tones in triple meter) and speech (foreign syllable structure). Infants' neural processing was quantified by the mismatch response (MMR) measured with a traditional oddball paradigm using magnetoencephalography (MEG). The intervention group exhibited significantly larger MMRs in response to music temporal structure violations in both auditory and prefrontal cortical regions. Identical results were obtained for temporal structure changes in speech. The intervention thus enhanced temporal structure processing not only in music, but also in speech, at 9 mo of age. We argue that the intervention enhanced infants' ability to extract temporal structure information and to predict future events in time, a skill affecting both music and speech processing.

  16. Musical intervention enhances infants’ neural processing of temporal structure in music and speech

    Science.gov (United States)

    Zhao, T. Christina; Kuhl, Patricia K.

    2016-01-01

    Individuals with music training in early childhood show enhanced processing of musical sounds, an effect that generalizes to speech processing. However, the conclusions drawn from previous studies are limited due to the possible confounds of predisposition and other factors affecting musicians and nonmusicians. We used a randomized design to test the effects of a laboratory-controlled music intervention on young infants’ neural processing of music and speech. Nine-month-old infants were randomly assigned to music (intervention) or play (control) activities for 12 sessions. The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize learning (e.g., multimodal, social, and repetitive experiences). Controls had similar multimodal, social, repetitive play, but without music. Upon completion, infants’ neural processing of temporal structure was tested in both music (tones in triple meter) and speech (foreign syllable structure). Infants’ neural processing was quantified by the mismatch response (MMR) measured with a traditional oddball paradigm using magnetoencephalography (MEG). The intervention group exhibited significantly larger MMRs in response to music temporal structure violations in both auditory and prefrontal cortical regions. Identical results were obtained for temporal structure changes in speech. The intervention thus enhanced temporal structure processing not only in music, but also in speech, at 9 mo of age. We argue that the intervention enhanced infants’ ability to extract temporal structure information and to predict future events in time, a skill affecting both music and speech processing. PMID:27114512

  17. A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure

    National Research Council Canada - National Science Library

    Miconi, Thomas; VanRullen, Rufin

    2016-01-01

    Visual attention has many effects on neural responses, producing complex changes in firing rates, as well as modifying the structure and size of receptive fields, both in topological and feature space...

  18. Structural Damage Identification Based on Rough Sets and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Chengyin Liu

    2014-01-01

    Full Text Available This paper investigates potential applications of the rough sets (RS theory and artificial neural network (ANN method on structural damage detection. An information entropy based discretization algorithm in RS is applied for dimension reduction of the original damage database obtained from finite element analysis (FEA. The proposed approach is tested with a 14-bay steel truss model for structural damage detection. The experimental results show that the damage features can be extracted efficiently from the combined utilization of RS and ANN methods even the volume of measurement data is enormous and with uncertainties.

  19. Structural proteins involved in emergence of microbial aerial hyphae

    NARCIS (Netherlands)

    Wosten, HAB; Willey, JM

    1999-01-01

    Filamentous fungi and filamentous bacteria (i.e., the streptomycetes) belong to different kingdoms that diverged early in evolution, Yet, they adopted similar lifestyles, After a submerged feeding mycelium has been established, hyphae grow into the air and form aerial structures from which (a)sexual

  20. Development of strongly coupled FSI technology involving thin walled structures

    CSIR Research Space (South Africa)

    Suliman, Ridhwaan

    2011-01-01

    Full Text Available A strongly coupled finite volume-finite element fluid-structure interaction (FSI) scheme is developed. Both an edge-based finite volume and Galerkin finite element scheme are implemented and evaluated for modelling the mechanics of solids...

  1. Towards the structural characterization of proteins involved in peptidoglycan biosynthesis

    NARCIS (Netherlands)

    Nikolaidis, I.|info:eu-repo/dai/nl/330830260

    2015-01-01

    The cell wall is an essential structure for bacterial survival and unique to bacteria. It is responsible for maintenance of cellular shape and allows the bacterium to withstand high differences in osmotic pressure between the inner and outer leaflet of the cell. Consequently, the bacterial cell wall

  2. Neural Differentiation of Human Adipose Tissue-Derived Stem Cells Involves Activation of the Wnt5a/JNK Signalling

    Directory of Open Access Journals (Sweden)

    Sujeong Jang

    2015-01-01

    Full Text Available Stem cells are a powerful resource for cell-based transplantation therapies, but understanding of stem cell differentiation at the molecular level is not clear yet. We hypothesized that the Wnt pathway controls stem cell maintenance and neural differentiation. We have characterized the transcriptional expression of Wnt during the neural differentiation of hADSCs. After neural induction, the expressions of Wnt2, Wnt4, and Wnt11 were decreased, but the expression of Wnt5a was increased compared with primary hADSCs in RT-PCR analysis. In addition, the expression levels of most Fzds and LRP5/6 ligand were decreased, but not Fzd3 and Fzd5. Furthermore, Dvl1 and RYK expression levels were downregulated in NI-hADSCs. There were no changes in the expression of ß-catenin and GSK3ß. Interestingly, Wnt5a expression was highly increased in NI-hADSCs by real time RT-PCR analysis and western blot. Wnt5a level was upregulated after neural differentiation and Wnt3, Dvl2, and Naked1 levels were downregulated. Finally, we found that the JNK expression was increased after neural induction and ERK level was decreased. Thus, this study shows for the first time how a single Wnt5a ligand can activate the neural differentiation pathway through the activation of Wnt5a/JNK pathway by binding Fzd3 and Fzd5 and directing Axin/GSK-3ß in hADSCs.

  3. Elements of an algorithm for optimizing a parameter-structural neural network

    Directory of Open Access Journals (Sweden)

    Mrówczyńska Maria

    2016-06-01

    Full Text Available The field of processing information provided by measurement results is one of the most important components of geodetic technologies. The dynamic development of this field improves classic algorithms for numerical calculations in the aspect of analytical solutions that are difficult to achieve. Algorithms based on artificial intelligence in the form of artificial neural networks, including the topology of connections between neurons have become an important instrument connected to the problem of processing and modelling processes. This concept results from the integration of neural networks and parameter optimization methods and makes it possible to avoid the necessity to arbitrarily define the structure of a network. This kind of extension of the training process is exemplified by the algorithm called the Group Method of Data Handling (GMDH, which belongs to the class of evolutionary algorithms. The article presents a GMDH type network, used for modelling deformations of the geometrical axis of a steel chimney during its operation.

  4. Task-dependent neural and behavioral effects of verb argument structure features.

    Science.gov (United States)

    Malyutina, Svetlana; den Ouden, Dirk-Bart

    2017-05-01

    Understanding which verb argument structure (VAS) features (if any) are part of verbs' lexical entries and under which conditions they are accessed provides information on the nature of lexical representations and sentence construction. We investigated neural and behavioral effects of three understudied VAS characteristics (number of subcategorization options, number of thematic options and overall number of valency frames) in lexical decision and sentence well-formedness judgment in healthy adults. VAS effects showed strong dependency on processing conditions. As reflected by behavioral performance and neural recruitment patterns, increased VAS complexity in terms of subcategorization options and thematic options had a detrimental effect on sentence processing, but facilitated lexical access to single words, possibly by providing more lexico-semantic associations and access routes (facilitation through complexity). Effects of the number of valency frames are equivocal. We suggest that VAS effects may be mediated semantically rather than by a dedicated VAS module in verbs' representations. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Neural Mechanisms of Verb Argument Structure Processing in Agrammatic Aphasic and Healthy Age-Matched Listeners

    Science.gov (United States)

    Thompson, Cynthia K.; Bonakdarpour, Borna; Fix, Stephen F.

    2010-01-01

    Processing of lexical verbs involves automatic access to argument structure entries entailed within the verb's representation. Recent neuroimaging studies with young normal listeners suggest that this involves bilateral posterior peri-sylvian tissue, with graded activation in these regions on the basis of argument structure complexity. The aim of…

  6. Precursor Events Involving Plasmas Structures Around Collapsing Black Holes Binaries

    Science.gov (United States)

    Medvedev, M.; Coppi, B.

    2017-10-01

    The plasma structures that can exist around black hole binaries can sustain intrinsic plasma collective modes that have characteristic low frequencies related to the particle rotation frequencies around the binary system. As the collapse approaches, with the loss of angular momentum by emission of gravitational waves from the binary system we have suggested that the frequency of the fluctuating component of the gravitational potential can go through that of the intrinsic modes of the surrounding plasma structure and lead to a sharp amplification of them. Then the precursor to the event reported in Ref., tentatively identified by the Agile X- γ-ray observatory may be associated with the high energy radiation emission due to the fields produced by excitation of the proposed plasma modes. M. Tavani is thanked for bringing Ref. to our attention while Ref. was being completed. Sponsored in part by the U.S. DoE.

  7. Patient preference for involvement, experienced involvement, decisional conflict, and satisfaction with physician: a structural equation model test.

    Science.gov (United States)

    Hölzel, Lars P; Kriston, Levente; Härter, Martin

    2013-06-25

    A comprehensive model of the relationships among different shared decision-making related constructs and their effects on patient-relevant outcomes is largely missing. Objective of our study was the development of a model linking decision-making in medical encounters to an intermediate and a long-term endpoint. The following hypotheses were tested: physicians are more likely to involve patients who have a preference for participation and are willing to take responsibility in the medical decision-making process, increased patient involvement decreases decisional conflict, and lower decisional conflict favourably influences patient satisfaction with the physician. This model was tested in a German primary care sample (N = 1,913). Psychometrically tested instruments were administered to assess the following: patients' preference for being involved in medical decision-making, patients' experienced involvement in medical decision-making, decisional conflict, and satisfaction with the primary care provider. Structural equation modelling was used to explore multiple associations. The model was tested and adjusted in a development sub-sample and cross-validated in a confirmatory sample. Demographic and clinical characteristics were accounted for as possible confounders. Local and global indexes suggested an acceptable fit between the theoretical model and the data. Increased patient involvement was strongly associated with decreased decisional conflict (standardised regression coefficient Β = -.73). Both high experienced involvement (Β = .34) and low decisional conflict (B = -.28) predicted higher satisfaction with the physician. Patients' preference for involvement was negatively associated with the experienced involvement (B = -.24). Altogether, our model could be largely corroborated by the collected empirical data except the unexpected negative association between preference for involvement and experienced involvement. Future research on the

  8. Applications of Artificial Neural Networks in Structural Engineering with Emphasis on Continuum Models

    Science.gov (United States)

    Kapania, Rakesh K.; Liu, Youhua

    1998-01-01

    The use of continuum models for the analysis of discrete built-up complex aerospace structures is an attractive idea especially at the conceptual and preliminary design stages. But the diversity of available continuum models and hard-to-use qualities of these models have prevented them from finding wide applications. In this regard, Artificial Neural Networks (ANN or NN) may have a great potential as these networks are universal approximators that can realize any continuous mapping, and can provide general mechanisms for building models from data whose input-output relationship can be highly nonlinear. The ultimate aim of the present work is to be able to build high fidelity continuum models for complex aerospace structures using the ANN. As a first step, the concepts and features of ANN are familiarized through the MATLAB NN Toolbox by simulating some representative mapping examples, including some problems in structural engineering. Then some further aspects and lessons learned about the NN training are discussed, including the performances of Feed-Forward and Radial Basis Function NN when dealing with noise-polluted data and the technique of cross-validation. Finally, as an example of using NN in continuum models, a lattice structure with repeating cells is represented by a continuum beam whose properties are provided by neural networks.

  9. Poor ability to resist tempting calorie rich food is linked to altered balance between neural systems involved in urge and self-control

    OpenAIRE

    He, Qinghua; Xiao, Lin; Xue, Gui; Wong, Savio; Ames, Susan L.; Schembre, Susan M.; Bechara, Antoine

    2014-01-01

    Background The loss of self-control or inability to resist tempting/rewarding foods, and the development of less healthful eating habits may be explained by three key neural systems: (1) a hyper-functioning striatum system driven by external rewarding cues; (2) a hypo-functioning decision-making and impulse control system; and (3) an altered insula system involved in the translation of homeostatic and interoceptive signals into self-awareness and what may be subjectively experienced as a feel...

  10. Identification of genetic and epigenetic marks involved in population structure.

    Directory of Open Access Journals (Sweden)

    Jingyu Liu

    2010-10-01

    Full Text Available Population structure is well known as a prevalent and important factor in genetic studies, but its relevance in epigenetics is unclear. Very little is known about the affected epigenetic markers and their connections with genetics. In this study we assessed the impact of population diversity on genome wide single nucleotide polymorphisms (SNPs and DNA methylation levels in 196 participants from five ethnic groups, using principle and independent component analyses. Three population stratification factors (PSFs were identified in the genomic SNP dataset, accounting for a relatively large portion of total variance (6%. In contrast, only one PSF was identified in genomic methylation dataset accounting for 0.2% of total variance. This methylation PSF, however, was significantly correlated with the largest SNP PSF (r = 0.72, p<1E-23. We then investigated the top contributing markers in these two linked PSFs. The SNP PSF predominantly consists of 8 SNPs from three genes, SLC45A2, HERC2 and CTNNA2, known to encode skin/hair/eye color. The methylation PSF includes 48 methylated sites in 44 genes coding for basic molecular functions, including transcription regulation, DNA binding, cytokine, and transferase activity. Among them, 8 sites are either hypo- or hyper-methylated correlating to minor alleles of SNPs in the SNP PSF. We found that the genes in SNP and methylation PSFs share common biological processes including sexual/multicellular organism reproduction, cell-cell signaling and cytoskeleton organization. We further investigated the transcription regulatory network operating at these genes and identified that most of genes closely interact with ID2, which encodes for a helix-loop-helix inhibitor of DNA binding. Overall, our results show a significant correlation between genetic and epigenetic population stratification, and suggest that the interrelationship between genetic and epigenetic population structure is mediated via complex multiple

  11. Hydrogel scaffolds promote neural gene expression and structural reorganization in human astrocyte cultures

    Directory of Open Access Journals (Sweden)

    V. Bleu Knight

    2017-01-01

    Full Text Available Biomaterial scaffolds have the potential to enhance neuronal development and regeneration. Understanding the genetic responses of astrocytes and neurons to biomaterials could facilitate the development of synthetic environments that enable the specification of neural tissue organization with engineered scaffolds. In this study, we used high throughput transcriptomic and imaging methods to determine the impact of a hydrogel, PuraMatrix™, on human glial cells in vitro. Parallel studies were undertaken with cells grown in a monolayer environment on tissue culture polystyrene. When the Normal Human Astrocyte (NHA cell line is grown in a hydrogel matrix environment, the glial cells adopt a structural organization that resembles that of neuronal-glial cocultures, where neurons form clusters that are distinct from the surrounding glia. Statistical analysis of next generation RNA sequencing data uncovered a set of genes that are differentially expressed in the monolayer and matrix hydrogel environments. Functional analysis demonstrated that hydrogel-upregulated genes can be grouped into three broad categories: neuronal differentiation and/or neural plasticity, response to neural insult, and sensory perception. Our results demonstrate that hydrogel biomaterials have the potential to transform human glial cell identity, and may have applications in the repair of damaged brain tissue.

  12. Localization and identification of structural nonlinearities using cascaded optimization and neural networks

    Science.gov (United States)

    Koyuncu, A.; Cigeroglu, E.; Özgüven, H. N.

    2017-10-01

    In this study, a new approach is proposed for identification of structural nonlinearities by employing cascaded optimization and neural networks. Linear finite element model of the system and frequency response functions measured at arbitrary locations of the system are used in this approach. Using the finite element model, a training data set is created, which appropriately spans the possible nonlinear configurations space of the system. A classification neural network trained on these data sets then localizes and determines the types of all nonlinearities associated with the nonlinear degrees of freedom in the system. A new training data set spanning the parametric space associated with the determined nonlinearities is created to facilitate parametric identification. Utilizing this data set, initially, a feed forward regression neural network is trained, which parametrically identifies the classified nonlinearities. Then, the results obtained are further improved by carrying out an optimization which uses network identified values as starting points. Unlike identification methods available in literature, the proposed approach does not require data collection from the degrees of freedoms where nonlinear elements are attached, and furthermore, it is sufficiently accurate even in the presence of measurement noise. The application of the proposed approach is demonstrated on an example system with nonlinear elements and on a real life experimental setup with a local nonlinearity.

  13. Efficient genome editing of genes involved in neural crest development using the CRISPR/Cas9 system in Xenopus embryos.

    Science.gov (United States)

    Liu, Zhongzhen; Cheng, Tina Tsz Kwan; Shi, Zhaoying; Liu, Ziran; Lei, Yong; Wang, Chengdong; Shi, Weili; Chen, Xiongfeng; Qi, Xufeng; Cai, Dongqing; Feng, Bo; Deng, Yi; Chen, Yonglong; Zhao, Hui

    2016-01-01

    The RNA guided CRISPR/Cas9 nucleases have been proven to be effective for gene disruption in various animal models including Xenopus tropicalis. The neural crest (NC) is a transient cell population during embryonic development and contributes to a large variety of tissues. Currently, loss-of-function studies on NC development in X. tropicalis are largely based on morpholino antisense oligonucleotide. It is worthwhile establishing targeted gene knockout X. tropicails line using CRISPR/Cas9 system to study NC development. We utilized CRISPR/Cas9 to disrupt genes that are involved in NC formation in X. tropicalis embryos. A single sgRNA and Cas9 mRNA synthesized in vitro, were co-injected into X. tropicalis embryos at one-cell stage to induce single gene disruption. We also induced duplex mutations, large segmental deletions and inversions in X. tropicalis by injecting Cas9 and a pair of sgRNAs. The specificity of CRISPR/Cas9 was assessed in X. tropicalis embryos and the Cas9 nickase was used to reduce the off-target cleavages. Finally, we crossed the G0 mosaic frogs with targeted mutations to wild type frogs and obtained the germline transmission. Total 16 target sites in 15 genes were targeted by CRISPR/Cas9 and resulted in successful indel mutations at 14 loci with disruption efficiencies in a range from 9.3 to 57.8 %. Furthermore, we demonstrated the feasibility of generation of duplex mutations, large segmental deletions and inversions by using Cas9 and a pair of sgRNAs. We observed that CRISPR/Cas9 displays obvious off-target effects at some loci in X. tropicalis embryos. Such off-target cleavages was reduced by using the D10A Cas9 nickase. Finally, the Cas9 induced indel mutations were efficiently passed to G1 offspring. Our study proved that CRISPR/Cas9 could mediate targeted gene mutation in X. tropicalis with high efficiency. This study expands the application of CRISPR/Cas9 platform in X. tropicalis and set a basis for studying NC development using genetic

  14. Predicting physical-chemical properties of compounds from molecular structures by recursive neural networks.

    Science.gov (United States)

    Bernazzani, Luca; Duce, Celia; Micheli, Alessio; Mollica, Vincenzo; Sperduti, Alessandro; Starita, Antonina; Tiné, Maria Rosaria

    2006-01-01

    In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property. Therefore, it combines in a learning system the flexibility and general advantages of a neural network model with the representational power of a structured domain. As a result, a completely new approach to quantitative structure-activity relationship/quantitative structure-property relationship (QSPR/QSAR) analysis is obtained. An original representation of the molecular structures has been developed accounting for both the occurrence of specific atoms/groups and the topological relationships among them. Gibbs free energy of solvation in water, Delta(solv)G degrees , has been chosen as a benchmark for the model. The different approaches proposed in the literature for the prediction of this property have been reconsidered from a general perspective. The advantages of RecNN as a suitable tool for the automatization of fundamental parts of the QSPR/QSAR analysis have been highlighted. The RecNN model has been applied to the analysis of the Delta(solv)G degrees in water of 138 monofunctional acyclic organic compounds and tested on an external data set of 33 compounds. As a result of the statistical analysis, we obtained, for the predictive accuracy estimated on the test set, correlation coefficient R = 0.9985, standard deviation S = 0.68 kJ mol(-1), and mean absolute error MAE = 0.46 kJ mol(-1). The inherent ability of RecNN to abstract chemical knowledge through the adaptive learning process has been investigated by principal components analysis of the internal representations computed by the network. It has been found that the model recognizes the chemical compounds on the

  15. Tracting the neural basis of music: Deficient structural connectivity underlying acquired amusia.

    Science.gov (United States)

    Sihvonen, Aleksi J; Ripollés, Pablo; Särkämö, Teppo; Leo, Vera; Rodríguez-Fornells, Antoni; Saunavaara, Jani; Parkkola, Riitta; Soinila, Seppo

    2017-12-01

    Acquired amusia provides a unique opportunity to investigate the fundamental neural architectures of musical processing due to the transition from a functioning to defective music processing system. Yet, the white matter (WM) deficits in amusia remain systematically unexplored. To evaluate which WM structures form the neural basis for acquired amusia and its recovery, we studied 42 stroke patients longitudinally at acute, 3-month, and 6-month post-stroke stages using DTI [tract-based spatial statistics (TBSS) and deterministic tractography (DT)] and the Scale and Rhythm subtests of the Montreal Battery of Evaluation of Amusia (MBEA). Non-recovered amusia was associated with structural damage and subsequent degeneration in multiple WM tracts including the right inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), and frontal aslant tract (FAT), as well as in the corpus callosum (CC) and its posterior part (tapetum). In a linear regression analysis, the volume of the right IFOF was the main predictor of MBEA performance across time. Overall, our results provide a comprehensive picture of the large-scale deficits in intra- and interhemispheric structural connectivity underlying amusia, and conversely highlight which pathways are crucial for normal music perception. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Prediction of Maximum Story Drift of MDOF Structures under Simulated Wind Loads Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Omar Payán-Serrano

    2017-05-01

    Full Text Available The aim of this paper is to investigate the prediction of maximum story drift of Multi-Degree of Freedom (MDOF structures subjected to dynamics wind load using Artificial Neural Networks (ANNs through the combination of several structural and turbulent wind parameters. The maximum story drift of 1600 MDOF structures under 16 simulated wind conditions are computed with the purpose of generating the data set for the networks training with the Levenberg–Marquardt method. The Shinozuka and Newmark methods are used to simulate the turbulent wind and dynamic response, respectively. In order to optimize the computational time required for the dynamic analyses, an array format based on the Shinozuka method is presented to perform the parallel computing. Finally, it is observed that the already trained ANNs allow for predicting adequately the maximum story drift with a correlation close to 99%.

  17. 40LoVe and Samba are involved in Xenopus neural development and functionally distinct from hnRNP AB.

    Directory of Open Access Journals (Sweden)

    Maria Andreou

    Full Text Available Heterogeneous nuclear ribonucleoproteins (hnRNPs comprise a large group of modular RNA-binding proteins classified according to their conserved domains. This modular nature, coupled with a large choice of alternative splice variants generates functional diversity. Here, we investigate the biological differences between 40LoVe, its splice variant Samba and its pseudoallele hnRNP AB in neural development. Loss of function experiments lead to defects in neural development with reduction of eye size, which stem primarily from increased apoptosis and reduced proliferation in neural tissues. Despite very high homology between 40LoVe/Samba and hnRNP AB, these proteins display major differences in localization, which appear to be in part responsible for functional differences. Specifically, we show that the 40Love/Samba carboxy-terminal domain (GRD enables nucleocytoplasmic shuttling behavior. This domain is slightly different in hnRNP AB, leading to nuclear-restricted localization. Finally, we show that shuttling is required for 40LoVe/Samba function in neural development.

  18. Oxytocin receptor polymorphism and childhood social experiences shape adult personality, brain structure and neural correlates of mentalizing.

    Science.gov (United States)

    Schneider-Hassloff, H; Straube, B; Jansen, A; Nuscheler, B; Wemken, G; Witt, S H; Rietschel, M; Kircher, T

    2016-07-01

    The oxytocin system is involved in human social behavior and social cognition such as attachment, emotion recognition and mentalizing (i.e. the ability to represent mental states of oneself and others). It is shaped by social experiences in early life, especially by parent-infant interactions. The single nucleotid polymorphism rs53576 in the oxytocin receptor (OXTR) gene has been linked to social behavioral phenotypes. In 195 adult healthy subjects we investigated the interaction of OXTR rs53576 and childhood attachment security (CAS) on the personality traits "adult attachment style" and "alexithymia" (i.e. emotional self-awareness), on brain structure (voxel-based morphometry) and neural activation (fMRI) during an interactive mentalizing paradigm (prisoner's dilemma game; subgroup: n=163). We found that in GG-homozygotes, but not in A-allele carriers, insecure childhood attachment is - in adulthood - associated with a) higher attachment-related anxiety and alexithymia, b) higher brain gray matter volume of left amygdala and lower volumes in right superior parietal lobule (SPL), left temporal pole (TP), and bilateral frontal regions, and c) higher mentalizing-related neural activity in bilateral TP and precunei, and right middle and superior frontal gyri. Interaction effects of genotype and CAS on brain volume and/or function were associated with individual differences in alexithymia and attachment-related anxiety. Interactive effects were in part sexually dimorphic. The interaction of OXTR genotype and CAS modulates adult personality as well as brain structure and function of areas implicated in salience processing and mentalizing. Rs53576 GG-homozygotes are partially more susceptible to childhood attachment experiences than A-allele carriers. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Ego Strength Development of Adolescents Involved in Adult-Sponsored Structured Activities.

    Science.gov (United States)

    Markstrom, Carol A.; Li, Xaioming; Blackshire, Shana L.; Wilfong, Juanita J.

    2005-01-01

    A psychosocial conception of ego strengths is presented in relation to adolescent involvement in adult-sponsored structured youth activities. Five-hundred and seventeen high school students completed measures on their involvement in structured activities and on 8 ego strengths. Gender, age, and SES were controlled in a MANCOVA procedure and it was…

  20. Structural Analysis of Three-dimensional Human Neural Tissue derived from Induced Pluripotent Stem Cells

    DEFF Research Database (Denmark)

    Terrence Brooks, Patrick; Rasmussen, Mikkel Aabech; Hyttel, Poul

    2016-01-01

    Objective: The present study aimed at establishing a method for production of a three-dimensional (3D) human neural tissue derived from induced pluripotent stem cells (iPSCs) and analyzing the outcome by a combination of tissue ultrastructure and expression of neural markers. Methods: A two......-step cell culture procedure was implemented by subjecting human iPSCs to a 3D scaffoldbased neural differentiation protocol. First, neural fate-inducing small molecules were used to create a neuroepithelial monolayer. Second, the monolayer was trypsinized into single cells and seeded into a porous...... polystyrene scaffold and further cultured to produce a 3D neural tissue. The neural tissue was characterized by a combination of immunohistochemistry and transmission electron microscopy (TEM). Results: iPSCs developed into a 3D neural tissue expressing markers for neural progenitor cells, early neural...

  1. Prion replication occurs in endogenous adult neural stem cells and alters their neuronal fate: involvement of endogenous neural stem cells in prion diseases.

    Directory of Open Access Journals (Sweden)

    Aroa Relaño-Ginès

    Full Text Available Prion diseases are irreversible progressive neurodegenerative diseases, leading to severe incapacity and death. They are characterized in the brain by prion amyloid deposits, vacuolisation, astrocytosis, neuronal degeneration, and by cognitive, behavioural and physical impairments. There is no treatment for these disorders and stem cell therapy therefore represents an interesting new approach. Gains could not only result from the cell transplantation, but also from the stimulation of endogenous neural stem cells (NSC or by the combination of both approaches. However, the development of such strategies requires a detailed knowledge of the pathology, particularly concerning the status of the adult neurogenesis and endogenous NSC during the development of the disease. During the past decade, several studies have consistently shown that NSC reside in the adult mammalian central nervous system (CNS and that adult neurogenesis occurs throughout the adulthood in the subventricular zone of the lateral ventricle or the Dentate Gyrus of the hippocampus. Adult NSC are believed to constitute a reservoir for neuronal replacement during normal cell turnover or after brain injury. However, the activation of this system does not fully compensate the neuronal loss that occurs during neurodegenerative diseases and could even contribute to the disease progression. We investigated here the status of these cells during the development of prion disorders. We were able to show that NSC accumulate and replicate prions. Importantly, this resulted in the alteration of their neuronal fate which then represents a new pathologic event that might underlie the rapid progression of the disease.

  2. Crystal structure of the Ig1 domain of the neural cell adhesion molecule NCAM2 displays domain swapping

    DEFF Research Database (Denmark)

    Rasmussen, Kim Krighaar; Kulahin, Nikolaj; Kristensen, Ole

    2008-01-01

    The crystal structure of the first immunoglobulin (Ig1) domain of neural cell adhesion molecule 2 (NCAM2/OCAM/RNCAM) is presented at a resolution of 2.7 A. NCAM2 is a member of the immunoglobulin superfamily of cell adhesion molecules (IgCAMs). In the structure, two Ig domains interact by domain...

  3. Effects of multitasking-training on gray matter structure and resting state neural mechanisms.

    Science.gov (United States)

    Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Hashizume, Hiroshi; Sekiguchi, Atsushi; Kotozaki, Yuka; Nakagawa, Seishu; Miyauchi, Carlos Makoto; Sassa, Yuko; Kawashima, Ryuta

    2014-08-01

    Multitasking (MT) constitutes engaging in two or more cognitive activities at the same time. MT-training improves performance on untrained MT tasks and alters the functional activity of the brain during MT. However, the effects of MT-training on neural mechanisms beyond MT-related functions are not known. We investigated the effects of 4 weeks of MT-training on regional gray matter volume (rGMV) and functional connectivity during rest (resting-FC) in young human adults. MT-training was associated with increased rGMV in three prefrontal cortical regions (left lateral rostral prefrontal cortex (PFC), dorsolateral PFC (DLPFC), and left inferior frontal junction), the left posterior parietal cortex, and the left temporal and lateral occipital areas as well as decreased resting-FC between the right DLPFC and an anatomical cluster around the ventral anterior cingulate cortex (ACC). Our findings suggest that participation in MT-training is as a whole associated with task-irrelevant plasticity (i.e., neural changes are not limited to certain specific task conditions) in regions and the network that are assumed to play roles in MT as well as diverse higher-order cognitive functions. We could not dissociate the effects of each task component and the diverse cognitive processes involved in MT because of the nature of the study, and these remain to be investigated. © 2013 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

  4. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

    Science.gov (United States)

    Abdeljaber, Osama; Avci, Onur; Kiranyaz, Serkan; Gabbouj, Moncef; Inman, Daniel J.

    2017-02-01

    Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.

  5. Effect of synapse dilution on the memory retrieval in structured attractor neural networks

    Science.gov (United States)

    Brunel, N.

    1993-08-01

    We investigate a simple model of structured attractor neural network (ANN). In this network a module codes for the category of the stored information, while another group of neurons codes for the remaining information. The probability distribution of stabilities of the patterns and the prototypes of the categories are calculated, for two different synaptic structures. The stability of the prototypes is shown to increase when the fraction of neurons coding for the category goes down. Then the effect of synapse destruction on the retrieval is studied in two opposite situations : first analytically in sparsely connected networks, then numerically in completely connected ones. In both cases the behaviour of the structured network and that of the usual homogeneous networks are compared. When lesions increase, two transitions are shown to appear in the behaviour of the structured network when one of the patterns is presented to the network. After the first transition the network recognizes the category of the pattern but not the individual pattern. After the second transition the network recognizes nothing. These effects are similar to syndromes caused by lesions in the central visual system, namely prosopagnosia and agnosia. In both types of networks (structured or homogeneous) the stability of the prototype is greater than the stability of individual patterns, however the first transition, for completely connected networks, occurs only when the network is structured.

  6. Functional and structural neural network characterization of serotonin transporter knockout rats.

    Directory of Open Access Journals (Sweden)

    Kajo van der Marel

    Full Text Available Brain serotonin homeostasis is crucially maintained by the serotonin transporter (5-HTT, and its down-regulation has been linked to increased vulnerability for anxiety- and depression-related behavior. Studies in 5-HTT knockout (5-HTT(-/- rodents have associated inherited reduced functional expression of 5-HTT with increased sensitivity to adverse as well as rewarding environmental stimuli, and in particular cocaine hyperresponsivity. 5-HTT down-regulation may affect normal neuronal wiring of implicated corticolimbic cerebral structures. To further our understanding of its contribution to potential alterations in basal functional and structural properties of neural network configurations, we applied resting-state functional MRI (fMRI, pharmacological MRI of cocaine-induced activation, and diffusion tensor imaging (DTI in 5-HTT(-/- rats and wild-type controls (5-HTT(+/+. We found that baseline functional connectivity values and cocaine-induced neural activity within the corticolimbic network was not significantly altered in 5-HTT(-/- versus 5-HTT(+/+ rats. Similarly, DTI revealed mostly intact white matter structural integrity, except for a reduced fractional anisotropy in the genu of the corpus callosum of 5-HTT(-/- rats. At the macroscopic level, analyses of complex graphs constructed from either functional connectivity values or structural DTI-based tractography results revealed that key properties of brain network organization were essentially similar between 5-HTT(+/+ and 5-HTT(-/- rats. The individual tests for differences between 5-HTT(+/+ and 5-HTT(-/- rats were capable of detecting significant effects ranging from 5.8% (fractional anisotropy to 26.1% (pharmacological MRI and 29.3% (functional connectivity. Tentatively, lower fractional anisotropy in the genu of the corpus callosum could indicate a reduced capacity for information integration across hemispheres in 5-HTT(-/- rats. Overall, the comparison of 5-HTT(-/- and wild-type rats

  7. Structural neural correlates of multitasking: A voxel-based morphometry study.

    Science.gov (United States)

    Zhang, Rui-Ting; Yang, Tian-Xiao; Wang, Yi; Sui, Yuxiu; Yao, Jingjing; Zhang, Chen-Yuan; Cheung, Eric F C; Chan, Raymond C K

    2016-12-01

    Multitasking refers to the ability to organize assorted tasks efficiently in a short period of time, which plays an important role in daily life. However, the structural neural correlates of multitasking performance remain unclear. The present study aimed at exploring the brain regions associated with multitasking performance using global correlation analysis. Twenty-six healthy participants first underwent structural brain scans and then performed the modified Six Element Test, which required participants to attempt six subtasks in 10 min while obeying a specific rule. Voxel-based morphometry of the whole brain was used to detect the structural correlates of multitasking ability. Grey matter volume of the anterior cingulate cortex (ACC) was positively correlated with the overall performance and time monitoring in multitasking. In addition, white matter volume of the anterior thalamic radiation (ATR) was also positively correlated with time monitoring during multitasking. Other related brain regions associated with multitasking included the superior frontal gyrus, the inferior occipital gyrus, the lingual gyrus, and the inferior longitudinal fasciculus. No significant correlation was found between grey matter volume of the prefrontal cortex (Brodmann Area 10) and multitasking performance. Using a global correlation analysis to examine various aspects of multitasking performance, this study provided new insights into the structural neural correlates of multitasking ability. In particular, the ACC was identified as an important brain region that played both a general and a specific time-monitoring role in multitasking, extending the role of the ACC from lesioned populations to healthy populations. The present findings also support the view that the ATR may influence multitasking performance by affecting time-monitoring abilities. © 2016 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

  8. High throughput analysis reveals dissociable gene expression profiles in two independent neural systems involved in the regulation of social behavior

    Directory of Open Access Journals (Sweden)

    Stevenson Tyler J

    2012-10-01

    Full Text Available Abstract Background Production of contextually appropriate social behaviors involves integrated activity across many brain regions. Many songbird species produce complex vocalizations called ‘songs’ that serve to attract potential mates, defend territories, and/or maintain flock cohesion. There are a series of discrete interconnect brain regions that are essential for the successful production of song. The probability and intensity of singing behavior is influenced by the reproductive state. The objectives of this study were to examine the broad changes in gene expression in brain regions that control song production with a brain region that governs the reproductive state. Results We show using microarray cDNA analysis that two discrete brain systems that are both involved in governing singing behavior show markedly different gene expression profiles. We found that cortical and basal ganglia-like brain regions that control the socio-motor production of song in birds exhibit a categorical switch in gene expression that was dependent on their reproductive state. This pattern is in stark contrast to the pattern of expression observed in a hypothalamic brain region that governs the neuroendocrine control of reproduction. Subsequent gene ontology analysis revealed marked variation in the functional categories of active genes dependent on reproductive state and anatomical localization. HVC, one cortical-like structure, displayed significant gene expression changes associated with microtubule and neurofilament cytoskeleton organization, MAP kinase activity, and steroid hormone receptor complex activity. The transitions observed in the preoptic area, a nucleus that governs the motivation to engage in singing, exhibited variation in functional categories that included thyroid hormone receptor activity, epigenetic and angiogenetic processes. Conclusions These findings highlight the importance of considering the temporal patterns of gene expression

  9. Black grandmothers in multigenerational households: diversity in family structure and parenting involvement in the Woodlawn community.

    Science.gov (United States)

    Pearson, J L; Hunter, A G; Ensminger, M E; Kellam, S G

    1990-04-01

    We report here the frequency of black grandmothers' coresidence in households with first-grade children, their patterns of involvement in parenting, and the degree to which family structure and employment affected the grandmothers' parenting involvement in a 1966/1967 community-defined population. Coresidence between grandmothers and their target first-grade grandchildren was found in 10% of the households. The 130 grandmothers' parenting involvement was substantial, second only to mother involvement, and was characterized by 2 parenting activity patterns: control and punishment, and support and punishment. The degree of grandmothers' parenting involvement differed by family structure, with grandmothers in mother-absent homes most likely to be involved. Grandmothers' employment did not moderate their engagement in parenting behaviors. These findings are consistent with previous reports of significant parenting involvement by black extended family members.

  10. Artificial-neural-network-based classification of mammographic microcalcifications using image structure features

    Science.gov (United States)

    Dhawan, Atam P.; Chitre, Yateen S.; Moskowitz, Myron

    1993-07-01

    Mammography associated with clinical breast examination and self-breast examination is the only effective and viable method for mass breast screening. It is however, difficult to distinguish between benign and malignant microcalcifications associated with breast cancer. Most of the techniques used in the computerized analysis of mammographic microcalcifications segment the digitized gray-level image into regions representing microcalcifications. We present a second-order gray-level histogram based feature extraction approach to extract microcalcification features. These features, called image structure features, are computed from the second-order gray-level histogram statistics, and do not require segmentation of the original image into binary regions. Several image structure features were computed for 100 cases of `difficult to diagnose' microcalcification cases with known biopsy results. These features were analyzed in a correlation study which provided a set of five best image structure features. A feedforward backpropagation neural network was used to classify mammographic microcalcifications using the image structure features. The network was trained on 10 cases of mammographic microcalcifications and tested on additional 85 `difficult-to-diagnose' microcalcifications cases using the selected image structure features. The trained network yielded good results for classification of `difficult-to- diagnose' microcalcifications into benign and malignant categories.

  11. A closer look at the apparent correlation of structural and functional connectivity in excitable neural networks

    Science.gov (United States)

    Messé, Arnaud; Hütt, Marc-Thorsten; König, Peter; Hilgetag, Claus C.

    2015-01-01

    The relationship between the structural connectivity (SC) and functional connectivity (FC) of neural systems is a central focus in brain network science. It is an open question, however, how strongly the SC-FC relationship depends on specific topological features of brain networks or the models used for describing excitable dynamics. Using a basic model of discrete excitable units that follow a susceptible - excited - refractory dynamic cycle (SER model), we here analyze how functional connectivity is shaped by the topological features of a neural network, in particular its modularity. We compared the results obtained by the SER model with corresponding simulations by another well established dynamic mechanism, the Fitzhugh-Nagumo model, in order to explore general features of the SC-FC relationship. We showed that apparent discrepancies between the results produced by the two models can be resolved by adjusting the time window of integration of co-activations from which the FC is derived, providing a clearer distinction between co-activations and sequential activations. Thus, network modularity appears as an important factor shaping the FC-SC relationship across different dynamic models.

  12. CNNdel: Calling Structural Variations on Low Coverage Data Based on Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Jing Wang

    2017-01-01

    Full Text Available Many structural variations (SVs detection methods have been proposed due to the popularization of next-generation sequencing (NGS. These SV calling methods use different SV-property-dependent features; however, they all suffer from poor accuracy when running on low coverage sequences. The union of results from these tools achieves fairly high sensitivity but still produces low accuracy on low coverage sequence data. That is, these methods contain many false positives. In this paper, we present CNNdel, an approach for calling deletions from paired-end reads. CNNdel gathers SV candidates reported by multiple tools and then extracts features from aligned BAM files at the positions of candidates. With labeled feature-expressed candidates as a training set, CNNdel trains convolutional neural networks (CNNs to distinguish true unlabeled candidates from false ones. Results show that CNNdel works well with NGS reads from 26 low coverage genomes of the 1000 Genomes Project. The paper demonstrates that convolutional neural networks can automatically assign the priority of SV features and reduce the false positives efficaciously.

  13. A hybrid neural network structure for application to nondestructive TRU waste assay

    Energy Technology Data Exchange (ETDEWEB)

    Becker, G. [Idaho National Engineering Lab., Idaho Falls, ID (United States)

    1995-12-31

    The determination of transuranic (TRU) and associated radioactive material quantities entrained in waste forms is a necessary component. of waste characterization. Measurement performance requirements are specified in the National TRU Waste Characterization Program quality assurance plan for which compliance must be demonstrated prior to the transportation and disposition of wastes. With respect to this criterion, the existing TRU nondestructive waste assay (NDA) capability is inadequate for a significant fraction of the US Department of Energy (DOE) complex waste inventory. This is a result of the general application of safeguard-type measurement and calibration schemes to waste form configurations. Incompatibilities between such measurement methods and actual waste form configurations complicate regulation compliance demonstration processes and illustrate the need for an alternate measurement interpretation paradigm. Hence, it appears necessary to supplement or perhaps restructure the perceived solution and approach to the waste NDA problem. The first step is to understand the magnitude of the waste matrix/source attribute space associated with those waste form configurations in inventory and how this creates complexities and unknowns with respect to existing NDA methods. Once defined and/or bounded, a conceptual method must be developed that specifies the necessary tools and the framework in which the tools are used. A promising framework is a hybridized neural network structure. Discussed are some typical complications associated with conventional waste NDA techniques and how improvements can be obtained through the application of neural networks.

  14. Neural and sympathetic activity associated with exploration in decision-making: Further evidence for involvement of insula

    Directory of Open Access Journals (Sweden)

    Hideki eOhira

    2014-11-01

    Full Text Available We previously reported that sympathetic activity was associated with exploration in decision-making indexed by entropy, which is a concept in information theory and indexes randomness of choices or the degree of deviation from sticking to recent experiences of gains and losses, and that activation of the anterior insula mediated this association. The current study aims to replicate and to expand these findings in a situation where contingency between options and outcomes is manipulated. Sixteen participants performed a stochastic decision-making task in which we manipulated a condition with low uncertainty of gain/loss (contingent-reward condition and a condition with high uncertainty of gain/loss (random-reward condition. Regional cerebral blood flow was measured by 15O-water positron emission tomography (PET, and cardiovascular parameters and catecholamine in the peripheral blood were measured, during the task. In the contingent-reward condition, norepinephrine as an index of sympathetic activity was positively correlated with entropy indicating exploration in decision-making. Norepinephrine was negatively correlated with neural activity in the right posterior insula, rostral anterior cingulate cortex, and dorsal pons, suggesting neural bases for detecting changes of bodily states. Furthermore, right anterior insular activity was negatively correlated with entropy, suggesting influences on exploration in decision-making. By contrast, in the random-reward condition, entropy correlated with activity in the dorsolateral prefrontal and parietal cortices but not with sympathetic activity. These findings suggest that influences of sympathetic activity on exploration in decision-making and its underlying neural mechanisms might be dependent on the degree of uncertainty of situations.

  15. Incorporation of iodine into apatite structure: a crystal chemistry approach using Artificial Neural Network

    Science.gov (United States)

    Wang, Jianwei

    2015-06-01

    Materials with apatite crystal structure provide a great potential for incorporating the long-lived radioactive iodine isotope (129I) in the form of iodide (I-) from nuclear waste streams. Because of its durability and potentially high iodine content, the apatite waste form can reduce iodine release rate and minimize the waste volume. Crystal structure and composition of apatite was investigated for iodide incorporation into the channel of the structure using Artificial Neural Network. A total of 86 experimentally determined apatite crystal structures of different compositions were compiled from literature, and 46 of them were used to train the networks and 42 were used to test the performance of the trained networks. The results show that the performances of the networks are satisfactory for predictions of unit cell parameters a and c and channel size of the structure. The trained and tested networks were then used to predict unknown compositions of apatite that incorporates iodide. With a crystal chemistry consideration, chemical compositions that lead to matching the size of the structural channel to the size of iodide were then predicted to be able to incorporate iodide in the structural channel. The calculations suggest that combinations of A site cations of Ag+, K+, Sr2+, Pb2+, Ba2+, and Cs+, and X site cations, mostly formed tetrahedron, of Mn5+, As5+, Cr5+, V5+, Mo5+, Si4+, Ge4+, and Re7+ are possible apatite compositions that are able to incorporate iodide. The charge balance of different apatite compositions can be achieved by multiple substitutions at a single site or coupled substitutions at both A and X sites. The results give important clues for designing experiments to synthesize new apatite compositions and also provide a fundamental understanding how iodide is incorporated in the apatite structure. This understanding can provide important insights for apatite waste forms design by optimizing the chemical composition and synthesis procedure.

  16. Effectiveness of a Treatment Involving Soft Tissue Techniques and/or Neural Mobilization Techniques in the Management of Tension-Type Headache: A Randomized Controlled Trial.

    Science.gov (United States)

    Ferragut-Garcías, Alejandro; Plaza-Manzano, Gustavo; Rodríguez-Blanco, Cleofás; Velasco-Roldán, Olga; Pecos-Martín, Daniel; Oliva-Pascual-Vaca, Jesús; Llabrés-Bennasar, Bartomeu; Oliva-Pascual-Vaca, Ángel

    2017-02-01

    To evaluate the effects of a protocol involving soft tissue techniques and/or neural mobilization techniques in the management of patients with frequent episodic tension-type headache (FETTH) and those with chronic tension-type headache (CTTH). Randomized, double-blind, placebo-controlled before and after trial. Rehabilitation area of the local hospital and a private physiotherapy center. Patients (N=97; 78 women, 19 men) diagnosed with FETTH or CTTH were randomly assigned to groups A, B, C, or D. (A) Placebo superficial massage; (B) soft tissue techniques; (C) neural mobilization techniques; (D) a combination of soft tissue and neural mobilization techniques. The pressure pain threshold (PPT) in the temporal muscles (points 1 and 2) and supraorbital region (point 3), the frequency and maximal intensity of pain crisis, and the score in the Headache Impact Test-6 (HIT-6) were evaluated. All variables were assessed before the intervention, at the end of the intervention, and 15 and 30 days after the intervention. Groups B, C, and D had an increase in PPT and a reduction in frequency, maximal intensity, and HIT-6 values in all time points after the intervention as compared with baseline and group A (P<.001 for all cases). Group D had the highest PPT values and the lowest frequency and HIT-6 values after the intervention. The application of soft tissue and neural mobilization techniques to patients with FETTH or CTTH induces significant changes in PPT, the characteristics of pain crisis, and its effect on activities of daily living as compared with the application of these techniques as isolated interventions. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  17. Dynamic changes in Ezh2 gene occupancy underlie its involvement in neural stem cell self-renewal and differentiation towards oligodendrocytes.

    Directory of Open Access Journals (Sweden)

    Falak Sher

    Full Text Available The polycomb group protein Ezh2 is an epigenetic repressor of transcription originally found to prevent untimely differentiation of pluripotent embryonic stem cells. We previously demonstrated that Ezh2 is also expressed in multipotent neural stem cells (NSCs. We showed that Ezh2 expression is downregulated during NSC differentiation into astrocytes or neurons. However, high levels of Ezh2 remained present in differentiating oligodendrocytes until myelinating. This study aimed to elucidate the target genes of Ezh2 in NSCs and in premyelinating oligodendrocytes (pOLs.We performed chromatin immunoprecipitation followed by high-throughput sequencing to detect the target genes of Ezh2 in NSCs and pOLs. We found 1532 target genes of Ezh2 in NSCs. During NSC differentiation, the occupancy of these genes by Ezh2 was alleviated. However, when the NSCs differentiated into oligodendrocytes, 393 of these genes remained targets of Ezh2. Analysis of the target genes indicated that the repressive activity of Ezh2 in NSCs concerns genes involved in stem cell maintenance, in cell cycle control and in preventing neural differentiation. Among the genes in pOLs that were still repressed by Ezh2 were most prominently those associated with neuronal and astrocytic committed cell lineages. Suppression of Ezh2 activity in NSCs caused loss of stem cell characteristics, blocked their proliferation and ultimately induced apoptosis. Suppression of Ezh2 activity in pOLs resulted in derangement of the oligodendrocytic phenotype, due to re-expression of neuronal and astrocytic genes, and ultimately in apoptosis.Our data indicate that the epigenetic repressor Ezh2 in NSCs is crucial for proliferative activity and maintenance of neural stemness. During differentiation towards oligodendrocytes, Ezh2 repression continues particularly to suppress other neural fate choices. Ezh2 is completely downregulated during differentiation towards neurons and astrocytes allowing transcription

  18. Ten-Structure as Strategy of Addition 1-20 by Involving Spatial Structuring Ability for First Grade Students

    Science.gov (United States)

    Salmah, Ummy; Putri, Ratu Ilma Indra; Somakim

    2015-01-01

    The aim of this study is to design learning activities that can support students to develop strategies for the addition of number 1 to 20 in the first grade by involving students' spatial structuring ability. This study was conducted in Indonesia by involving 27 students. In this paper, one of three activities is discussed namely ten-box activity.…

  19. A simple structure wavelet transform circuit employing function link neural networks and SI filters

    Science.gov (United States)

    Mu, Li; Yigang, He

    2016-12-01

    Signal processing by means of analog circuits offers advantages from a power consumption viewpoint. Implementing wavelet transform (WT) using analog circuits is of great interest when low-power consumption becomes an important issue. In this article, a novel simple structure WT circuit in analog domain is presented by employing functional link neural network (FLNN) and switched-current (SI) filters. First, the wavelet base is approximated using FLNN algorithms for giving a filter transfer function that is suitable for simple structure WT circuit implementation. Next, the WT circuit is constructed with the wavelet filter bank, whose impulse response is the approximated wavelet and its dilations. The filter design that follows is based on a follow-the-leader feedback (FLF) structure with multiple output bilinear SI integrators and current mirrors as the main building blocks. SI filter is well suited for this application since the dilation constant across different scales of the transform can be precisely implemented and controlled by the clock frequency of the circuit with the same system architecture. Finally, to illustrate the design procedure, a seventh-order FLNN-approximated Gaussian wavelet is implemented as an example. Simulations have successfully verified that the designed simple structure WT circuit has low sensitivity, low-power consumption and litter effect to the imperfections.

  20. The necessity of connection structures in neural models of variable binding.

    Science.gov (United States)

    van der Velde, Frank; de Kamps, Marc

    2015-08-01

    In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

  1. Neural-Net Based Optical NDE Method for Structural Health Monitoring

    Science.gov (United States)

    Decker, Arthur J.; Weiland, Kenneth E.

    2003-01-01

    This paper answers some performance and calibration questions about a non-destructive-evaluation (NDE) procedure that uses artificial neural networks to detect structural damage or other changes from sub-sampled characteristic patterns. The method shows increasing sensitivity as the number of sub-samples increases from 108 to 6912. The sensitivity of this robust NDE method is not affected by noisy excitations of the first vibration mode. A calibration procedure is proposed and demonstrated where the output of a trained net can be correlated with the outputs of the point sensors used for vibration testing. The calibration procedure is based on controlled changes of fastener torques. A heterodyne interferometer is used as a displacement sensor for a demonstration of the challenges to be handled in using standard point sensors for calibration.

  2. The Development of a Structural Equation Model to Demonstrate the Correlations between Marijuana Use and Involvement

    Science.gov (United States)

    Borcherding, Matthew J.

    2017-01-01

    This quantitative study examined the effects of marijuana on academic and social involvement in undergraduates using a structural equation model. The study was conducted at a midsized comprehensive community college in the Midwest and was guided by Astin's (1985) theory of student involvement. A survey link was e-mailed to all 4,527 eligible…

  3. Neural substrates involved in anger induced by audio-visual film clips among patients with alcohol dependency.

    Science.gov (United States)

    Park, Mi-Sook; Lee, Bae Hwan; Sohn, Jin-Hun

    2016-07-08

    Very little is known about the neural circuitry underlying anger processing among alcoholics. The purpose of this study was to examine the altered brain activity of alcoholic individuals during transient anger emotion. Using functional magnetic resonance imaging (fMRI), 18 male patients diagnosed with alcohol dependence in an inpatient alcohol treatment facility and 16 social drinkers with similar demographics were scanned during the viewing of anger-provoking film clips. While there was no significant difference in the level of experienced anger between alcohol-dependent patients and non-alcoholic controls, significantly greater activation was observed in the bilateral dorsal anterior cingulate cortex (dACC) and the right precentral gyrus among alcoholic patients compared to the normal controls. In summary, specific brain regions were identified that are associated with anger among patients with alcohol dependency.

  4. The morphology of the sella turcica in velocardiofacial syndrome suggests involvement of a neural crest developmental field

    DEFF Research Database (Denmark)

    Mølsted, Kirsten; Boers, Maria; Kjaer, Inger

    2010-01-01

    was to measure the cranial base angles in individuals with VCFS and, if possible, to discover the developmental field that may be involved in the condition. The study included 33 patients with VCFS from the Copenhagen Cleft Palate Center, Denmark. The genotype was confirmed by fluorescence in situ hybridization......, hypothyroidism, and posterior brain abnormality), suggest involvement of a specific developmental field....

  5. Nonlinear dynamic systems identification using recurrent interval type-2 TSK fuzzy neural network - A novel structure.

    Science.gov (United States)

    El-Nagar, Ahmad M

    2017-10-31

    In this study, a novel structure of a recurrent interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy neural network (FNN) is introduced for nonlinear dynamic and time-varying systems identification. It combines the type-2 fuzzy sets (T2FSs) and a recurrent FNN to avoid the data uncertainties. The fuzzy firing strengths in the proposed structure are returned to the network input as internal variables. The interval type-2 fuzzy sets (IT2FSs) is used to describe the antecedent part for each rule while the consequent part is a TSK-type, which is a linear function of the internal variables and the external inputs with interval weights. All the type-2 fuzzy rules for the proposed RIT2TSKFNN are learned on-line based on structure and parameter learning, which are performed using the type-2 fuzzy clustering. The antecedent and consequent parameters of the proposed RIT2TSKFNN are updated based on the Lyapunov function to achieve network stability. The obtained results indicate that our proposed network has a small root mean square error (RMSE) and a small integral of square error (ISE) with a small number of rules and a small computation time compared with other type-2 FNNs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Preschool externalizing behavior predicts gender-specific variation in adolescent neural structure.

    Directory of Open Access Journals (Sweden)

    Jessica Z K Caldwell

    Full Text Available Dysfunction in the prefrontal cortex, amygdala, and hippocampus is believed to underlie the development of much psychopathology. However, to date only limited longitudinal data relate early behavior with neural structure later in life. Our objective was to examine the relationship of early life externalizing behavior with adolescent brain structure. We report here the first longitudinal study linking externalizing behavior during preschool to brain structure during adolescence. We examined the relationship of preschool externalizing behavior with amygdala, hippocampus, and prefrontal cortex volumes at age 15 years in a community sample of 76 adolescents followed longitudinally since their mothers' pregnancy. A significant gender by externalizing behavior interaction revealed that males-but not females-with greater early childhood externalizing behavior had smaller amygdala volumes at adolescence (t = 2.33, p = .023. No significant results were found for the hippocampus or the prefrontal cortex. Greater early externalizing behavior also related to smaller volume of a cluster including the angular gyrus and tempoparietal junction across genders. Results were not attributable to the impact of preschool anxiety, preschool maternal stress, school-age internalizing or externalizing behaviors, or adolescent substance use. These findings demonstrate a novel, gender-specific relationship between early-childhood externalizing behavior and adolescent amygdala volume, as well as a cross-gender result for the angular gyrus and tempoparietal junction.

  7. Sensory-related neural activity regulates the structure of vascular networks in the cerebral cortex

    Science.gov (United States)

    Lacoste, Baptiste; Comin, Cesar H.; Ben-Zvi, Ayal; Kaeser, Pascal S.; Xu, Xiaoyin; Costa, Luciano da F.; Gu, Chenghua

    2014-01-01

    SUMMARY Neurovascular interactions are essential for proper brain function. While the effect of neural activity on cerebral blood flow has been extensively studied, whether neural activity influences vascular patterning remains elusive. Here, we demonstrate that neural activity promotes the formation of vascular networks in the early postnatal mouse barrel cortex. Using a combination of genetics, imaging, and computational tools to allow simultaneous analysis of neuronal and vascular components, we found that vascular density and branching were decreased in the barrel cortex when sensory input was reduced by either a complete deafferentation, a genetic impairment of neurotransmitter release at thalamocortical synapses, or a selective reduction of sensory-related neural activity by whisker plucking. In contrast, enhancement of neural activity by whisker stimulation led to an increase in vascular density and branching. The finding that neural activity is necessary and sufficient to trigger alterations of vascular networks reveals a novel feature of neurovascular interactions. PMID:25155955

  8. Sensory-related neural activity regulates the structure of vascular networks in the cerebral cortex.

    Science.gov (United States)

    Lacoste, Baptiste; Comin, Cesar H; Ben-Zvi, Ayal; Kaeser, Pascal S; Xu, Xiaoyin; Costa, Luciano da F; Gu, Chenghua

    2014-09-03

    Neurovascular interactions are essential for proper brain function. While the effect of neural activity on cerebral blood flow has been extensively studied, whether or not neural activity influences vascular patterning remains elusive. Here, we demonstrate that neural activity promotes the formation of vascular networks in the early postnatal mouse barrel cortex. Using a combination of genetics, imaging, and computational tools to allow simultaneous analysis of neuronal and vascular components, we found that vascular density and branching were decreased in the barrel cortex when sensory input was reduced by either a complete deafferentation, a genetic impairment of neurotransmitter release at thalamocortical synapses, or a selective reduction of sensory-related neural activity by whisker plucking. In contrast, enhancement of neural activity by whisker stimulation led to an increase in vascular density and branching. The finding that neural activity is necessary and sufficient to trigger alterations of vascular networks reveals an important feature of neurovascular interactions. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. The structure of parental involvement and relations to disease management for youth with type 1 diabetes.

    Science.gov (United States)

    Palmer, Debra L; Osborn, Peter; King, Pamela S; Berg, Cynthia A; Butler, Jorie; Butner, Jonathan; Horton, Dwayne; Wiebe, Deborah J

    2011-06-01

    To test structural models of parental involvement in type 1 diabetes and to examine associations of parental involvement with adherence and metabolic control. Two hundred and fifty-two young adolescents (10-14 years) completed reports of adherence and parents' involvement: acceptance, independence encouragement, communication, general and diabetes-specific monitoring, frequency of help, and intrusive support. HbA(1c) values came from medical records. A model of relationship quality, behavioral involvement, and monitoring as three separate yet interrelated factors best fit the data. Higher reports of mothers' and fathers' monitoring and fathers' relationship quality uniquely related to better adherence, whereas higher reports of fathers' behavioral involvement uniquely related to poorer adherence. Higher reports of paternal monitoring were related to lower HbA(1c). Adolescent perceptions of components of parental involvement are interrelated, yet separate constructs for both mothers and fathers. Parental monitoring was an important predictor of management of type 1 diabetes during adolescence.

  10. The music of your emotions: neural substrates involved in detection of emotional correspondence between auditory and visual music actions.

    Directory of Open Access Journals (Sweden)

    Karin Petrini

    Full Text Available In humans, emotions from music serve important communicative roles. Despite a growing interest in the neural basis of music perception, action and emotion, the majority of previous studies in this area have focused on the auditory aspects of music performances. Here we investigate how the brain processes the emotions elicited by audiovisual music performances. We used event-related functional magnetic resonance imaging, and in Experiment 1 we defined the areas responding to audiovisual (musician's movements with music, visual (musician's movements only, and auditory emotional (music only displays. Subsequently a region of interest analysis was performed to examine if any of the areas detected in Experiment 1 showed greater activation for emotionally mismatching performances (combining the musician's movements with mismatching emotional sound than for emotionally matching music performances (combining the musician's movements with matching emotional sound as presented in Experiment 2 to the same participants. The insula and the left thalamus were found to respond consistently to visual, auditory and audiovisual emotional information and to have increased activation for emotionally mismatching displays in comparison with emotionally matching displays. In contrast, the right thalamus was found to respond to audiovisual emotional displays and to have similar activation for emotionally matching and mismatching displays. These results suggest that the insula and left thalamus have an active role in detecting emotional correspondence between auditory and visual information during music performances, whereas the right thalamus has a different role.

  11. Developmental iodine deficiency and hypothyroidism impair neural development in rat hippocampus: involvement of doublecortin and NCAM-180

    Science.gov (United States)

    2010-01-01

    Background Developmental iodine deficiency results in inadequate thyroid hormone (TH), which damages the hippocampus. Here, we explored the roles of hippocampal doublecortin and neural cell adhesion molecule (NCAM)-180 in developmental iodine deficiency and hypothyroidism. Methods Two developmental rat models were established with either an iodine-deficient diet, or propylthiouracil (PTU)-adulterated water (5 ppm or 15 ppm) to impair thyroid function, in pregnant rats from gestational day 6 until postnatal day (PN) 28. Silver-stained neurons and protein levels of doublecortin and NCAM-180 in several hippocampal subregions were assessed on PN14, PN21, PN28, and PN42. Results The results show that nerve fibers in iodine-deficient and 15 ppm PTU-treated rats were injured on PN28 and PN42. Downregulation of doublecortin and upregulation of NCAM-180 were observed in iodine-deficient and 15 ppm PTU-treated rats from PN14 on. These alterations were irreversible by the restoration of serum TH concentrations on PN42. Conclusion Developmental iodine deficiency and hypothyroidism impair the expression of doublecortin and NCAM-180, leading to nerve fiber malfunction and thus impairments in hippocampal development. PMID:20412599

  12. Developmental iodine deficiency and hypothyroidism impair neural development in rat hippocampus: involvement of doublecortin and NCAM-180

    Directory of Open Access Journals (Sweden)

    Zhong Jiapeng

    2010-04-01

    Full Text Available Abstract Background Developmental iodine deficiency results in inadequate thyroid hormone (TH, which damages the hippocampus. Here, we explored the roles of hippocampal doublecortin and neural cell adhesion molecule (NCAM-180 in developmental iodine deficiency and hypothyroidism. Methods Two developmental rat models were established with either an iodine-deficient diet, or propylthiouracil (PTU-adulterated water (5 ppm or 15 ppm to impair thyroid function, in pregnant rats from gestational day 6 until postnatal day (PN 28. Silver-stained neurons and protein levels of doublecortin and NCAM-180 in several hippocampal subregions were assessed on PN14, PN21, PN28, and PN42. Results The results show that nerve fibers in iodine-deficient and 15 ppm PTU-treated rats were injured on PN28 and PN42. Downregulation of doublecortin and upregulation of NCAM-180 were observed in iodine-deficient and 15 ppm PTU-treated rats from PN14 on. These alterations were irreversible by the restoration of serum TH concentrations on PN42. Conclusion Developmental iodine deficiency and hypothyroidism impair the expression of doublecortin and NCAM-180, leading to nerve fiber malfunction and thus impairments in hippocampal development.

  13. The music of your emotions: neural substrates involved in detection of emotional correspondence between auditory and visual music actions.

    Science.gov (United States)

    Petrini, Karin; Crabbe, Frances; Sheridan, Carol; Pollick, Frank E

    2011-04-29

    In humans, emotions from music serve important communicative roles. Despite a growing interest in the neural basis of music perception, action and emotion, the majority of previous studies in this area have focused on the auditory aspects of music performances. Here we investigate how the brain processes the emotions elicited by audiovisual music performances. We used event-related functional magnetic resonance imaging, and in Experiment 1 we defined the areas responding to audiovisual (musician's movements with music), visual (musician's movements only), and auditory emotional (music only) displays. Subsequently a region of interest analysis was performed to examine if any of the areas detected in Experiment 1 showed greater activation for emotionally mismatching performances (combining the musician's movements with mismatching emotional sound) than for emotionally matching music performances (combining the musician's movements with matching emotional sound) as presented in Experiment 2 to the same participants. The insula and the left thalamus were found to respond consistently to visual, auditory and audiovisual emotional information and to have increased activation for emotionally mismatching displays in comparison with emotionally matching displays. In contrast, the right thalamus was found to respond to audiovisual emotional displays and to have similar activation for emotionally matching and mismatching displays. These results suggest that the insula and left thalamus have an active role in detecting emotional correspondence between auditory and visual information during music performances, whereas the right thalamus has a different role.

  14. A Physics-driven Neural Networks-based Simulation System (PhyNNeSS) for multimodal interactive virtual environments involving nonlinear deformable objects.

    Science.gov (United States)

    De, Suvranu; Deo, Dhannanjay; Sankaranarayanan, Ganesh; Arikatla, Venkata S

    2011-08-01

    BACKGROUND: While an update rate of 30 Hz is considered adequate for real time graphics, a much higher update rate of about 1 kHz is necessary for haptics. Physics-based modeling of deformable objects, especially when large nonlinear deformations and complex nonlinear material properties are involved, at these very high rates is one of the most challenging tasks in the development of real time simulation systems. While some specialized solutions exist, there is no general solution for arbitrary nonlinearities. METHODS: In this work we present PhyNNeSS - a Physics-driven Neural Networks-based Simulation System - to address this long-standing technical challenge. The first step is an off-line pre-computation step in which a database is generated by applying carefully prescribed displacements to each node of the finite element models of the deformable objects. In the next step, the data is condensed into a set of coefficients describing neurons of a Radial Basis Function network (RBFN). During real-time computation, these neural networks are used to reconstruct the deformation fields as well as the interaction forces. RESULTS: We present realistic simulation examples from interactive surgical simulation with real time force feedback. As an example, we have developed a deformable human stomach model and a Penrose-drain model used in the Fundamentals of Laparoscopic Surgery (FLS) training tool box. CONCLUSIONS: A unique computational modeling system has been developed that is capable of simulating the response of nonlinear deformable objects in real time. The method distinguishes itself from previous efforts in that a systematic physics-based pre-computational step allows training of neural networks which may be used in real time simulations. We show, through careful error analysis, that the scheme is scalable, with the accuracy being controlled by the number of neurons used in the simulation. PhyNNeSS has been integrated into SoFMIS (Software Framework for Multimodal

  15. A Damage Prognosis Method of Girder Structures Based on Wavelet Neural Networks

    Directory of Open Access Journals (Sweden)

    Rumian Zhong

    2014-01-01

    Full Text Available Based on the basic theory of wavelet neural networks and finite element model updating method, a basic framework of damage prognosis method is proposed in this paper. Firstly, a damaged I-steel beam model testing is used to verify the feasibility and effectiveness of the proposed damage prognosis method. The results show that the predicted results of the damage prognosis method and the measured results are very well consistent, and the maximum error is less than 5%. Furthermore, Xinyihe Bridge in the Beijing-Shanghai Highway is selected as the engineering background, and the damage prognosis is conducted based on the data from the structural health monitoring system. The results show that the traffic volume will increase and seasonal differences will decrease in the next year and a half. The displacement has a slight increase and seasonal characters in the critical section of mid span, but the strain will increase distinctly. The analysis results indicate that the proposed method can be applied to the damage prognosis of girder bridge structures and has the potential for the bridge health monitoring and safety prognosis.

  16. Frontal Structural Neural Correlates of Working Memory Performance in Older Adults

    Science.gov (United States)

    Nissim, Nicole R.; O’Shea, Andrew M.; Bryant, Vaughn; Porges, Eric C.; Cohen, Ronald; Woods, Adam J.

    2017-01-01

    Working memory is an executive memory process that allows transitional information to be held and manipulated temporarily in memory stores before being forgotten or encoded into long-term memory. Working memory is necessary for everyday decision-making and problem solving, making it a fundamental process in the daily lives of older adults. Working memory relies heavily on frontal lobe structures and is known to decline with age. The current study aimed to determine the neural correlates of decreased working memory performance in the frontal lobes by comparing cortical thickness and cortical surface area from two demographically matched groups of healthy older adults, free from cognitive impairment, with high versus low N-Back working memory performance (N = 56; average age = 70.29 ± 10.64). High-resolution structural T1-weighted images (1 mm isotropic voxels) were obtained on a 3T Philips MRI scanner. When compared to high performers, low performers exhibited significantly decreased cortical surface area in three frontal lobe regions lateralized to the right hemisphere: medial orbital frontal gyrus, inferior frontal gyrus, and superior frontal gyrus (FDR p working memory function. PMID:28101053

  17. BrainSegNet: a convolutional neural network architecture for automated segmentation of human brain structures.

    Science.gov (United States)

    Mehta, Raghav; Majumdar, Aabhas; Sivaswamy, Jayanthi

    2017-04-01

    Automated segmentation of cortical and noncortical human brain structures has been hitherto approached using nonrigid registration followed by label fusion. We propose an alternative approach for this using a convolutional neural network (CNN) which classifies a voxel into one of many structures. Four different kinds of two-dimensional and three-dimensional intensity patches are extracted for each voxel, providing local and global (context) information to the CNN. The proposed approach is evaluated on five different publicly available datasets which differ in the number of labels per volume. The obtained mean Dice coefficient varied according to the number of labels, for example, it is [Formula: see text] and [Formula: see text] for datasets with the least (32) and the most (134) number of labels, respectively. These figures are marginally better or on par with those obtained with the current state-of-the-art methods on nearly all datasets, at a reduced computational time. The consistently good performance of the proposed method across datasets and no requirement for registration make it attractive for many applications where reduced computational time is necessary.

  18. Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

    Science.gov (United States)

    Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

    2017-10-23

    Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.

  19. Neural correlates and structural markers of emotion dysregulation in traumatized civilians

    Science.gov (United States)

    Stevens, Jennifer S.; van Rooij, Sanne J.H.; Ely, Timothy D.; Fani, Negar; Jovanovic, Tanja; Ressler, Kerry J.; Bradley, Bekh

    2017-01-01

    Abstract Emotion dysregulation (ED) reflects deficits in understanding and managing negative emotions and may serve as a transdiagnostic mechanism of risk for trauma-related psychiatric disorders. Therefore, understanding neurobiological substrates of ED in traumatized individuals is critical. The present study examined associations between ED and baseline structural differences and patterns of functional activity during an emotional task in a sample of African American women (n = 136) recruited from an urban hospital. Participants engaged in a structural magnetic resonance imaging (MRI) session. A subsample (n = 92) also viewed emotional face stimuli during functional MRI. ED was related to greater dorsal anterior cingulate cortex (dACC) surface area (Pcorr < 0.05) and increased dorsomedial prefrontal cortex (dmPFC) and ventromedial PFC activation to fearful stimuli (Pcorr < 0.05), independent of the trauma and psychiatric symptoms. DMPFC activation was also associated with posttraumatic stress disorder and depression symptoms. Mediation analyses showed a significant mediation effect of ED on the relation between dmPFC activation and psychiatric symptoms. These findings are important since dACC and dmPFC play central roles in fear expression and attention to emotional stimuli. Future longitudinal research is needed to help solidify a model of risk for how such neural substrates may be impacted by traumatic experiences to create ED. PMID:28158800

  20. Inverse analysis of aerodynamic loads from strain information using structural models and neural networks

    Science.gov (United States)

    Wada, Daichi; Sugimoto, Yohei

    2017-04-01

    Aerodynamic loads on aircraft wings are one of the key parameters to be monitored for reliable and effective aircraft operations and management. Flight data of the aerodynamic loads would be used onboard to control the aircraft and accumulated data would be used for the condition-based maintenance and the feedback for the fatigue and critical load modeling. The effective sensing techniques such as fiber optic distributed sensing have been developed and demonstrated promising capability of monitoring structural responses, i.e., strains on the surface of the aircraft wings. By using the developed techniques, load identification methods for structural health monitoring are expected to be established. The typical inverse analysis for load identification using strains calculates the loads in a discrete form of concentrated forces, however, the distributed form of the loads is essential for the accurate and reliable estimation of the critical stress at structural parts. In this study, we demonstrate an inverse analysis to identify the distributed loads from measured strain information. The introduced inverse analysis technique calculates aerodynamic loads not in a discrete but in a distributed manner based on a finite element model. In order to verify the technique through numerical simulations, we apply static aerodynamic loads on a flat panel model, and conduct the inverse identification of the load distributions. We take two approaches to build the inverse system between loads and strains. The first one uses structural models and the second one uses neural networks. We compare the performance of the two approaches, and discuss the effect of the amount of the strain sensing information.

  1. Revisiting the Neural Basis of Acquired Amusia: Lesion Patterns and Structural Changes Underlying Amusia Recovery

    Directory of Open Access Journals (Sweden)

    Aleksi J. Sihvonen

    2017-07-01

    Full Text Available Although, acquired amusia is a common deficit following stroke, relatively little is still known about its precise neural basis, let alone to its recovery. Recently, we performed a voxel-based lesion-symptom mapping (VLSM and morphometry (VBM study which revealed a right lateralized lesion pattern, and longitudinal gray matter volume (GMV and white matter volume (WMV changes that were specifically associated with acquired amusia after stroke. In the present study, using a larger sample of stroke patients (N = 90, we aimed to replicate and extend the previous structural findings as well as to determine the lesion patterns and volumetric changes associated with amusia recovery. Structural MRIs were acquired at acute and 6-month post-stroke stages. Music perception was behaviorally assessed at acute and 3-month post-stroke stages using the Scale and Rhythm subtests of the Montreal Battery of Evaluation of Amusia (MBEA. Using these scores, the patients were classified as non-amusic, recovered amusic, and non-recovered amusic. The results of the acute stage VLSM analyses and the longitudinal VBM analyses converged to show that more severe and persistent (non-recovered amusia was associated with an extensive pattern of lesions and GMV/WMV decrease in right temporal, frontal, parietal, striatal, and limbic areas. In contrast, less severe and transient (recovered amusia was linked to lesions specifically in left inferior frontal gyrus as well as to a GMV decrease in right parietal areas. Separate continuous analyses of MBEA Scale and Rhythm scores showed extensively overlapping lesion pattern in right temporal, frontal, and subcortical structures as well as in the right insula. Interestingly, the recovered pitch amusia was related to smaller GMV decreases in the temporoparietal junction whereas the recovered rhythm amusia was associated to smaller GMV decreases in the inferior temporal pole. Overall, the results provide a more comprehensive picture of

  2. Customer involvement in greening the supply chain: an interpretive structural modeling methodology

    Science.gov (United States)

    Kumar, Sanjay; Luthra, Sunil; Haleem, Abid

    2013-04-01

    The role of customers in green supply chain management needs to be identified and recognized as an important research area. This paper is an attempt to explore the involvement aspect of customers towards greening of the supply chain (SC). An empirical research approach has been used to collect primary data to rank different variables for effective customer involvement in green concept implementation in SC. An interpretive structural-based model has been presented, and variables have been classified using matrice d' impacts croises- multiplication appliqué a un classement analysis. Contextual relationships among variables have been established using experts' opinions. The research may help practicing managers to understand the interaction among variables affecting customer involvement. Further, this understanding may be helpful in framing the policies and strategies to green SC. Analyzing interaction among variables for effective customer involvement in greening SC to develop the structural model in the Indian perspective is an effort towards promoting environment consciousness.

  3. Oleanolic Acid Induces Differentiation of Neural Stem Cells to Neurons: An Involvement of Transcription Factor Nkx-2.5

    Directory of Open Access Journals (Sweden)

    You Ning

    2015-01-01

    Full Text Available Neural stem cells (NSCs harbor the potential to differentiate into neurons, astrocytes, and oligodendrocytes under normal conditions and/or in response to tissue damage. NSCs open a new way of treatment of the injured central nervous system and neurodegenerative disorders. Thus far, few drugs have been developed for controlling NSC functions. Here, the effect as well as mechanism of oleanolic acid (OA, a pentacyclic triterpenoid, on NSC function was investigated. We found OA significantly inhibited neurosphere formation in a dose-dependent manner and achieved a maximum effect at 10 nM. OA also reduced 5-ethynyl-2′-deoxyuridine (EdU incorporation into NSCs, which was indicative of inhibited NSC proliferation. Western blotting analysis revealed the protein levels of neuron-specific marker tubulin-βIII (TuJ1 and Mash1 were increased whilst the astrocyte-specific marker glial fibrillary acidic protein (GFAP decreased. Immunofluorescence analysis showed OA significantly elevated the percentage of TuJ1-positive cells and reduced GFAP-positive cells. Using DNA microarray analysis, 183 genes were differentially regulated by OA. Through transcription factor binding site analyses of the upstream regulatory sequences of these genes, 87 genes were predicted to share a common motif for Nkx-2.5 binding. Finally, small interfering RNA (siRNA methodology was used to silence Nkx-2.5 expression and found silence of Nkx-2.5 alone did not change the expression of TuJ-1 and the percentage of TuJ-1-positive cells. But in combination of OA treatment and silence of Nkx-2.5, most effects of OA on NSCs were abolished. These results indicated that OA is an effective inducer for NSCs differentiation into neurons at least partially by Nkx-2.5-dependent mechanism.

  4. Capturing multidimensionality in stroke aphasia: mapping principal behavioural components to neural structures.

    Science.gov (United States)

    Butler, Rebecca A; Lambon Ralph, Matthew A; Woollams, Anna M

    2014-12-01

    Stroke aphasia is a multidimensional disorder in which patient profiles reflect variation along multiple behavioural continua. We present a novel approach to separating the principal aspects of chronic aphasic performance and isolating their neural bases. Principal components analysis was used to extract core factors underlying performance of 31 participants with chronic stroke aphasia on a large, detailed battery of behavioural assessments. The rotated principle components analysis revealed three key factors, which we labelled as phonology, semantic and executive/cognition on the basis of the common elements in the tests that loaded most strongly on each component. The phonology factor explained the most variance, followed by the semantic factor and then the executive-cognition factor. The use of principle components analysis rendered participants' scores on these three factors orthogonal and therefore ideal for use as simultaneous continuous predictors in a voxel-based correlational methodology analysis of high resolution structural scans. Phonological processing ability was uniquely related to left posterior perisylvian regions including Heschl's gyrus, posterior middle and superior temporal gyri and superior temporal sulcus, as well as the white matter underlying the posterior superior temporal gyrus. The semantic factor was uniquely related to left anterior middle temporal gyrus and the underlying temporal stem. The executive-cognition factor was not correlated selectively with the structural integrity of any particular region, as might be expected in light of the widely-distributed and multi-functional nature of the regions that support executive functions. The identified phonological and semantic areas align well with those highlighted by other methodologies such as functional neuroimaging and neurostimulation. The use of principle components analysis allowed us to characterize the neural bases of participants' behavioural performance more robustly and

  5. Capturing multidimensionality in stroke aphasia: mapping principal behavioural components to neural structures

    Science.gov (United States)

    Butler, Rebecca A.

    2014-01-01

    Stroke aphasia is a multidimensional disorder in which patient profiles reflect variation along multiple behavioural continua. We present a novel approach to separating the principal aspects of chronic aphasic performance and isolating their neural bases. Principal components analysis was used to extract core factors underlying performance of 31 participants with chronic stroke aphasia on a large, detailed battery of behavioural assessments. The rotated principle components analysis revealed three key factors, which we labelled as phonology, semantic and executive/cognition on the basis of the common elements in the tests that loaded most strongly on each component. The phonology factor explained the most variance, followed by the semantic factor and then the executive-cognition factor. The use of principle components analysis rendered participants’ scores on these three factors orthogonal and therefore ideal for use as simultaneous continuous predictors in a voxel-based correlational methodology analysis of high resolution structural scans. Phonological processing ability was uniquely related to left posterior perisylvian regions including Heschl’s gyrus, posterior middle and superior temporal gyri and superior temporal sulcus, as well as the white matter underlying the posterior superior temporal gyrus. The semantic factor was uniquely related to left anterior middle temporal gyrus and the underlying temporal stem. The executive-cognition factor was not correlated selectively with the structural integrity of any particular region, as might be expected in light of the widely-distributed and multi-functional nature of the regions that support executive functions. The identified phonological and semantic areas align well with those highlighted by other methodologies such as functional neuroimaging and neurostimulation. The use of principle components analysis allowed us to characterize the neural bases of participants’ behavioural performance more robustly and

  6. Filtrado digital neuronal difuso: caso MIMO Neural fuzzy digital filtering: multivariate identifier filters involving multiple inputs and multiple outputs (MIMO

    Directory of Open Access Journals (Sweden)

    Medel Juárez José de J.

    2011-05-01

    convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948. This paper considers the MIMO digital filter model using neuro fuzzy digital filtering to find an adaptive  parameter matrix which is integrated into the Kalman filter by the transition matrix. The filter uses the neural network as back-propagation into the fuzzy mechanism to do this, interpreting its variables and its respective levels and selecting the best values for automatically adjusting transition matrix values. The Matlab simulation describes the neural fuzzy digital filter giving an approximation of exponential convergence seen in functional error.

     

  7. A place for time: the spatiotemporal structure of neural dynamics during natural audition

    NARCIS (Netherlands)

    Stephens, G.J.; Honey, C.J.; Hasson, U.

    2013-01-01

    We use functional magnetic resonance imaging (fMRI) to analyze neural responses to natural auditory stimuli. We characterize the fMRI time series through the shape of the voxel power spectrum and find that the timescales of neural dynamics vary along a spatial gradient, with faster dynamics in early

  8. Dynamic Changes in Ezh2 Gene Occupancy Underlie Its Involvement in Neural Stem Cell Self-Renewal and Differentiation towards Oligodendrocytes

    Science.gov (United States)

    Sher, Falak; Boddeke, Erik; Olah, Marta; Copray, Sjef

    2012-01-01

    Background The polycomb group protein Ezh2 is an epigenetic repressor of transcription originally found to prevent untimely differentiation of pluripotent embryonic stem cells. We previously demonstrated that Ezh2 is also expressed in multipotent neural stem cells (NSCs). We showed that Ezh2 expression is downregulated during NSC differentiation into astrocytes or neurons. However, high levels of Ezh2 remained present in differentiating oligodendrocytes until myelinating. This study aimed to elucidate the target genes of Ezh2 in NSCs and in premyelinating oligodendrocytes (pOLs). Methodology/Principal Findings We performed chromatin immunoprecipitation followed by high-throughput sequencing to detect the target genes of Ezh2 in NSCs and pOLs. We found 1532 target genes of Ezh2 in NSCs. During NSC differentiation, the occupancy of these genes by Ezh2 was alleviated. However, when the NSCs differentiated into oligodendrocytes, 393 of these genes remained targets of Ezh2. Analysis of the target genes indicated that the repressive activity of Ezh2 in NSCs concerns genes involved in stem cell maintenance, in cell cycle control and in preventing neural differentiation. Among the genes in pOLs that were still repressed by Ezh2 were most prominently those associated with neuronal and astrocytic committed cell lineages. Suppression of Ezh2 activity in NSCs caused loss of stem cell characteristics, blocked their proliferation and ultimately induced apoptosis. Suppression of Ezh2 activity in pOLs resulted in derangement of the oligodendrocytic phenotype, due to re-expression of neuronal and astrocytic genes, and ultimately in apoptosis. Conclusions/Significance Our data indicate that the epigenetic repressor Ezh2 in NSCs is crucial for proliferative activity and maintenance of neural stemness. During differentiation towards oligodendrocytes, Ezh2 repression continues particularly to suppress other neural fate choices. Ezh2 is completely downregulated during differentiation

  9. Motivational climate, achievement goals, perceived sport competence, and involvement in physical activity: structural and mediator models.

    Science.gov (United States)

    Skjesol, Knut; Halvari, Hallgeir

    2005-04-01

    Students (N=231) were tested on involvement in physical activity, motivational climate, perceived sport competence, and goal orientations. Multiple regression, partial correlation, and LISREL analyses indicated that mastery goal adoption is positively correlated with a mastery climate. Performance-approach goal adoption is positively correlated with a performance climate. Mastery climate, mastery goal, and perceived sport competence are all positively correlated with involvement in physical activity. LISREL analyses supported three mediational hypotheses: (I) the positive correlation between the performance-approach goal and involvement in physical activity is mediated by (high) perceived sport competence, (II) the negative correlation between the performance-avoidance goal and involvement in physical activity is mediated by (low) perceived sport competence, (III) the positive correlation between mastery climate and involvement in physical activity is mediated by (high) mastery goal orientation. An alternative structural model with perceived competence as the last latent construct in the path was also tested.

  10. Ontogeny of avian thermoregulation from a neural point of view

    OpenAIRE

    Baarendse, P.J.J.; Debonne, M.; Decuypere, M.P.; Kemp, B.; Brand, van den, H.

    2007-01-01

    The ontogeny of thermoregulation differs among (avian) species, but in all species both neural and endocrinological processes are involved. In this review the neural processes in ontogeny of thermoregulation during the prenatal and early postnatal phase are discussed. Only in a few avian species (chicken, ducklings) the ontogeny of some important neural structures are described. In the early post hatching phase, peripheral and deep-body thermoreceptors are present and functional, even in altr...

  11. Tinnitus Neural Mechanisms and Structural Changes in the Brain: The Contribution of Neuroimaging Research

    Directory of Open Access Journals (Sweden)

    Simonetti, Patricia

    2015-03-01

    Full Text Available Introduction Tinnitus is an abnormal perception of sound in the absence of an external stimulus. Chronic tinnitus usually has a high impact in many aspects of patients' lives, such as emotional stress, sleep disturbance, concentration difficulties, and so on. These strong reactions are usually attributed to central nervous system involvement. Neuroimaging has revealed the implication of brain structures in the auditory system. Objective This systematic review points out neuroimaging studies that contribute to identifying the structures involved in the pathophysiological mechanism of generation and persistence of various forms of tinnitus. Data Synthesis Functional imaging research reveals that tinnitus perception is associated with the involvement of the nonauditory brain areas, including the front parietal area; the limbic system, which consists of the anterior cingulate cortex, anterior insula, and amygdala; and the hippocampal and parahippocampal area. Conclusion The neuroimaging research confirms the involvement of the mechanisms of memory and cognition in the persistence of perception, anxiety, distress, and suffering associated with tinnitus.

  12. Sum rules across the unpolarized Compton processes involving generalized polarizabilities and moments of nucleon structure functions

    OpenAIRE

    Lensky, Vadim; Hagelstein, Franziska; Pascalutsa, Vladimir; Vanderhaeghen, Marc

    2017-01-01

    We derive two new sum rules for the unpolarized doubly-virtual Compton scattering (VVCS) process on a nucleon, which establish novel low-$Q^2$ relations involving the so-called generalized polarizabilities (GPs) and moments of the nucleon's unpolarized structure functions $F_1$ and $F_2(x,Q^2)$. These relations facilitate the determination of some structure constants which can only be accessed in off-forward VVCS, not experimentally accessible at present. We perform an empirical determination...

  13. Feature Selection Combined with Neural Network Structure Optimization for HIV-1 Protease Cleavage Site Prediction

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2015-01-01

    Full Text Available It is crucial to understand the specificity of HIV-1 protease for designing HIV-1 protease inhibitors. In this paper, a new feature selection method combined with neural network structure optimization is proposed to analyze the specificity of HIV-1 protease and find the important positions in an octapeptide that determined its cleavability. Two kinds of newly proposed features based on Amino Acid Index database plus traditional orthogonal encoding features are used in this paper, taking both physiochemical and sequence information into consideration. Results of feature selection prove that p2, p1, p1′, and p2′ are the most important positions. Two feature fusion methods are used in this paper: combination fusion and decision fusion aiming to get comprehensive feature representation and improve prediction performance. Decision fusion of subsets that getting after feature selection obtains excellent prediction performance, which proves feature selection combined with decision fusion is an effective and useful method for the task of HIV-1 protease cleavage site prediction. The results and analysis in this paper can provide useful instruction and help designing HIV-1 protease inhibitor in the future.

  14. Feature Selection Combined with Neural Network Structure Optimization for HIV-1 Protease Cleavage Site Prediction.

    Science.gov (United States)

    Liu, Hui; Shi, Xiaomiao; Guo, Dongmei; Zhao, Zuowei; Yimin

    2015-01-01

    It is crucial to understand the specificity of HIV-1 protease for designing HIV-1 protease inhibitors. In this paper, a new feature selection method combined with neural network structure optimization is proposed to analyze the specificity of HIV-1 protease and find the important positions in an octapeptide that determined its cleavability. Two kinds of newly proposed features based on Amino Acid Index database plus traditional orthogonal encoding features are used in this paper, taking both physiochemical and sequence information into consideration. Results of feature selection prove that p2, p1, p1', and p2' are the most important positions. Two feature fusion methods are used in this paper: combination fusion and decision fusion aiming to get comprehensive feature representation and improve prediction performance. Decision fusion of subsets that getting after feature selection obtains excellent prediction performance, which proves feature selection combined with decision fusion is an effective and useful method for the task of HIV-1 protease cleavage site prediction. The results and analysis in this paper can provide useful instruction and help designing HIV-1 protease inhibitor in the future.

  15. Artificial neural network prediction of quantitative structure - retention relationships of polycyclic aromatic hydocarbons in gas chromatography

    Directory of Open Access Journals (Sweden)

    SNEZANA SREMAC

    2005-11-01

    Full Text Available A feed-forward artificial neural network (ANN model was used to link molecular structures (boiling points, connectivity indices and molecular weights and retention indices of polycyclic aromatic hydrocarbons (PAHs in linear temperature-programmed gas chromatography. A randomly taken subset of PAH retention data reported by Lee et al. [Anal. Chem. 51 (1979 768], containing retention index data for 30 PAHs, was used to make the ANN model. The prediction ability of the trained ANN was tested on unseen data for 18 PAHs from the same article, as well as on the retention data for 7 PAHs experimentally obtained in this work. In addition, two different data sets with known retention indices taken from the literature were analyzed by the same ANN model. It has been shown that the relative accuracy as the degree of agreement between the measured and the predicted retention indices in all testing sets, for most of the studied PAHs, were within the experimental error margins (±3%.

  16. A phenotypic structure and neural correlates of compulsive behaviors in adolescents.

    Directory of Open Access Journals (Sweden)

    Chantale Montigny

    Full Text Available A compulsivity spectrum has been hypothesized to exist across Obsessive-Compulsive disorder (OCD, Eating Disorders (ED, substance abuse (SA and binge-drinking (BD. The objective was to examine the validity of this compulsivity spectrum, and differentiate it from an externalizing behaviors dimension, but also to look at hypothesized personality and neural correlates.A community-sample of adolescents (N=1938; mean age 14.5 years, and their parents were recruited via high-schools in 8 European study sites. Data on adolescents' psychiatric symptoms, DSM diagnoses (DAWBA and substance use behaviors (AUDIT and ESPAD were collected through adolescent- and parent-reported questionnaires and interviews. The phenotypic structure of compulsive behaviors was then tested using structural equation modeling. The model was validated using personality variables (NEO-FFI and TCI, and Voxel-Based Morphometry (VBM analysis.Compulsivity symptoms best fit a higher-order two factor model, with ED and OCD loading onto a compulsivity factor, and BD and SA loading onto an externalizing factor, composed also of ADHD and conduct disorder symptoms. The compulsivity construct correlated with neuroticism (r=0.638; p ≤ 0.001, conscientiousness (r=0.171; p ≤ 0.001, and brain gray matter volume in left and right orbitofrontal cortex, right ventral striatum and right dorsolateral prefrontal cortex. The externalizing factor correlated with extraversion (r=0.201; p ≤ 0.001, novelty-seeking (r=0.451; p ≤ 0.001, and negatively with gray matter volume in the left inferior and middle frontal gyri.Results suggest that a compulsivity spectrum exists in an adolescent, preclinical sample and accounts for variance in both OCD and ED, but not substance-related behaviors, and can be differentiated from an externalizing spectrum.

  17. Relationships among Adolescents' Leisure Motivation, Leisure Involvement, and Leisure Satisfaction: A Structural Equation Model

    Science.gov (United States)

    Chen, Ying-Chieh; Li, Ren-Hau; Chen, Sheng-Hwang

    2013-01-01

    The purpose of this cross-sectional study was to test a cause-and-effect model of factors affecting leisure satisfaction among Taiwanese adolescents. A structural equation model was proposed in which the relationships among leisure motivation, leisure involvement, and leisure satisfaction were explored. The study collected data from 701 adolescent…

  18. Modular Adaptive System Based on a Multi-Stage Neural Structure for Recognition of 2D Objects of Discontinuous Production

    Directory of Open Access Journals (Sweden)

    I. Topalova

    2005-03-01

    Full Text Available This is a presentation of a new system for invariant recognition of 2D objects with overlapping classes, that can not be effectively recognized with the traditional methods. The translation, scale and partial rotation invariant contour object description is transformed in a DCT spectrum space. The obtained frequency spectrums are decomposed into frequency bands in order to feed different BPG neural nets (NNs. The NNs are structured in three stages - filtering and full rotation invariance; partial recognition; general classification. The designed multi-stage BPG Neural Structure shows very good accuracy and flexibility when tested with 2D objects used in the discontinuous production. The reached speed and the opportunuty for an easy restructuring and reprogramming of the system makes it suitable for application in different applied systems for real time work.

  19. Analysis of the internal representations developed by neural networks for structures applied to quantitative structure--activity relationship studies of benzodiazepines.

    Science.gov (United States)

    Micheli, A; Sperduti, A; Starita, A; Bianucci, A M

    2001-01-01

    An application of recursive cascade correlation (CC) neural networks to quantitative structure-activity relationship (QSAR) studies is presented, with emphasis on the study of the internal representations developed by the neural networks. Recursive CC is a neural network model recently proposed for the processing of structured data. It allows the direct handling of chemical compounds as labeled ordered directed graphs, and constitutes a novel approach to QSAR. The adopted representation of molecular structure captures, in a quite general and flexible way, significant topological aspects and chemical functionalities for each specific class of molecules showing a particular chemical reactivity or biological activity. A class of 1,4-benzodiazepin-2-ones is analyzed by the proposed approach. It compares favorably versus the traditional QSAR treatment based on equations. To show the ability of the model in capturing most of the structural features that account for the biological activity, the internal representations developed by the networks are analyzed by principal component analysis. This analysis shows that the networks are able to discover relevant structural features just on the basis of the association between the molecular morphology and the target property (affinity).

  20. The Effect of an Enrichment Reading Program on the Cognitive Processes and Neural Structures of Children Having Reading Difficulties

    Directory of Open Access Journals (Sweden)

    Hayriye Gül KURUYER

    2017-06-01

    Full Text Available The main purpose of the current study is to explain the effect of an enrichment reading program on the cognitive processes and neural structures of children experiencing reading difficulties. The current study was carried out in line with a single-subject research method and the between-subjects multiple probe design belonging to this method. This research focuses on a group of eight students with reading difficulties. Within the context of the study, memory capacities, attention spans, reading-related activation and white matter pathways of the students were determined before and after the application of the enrichment reading program. This determination process was carried out in two stages. Neuro-imaging was performed in the first stage and in the second stage the students’ cognitive processes and neural structures were investigated in terms of focusing attention and memory capacities by using the following tools: Stroop Test TBAG Form, Auditory Verbal Digit Span Test-Form B, Cancellation Test and Number Order Learning Test. The results obtained show that the enrichment reading program resulted in an improvement in the reading profiles of the students having reading difficulties in terms of their cognitive processes and neural structures.

  1. The Burden of Binge and Heavy Drinking on the Brain: Effects on Adolescent and Young Adult Neural Structure and Function

    Directory of Open Access Journals (Sweden)

    Anita Cservenka

    2017-06-01

    Full Text Available Introduction: Adolescence and young adulthood are periods of continued biological and psychosocial maturation. Thus, there may be deleterious effects of consuming large quantities of alcohol on neural development and associated cognition during this time. The purpose of this mini review is to highlight neuroimaging research that has specifically examined the effects of binge and heavy drinking on adolescent and young adult brain structure and function.Methods: We review cross-sectional and longitudinal studies of young binge and heavy drinkers that have examined brain structure (e.g., gray and white matter volume, cortical thickness, white matter microstructure and investigated brain response using functional magnetic resonance imaging (fMRI.Results: Binge and heavy-drinking adolescents and young adults have systematically thinner and lower volume in prefrontal cortex and cerebellar regions, and attenuated white matter development. They also show elevated brain activity in fronto-parietal regions during working memory, verbal learning, and inhibitory control tasks. In response to alcohol cues, relative to controls or light-drinking individuals, binge and heavy drinkers show increased neural response mainly in mesocorticolimbic regions, including the striatum, anterior cingulate cortex (ACC, hippocampus, and amygdala. Mixed findings are present in risky decision-making tasks, which could be due to large variation in task design and analysis.Conclusions: These findings suggest altered neural structure and activity in binge and heavy-drinking youth may be related to the neurotoxic effects of consuming alcohol in large quantities during a highly plastic neurodevelopmental period, which could result in neural reorganization, and increased risk for developing an alcohol use disorder (AUD.

  2. Compensation or inhibitory failure? Testing hypotheses of age-related right frontal lobe involvement in verbal memory ability using structural and diffusion MRI

    Science.gov (United States)

    Cox, Simon R.; Bastin, Mark E.; Ferguson, Karen J.; Allerhand, Mike; Royle, Natalie A.; Maniega, Susanna Muñoz; Starr, John M.; MacLullich, Alasdair M.J.; Wardlaw, Joanna M.; Deary, Ian J.; MacPherson, Sarah E.

    2015-01-01

    Functional neuroimaging studies report increased right prefrontal cortex (PFC) involvement during verbal memory tasks amongst low-scoring older individuals, compared to younger controls and their higher-scoring contemporaries. Some propose that this reflects inefficient use of neural resources through failure of the left PFC to inhibit non-task-related right PFC activity, via the anterior corpus callosum (CC). For others, it indicates partial compensation – that is, the right PFC cannot completely supplement the failing neural network, but contributes positively to performance. We propose that combining structural and diffusion brain MRI can be used to test predictions from these theories which have arisen from fMRI studies. We test these hypotheses in immediate and delayed verbal memory ability amongst 90 healthy older adults of mean age 73 years. Right hippocampus and left dorsolateral prefrontal cortex (DLPFC) volumes, and fractional anisotropy (FA) in the splenium made unique contributions to verbal memory ability in the whole group. There was no significant effect of anterior callosal white matter integrity on performance. Rather, segmented linear regression indicated that right DLPFC volume was a significantly stronger positive predictor of verbal memory for lower-scorers than higher-scorers, supporting a compensatory explanation for the differential involvement of the right frontal lobe in verbal memory tasks in older age. PMID:25241394

  3. A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure: e1004770

    National Research Council Canada - National Science Library

    Thomas Miconi; Rufin VanRullen

    2016-01-01

      Visual attention has many effects on neural responses, producing complex changes in firing rates, as well as modifying the structure and size of receptive fields, both in topological and feature space...

  4. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

    Science.gov (United States)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  5. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin, E-mail: xmli@cqu.edu.cn [Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044 (China); College of Automation, Chongqing University, Chongqing 400044 (China)

    2015-11-15

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  6. An application of neural network for Structural Health Monitoring of an adaptive wing with an array of FBG sensors

    Energy Technology Data Exchange (ETDEWEB)

    Mieloszyk, Magdalena; Skarbek, Lukasz; Ostachowicz, Wieslaw [IFFM PASci, Fiszera14, 80-952 Gdansk (Poland); Krawczuk, Marek, E-mail: mmieloszyk@imp.gda.pl [IFFM PASci, Fiszera 14, 80-952 Gdansk and Technical University of Gdansk, Wlasna Strzecha 18a Street, 80-233, Gdansk (Poland)

    2011-07-19

    This paper presents an application of neural networks to determinate the level of activation of shape memory alloy actuators of an adaptive wing. In this concept the shape of the wing can be controlled and altered thanks to the wing design and the use of integrated shape memory alloy actuators. The wing is assumed as assembled from a number of wing sections that relative positions can be controlled independently by thermal activation of shape memory actuators. The investigated wing is employed with an array of Fibre Bragg Grating sensors. The Fibre Bragg Grating sensors with combination of a neural network have been used to Structural Health Monitoring of the wing condition. The FBG sensors are a great tool to control the condition of composite structures due to their immunity to electromagnetic fields as well as their small size and weight. They can be mounted onto the surface or embedded into the wing composite material without any significant influence on the wing strength. The paper concentrates on analysis of the determination of the twisting moment produced by an activated shape memory alloy actuator. This has been analysed both numerically using the finite element method by a commercial code ABAQUS (registered) and experimentally using Fibre Bragg Grating sensor measurements. The results of the analysis have been then used by a neural network to determine twisting moments produced by each shape memory alloy actuator.

  7. Neural-network-based depth-resolved multiscale structural optimization using density functional theory and electron diffraction data

    Science.gov (United States)

    Pennington, Robert S.; Coll, Catalina; Estradé, Sònia; Peiró, Francesca; Koch, Christoph T.

    2018-01-01

    Iterative neural-network-based three-dimensional structural optimization of atomic positions over tens of nanometers is performed using transmission electron microscope (TEM) diffraction data simulated from density functional theory (DFT) all-electron densities, thus retrieving parameter variations along the beam direction. We first use experimental data to show that the GPAW DFT code's all-electron densities are considerably more accurate for electron diffraction calculations compared to conventional isolated-atom scattering factors, and they also compare well to Wien2K DFT simulations. This DFT-TEM combination is then integrated into an iterative neural-network-optimization-based algorithm (PRIMES, parameter retrieval and inversion from multiple electron scattering) to retrieve nanometer-scale ferroelectric polarization domains and strain in theoretical bulklike specimens from TEM data. DFT and isolated-atom methods produce substantially different diffraction patterns and retrieved polarization domain parameters, and DFT is sufficient to retrieve strain properties from a silicon specimen simulated using experimentally derived structure factors. Thus, we show that the improved accuracy, fast computation, and intuitive integration make the GPAW DFT code well suited for three-dimensional materials characterization and demonstrate this using an iterative neural-network algorithm that is verifiable on the mesoscale and, with DFT integration, self-consistent on the nanoscale.

  8. A structural model of customer satisfaction and trust in vendors involved in mobile commerce

    OpenAIRE

    Suki, N.M.

    2011-01-01

    The purpose of this paper is to provide an explanation of factors influencing customer satisfaction and trust in vendors involved in mobile commerce (m-commerce). The study sample consists of 200 respondents. Data were analyzed by employing structural equation modelling (SEM) supported by AMOS 5.0 with maximum likelihood estimation in order to test the proposed hypotheses. The proposed model was empirically tested and results confirmed that users’ satisfaction with vendors in m-commerce was n...

  9. The Anthropic Principle and numerical coincidences involving the cosmological, gravitational and fine structure constants

    CERN Document Server

    Eaves, Laurence

    2014-01-01

    Christian Beck has proposed a set of Shannon-Khinchin axioms to derive a formula for the cosmological constant, {\\Lambda}. We discuss this result in relation to numerical coincidences involving the measured values of {\\Lambda} and the gravitational and fine structure constants, G and {\\alpha}. The empirical formulae that inter-relate the three constants suggest that the measured values of G and {\\Lambda} are consistent with the apparent anthropic fine-tuning of {\\alpha}.

  10. Episodic memory impairment in systemic lupus erythematosus: involvement of thalamic structures.

    Science.gov (United States)

    Zimmermann, Nicolle; Corrêa, Diogo Goulart; Netto, Tania Maria; Kubo, Tadeu; Pereira, Denis Batista; Fonseca, Rochele Paz; Gasparetto, Emerson Leandro

    2015-02-01

    Episodic memory deficits in systemic lupus erythematosus (SLE) have been frequently reported in the literature; however, little is known about the neural correlates of these deficits. We investigated differences in the volumes of different brain structures of SLE patients with and without episodic memory impairments diagnosed by the Rey Auditory Verbal Learning Test (RAVLT). Groups were paired based on age, education, sex, Mini Mental State Examination score, accumulation of disease burden (SLICC), and focused attention dimension score. Patients underwent magnetic resonance imaging (MRI). Cortical volumetric reconstruction and segmentation of the MR images were performed with the FreeSurfer software program. SLE patients with episodic memory deficits presented shorter time of diagnosis than SLE patients without episodic memory deficits. ANOVA revealed that SLE patients with episodic memory deficits had a larger third ventricle volume than SLE patients without episodic memory deficits and controls. Additionally, covariance analysis indicated group effects on the bilateral thalamus and on the third ventricle. Our findings indicate that episodic memory may be impaired in SLE patients with normal hippocampal volume. In addition, the thalamus may undergo volumetric changes associated with episodic memory loss in SLE.

  11. Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures

    DEFF Research Database (Denmark)

    Christiansen, Niels H.; Voie, Per Erlend Torbergsen; Winther, Ole

    2014-01-01

    platform is designed and tested. The purpose of setting up the network is to reduce calculation time in a fatigue life analysis. Therefore, the networks trained on different error functions are compared with respect to accuracy of rain flow counts of stress cycles over a number of time series simulations......Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure. This error measure is given by an error function. Several different error functions are suggested in the literature. However, the far most common measure...... for regression is the mean square error. This paper looks into the possibility of improving the performance of neural networks by selecting or defining error functions that are tailor-made for a specific objective. A neural network trained to simulate tension forces in an anchor chain on a floating offshore...

  12. The artist emerges: visual art learning alters neural structure and function.

    Science.gov (United States)

    Schlegel, Alexander; Alexander, Prescott; Fogelson, Sergey V; Li, Xueting; Lu, Zhengang; Kohler, Peter J; Riley, Enrico; Tse, Peter U; Meng, Ming

    2015-01-15

    How does the brain mediate visual artistic creativity? Here we studied behavioral and neural changes in drawing and painting students compared to students who did not study art. We investigated three aspects of cognition vital to many visual artists: creative cognition, perception, and perception-to-action. We found that the art students became more creative via the reorganization of prefrontal white matter but did not find any significant changes in perceptual ability or related neural activity in the art students relative to the control group. Moreover, the art students improved in their ability to sketch human figures from observation, and multivariate patterns of cortical and cerebellar activity evoked by this drawing task became increasingly separable between art and non-art students. Our findings suggest that the emergence of visual artistic skills is supported by plasticity in neural pathways that enable creative cognition and mediate perceptuomotor integration. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Sequence and structural features of carbohydrate binding in proteins and assessment of predictability using a neural network

    Directory of Open Access Journals (Sweden)

    Ahmad Shandar

    2007-01-01

    Full Text Available Abstract Background Protein-Carbohydrate interactions are crucial in many biological processes with implications to drug targeting and gene expression. Nature of protein-carbohydrate interactions may be studied at individual residue level by analyzing local sequence and structure environments in binding regions in comparison to non-binding regions, which provide an inherent control for such analyses. With an ultimate aim of predicting binding sites from sequence and structure, overall statistics of binding regions needs to be compiled. Sequence-based predictions of binding sites have been successfully applied to DNA-binding proteins in our earlier works. We aim to apply similar analysis to carbohydrate binding proteins. However, due to a relatively much smaller region of proteins taking part in such interactions, the methodology and results are significantly different. A comparison of protein-carbohydrate complexes has also been made with other protein-ligand complexes. Results We have compiled statistics of amino acid compositions in binding versus non-binding regions- general as well as in each different secondary structure conformation. Binding propensities of each of the 20 residue types and their structure features such as solvent accessibility, packing density and secondary structure have been calculated to assess their predisposition to carbohydrate interactions. Finally, evolutionary profiles of amino acid sequences have been used to predict binding sites using a neural network. Another set of neural networks was trained using information from single sequences and the prediction performance from the evolutionary profiles and single sequences were compared. Best of the neural network based prediction could achieve an 87% sensitivity of prediction at 23% specificity for all carbohydrate-binding sites, using evolutionary information. Single sequences gave 68% sensitivity and 55% specificity for the same data set. Sensitivity and specificity

  14. Neural correlates of emotional personality: a structural and functional magnetic resonance imaging study.

    Directory of Open Access Journals (Sweden)

    Stefan Koelsch

    Full Text Available Studies addressing brain correlates of emotional personality have remained sparse, despite the involvement of emotional personality in health and well-being. This study investigates structural and functional brain correlates of psychological and physiological measures related to emotional personality. Psychological measures included neuroticism, extraversion, and agreeableness scores, as assessed using a standard personality questionnaire. As a physiological measure we used a cardiac amplitude signature, the so-called E κ value (computed from the electrocardiogram which has previously been related to tender emotionality. Questionnaire scores and E κ values were related to both functional (eigenvector centrality mapping, ECM and structural (voxel-based morphometry, VBM neuroimaging data. Functional magnetic resonance imaging (fMRI data were obtained from 22 individuals (12 females while listening to music (joy, fear, or neutral music. ECM results showed that agreeableness scores correlated with centrality values in the dorsolateral prefrontal cortex, the anterior cingulate cortex, and the ventral striatum (nucleus accumbens. Individuals with higher E κ values (indexing higher tender emotionality showed higher centrality values in the subiculum of the right hippocampal formation. Structural MRI data from an independent sample of 59 individuals (34 females showed that neuroticism scores correlated with volume of the left amygdaloid complex. In addition, individuals with higher E κ showed larger gray matter volume in the same portion of the subiculum in which individuals with higher E κ showed higher centrality values. Our results highlight a role of the amygdala in neuroticism. Moreover, they indicate that a cardiac signature related to emotionality (E κ correlates with both function (increased network centrality and structure (grey matter volume of the subiculum of the hippocampal formation, suggesting a role of the hippocampal formation for

  15. Neural Correlates of Emotional Personality: A Structural and Functional Magnetic Resonance Imaging Study

    Science.gov (United States)

    Koelsch, Stefan; Skouras, Stavros; Jentschke, Sebastian

    2013-01-01

    Studies addressing brain correlates of emotional personality have remained sparse, despite the involvement of emotional personality in health and well-being. This study investigates structural and functional brain correlates of psychological and physiological measures related to emotional personality. Psychological measures included neuroticism, extraversion, and agreeableness scores, as assessed using a standard personality questionnaire. As a physiological measure we used a cardiac amplitude signature, the so-called Eκ value (computed from the electrocardiogram) which has previously been related to tender emotionality. Questionnaire scores and Eκ values were related to both functional (eigenvector centrality mapping, ECM) and structural (voxel-based morphometry, VBM) neuroimaging data. Functional magnetic resonance imaging (fMRI) data were obtained from 22 individuals (12 females) while listening to music (joy, fear, or neutral music). ECM results showed that agreeableness scores correlated with centrality values in the dorsolateral prefrontal cortex, the anterior cingulate cortex, and the ventral striatum (nucleus accumbens). Individuals with higher Eκ values (indexing higher tender emotionality) showed higher centrality values in the subiculum of the right hippocampal formation. Structural MRI data from an independent sample of 59 individuals (34 females) showed that neuroticism scores correlated with volume of the left amygdaloid complex. In addition, individuals with higher Eκ showed larger gray matter volume in the same portion of the subiculum in which individuals with higher Eκ showed higher centrality values. Our results highlight a role of the amygdala in neuroticism. Moreover, they indicate that a cardiac signature related to emotionality (Eκ) correlates with both function (increased network centrality) and structure (grey matter volume) of the subiculum of the hippocampal formation, suggesting a role of the hippocampal formation for emotional

  16. Neural correlates of emotional personality: a structural and functional magnetic resonance imaging study.

    Science.gov (United States)

    Koelsch, Stefan; Skouras, Stavros; Jentschke, Sebastian

    2013-01-01

    Studies addressing brain correlates of emotional personality have remained sparse, despite the involvement of emotional personality in health and well-being. This study investigates structural and functional brain correlates of psychological and physiological measures related to emotional personality. Psychological measures included neuroticism, extraversion, and agreeableness scores, as assessed using a standard personality questionnaire. As a physiological measure we used a cardiac amplitude signature, the so-called E κ value (computed from the electrocardiogram) which has previously been related to tender emotionality. Questionnaire scores and E κ values were related to both functional (eigenvector centrality mapping, ECM) and structural (voxel-based morphometry, VBM) neuroimaging data. Functional magnetic resonance imaging (fMRI) data were obtained from 22 individuals (12 females) while listening to music (joy, fear, or neutral music). ECM results showed that agreeableness scores correlated with centrality values in the dorsolateral prefrontal cortex, the anterior cingulate cortex, and the ventral striatum (nucleus accumbens). Individuals with higher E κ values (indexing higher tender emotionality) showed higher centrality values in the subiculum of the right hippocampal formation. Structural MRI data from an independent sample of 59 individuals (34 females) showed that neuroticism scores correlated with volume of the left amygdaloid complex. In addition, individuals with higher E κ showed larger gray matter volume in the same portion of the subiculum in which individuals with higher E κ showed higher centrality values. Our results highlight a role of the amygdala in neuroticism. Moreover, they indicate that a cardiac signature related to emotionality (E κ) correlates with both function (increased network centrality) and structure (grey matter volume) of the subiculum of the hippocampal formation, suggesting a role of the hippocampal formation for

  17. Filovirus proteins for antiviral drug discovery: Structure/function of proteins involved in assembly and budding.

    Science.gov (United States)

    Martin, Baptiste; Reynard, Olivier; Volchkov, Viktor; Decroly, Etienne

    2018-02-01

    There are no approved medications for the treatment of Marburg or Ebola virus infection. In two previous articles (Martin et al., 2016, Martin et al., 2017), we reviewed surface glycoprotein and replication proteins structure/function relationship to decipher the molecular mechanisms of filovirus life cycle and identify antiviral strategies. In the present article, we recapitulate knowledge about the viral proteins involved in filovirus assembly and budding. First we describe the structural data available for viral proteins associated with virus assembly and virion egress and then, we integrate the structural features of these proteins in the functional context of the viral replication cycle. Finally, we summarize recent advances in the development of innovative antiviral strategies to target filovirus assembly and egress. The development of such prophylactic or post-exposure treatments could help controlling future filovirus outbreaks. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. The gender gap in student engagement: The role of teachers' autonomy support, structure, and involvement.

    Science.gov (United States)

    Lietaert, Sofie; Roorda, Debora; Laevers, Ferre; Verschueren, Karine; De Fraine, Bieke

    2015-12-01

    The gender gap in education in favour of girls is a widely known phenomenon. Boys generally have higher dropout rates, obtain lower grades, and show lower engagement. Insight into factors related to these academic outcomes could help to address the gender gap. This study investigated, for Dutch language classes, (1) how boys and girls differ in behavioural engagement, (2) which teacher support dimensions (autonomy support, structure, involvement) may explain gender differences in engagement (mediation hypothesis), and (3) whether and which of these teacher support dimensions matter more for boys' as opposed to girls' engagement (moderation or differential effects hypothesis). A total of 385 Grade 7 students and their 15 language teachers participated in this study. Teacher support was assessed through student reports. Student engagement was measured using student, teacher, and observer reports. By means of structural equation modelling, the mediating role of the teacher support dimensions for gender differences in behavioural engagement was tested. The potential differential role of the teacher support dimensions for boys' and girls' engagement was investigated through multigroup analysis. Boys were less engaged than girls and reported lower support from their teacher. Autonomy support and involvement partially mediated the relationship between gender and behavioural engagement. Autonomy support was demonstrated to be a protective factor for boys' engagement but not for girls'. Structure and involvement contributed equally to engagement for both sexes. Although involvement and autonomy support partly explained the gender gap in engagement (mediation hypothesis), more support was found for differential effects of autonomy support on boys' versus girls' engagement (differential effects hypothesis). © 2015 The British Psychological Society.

  19. Power prediction in mobile communication systems using an optimal neural-network structure.

    Science.gov (United States)

    Gao, X M; Gao, X Z; Tanskanen, J A; Ovaska, S J

    1997-01-01

    Presents a novel neural-network-based predictor for received power level prediction in direct sequence code division multiple access (DS/CDMA) systems. The predictor consists of an adaptive linear element (Adaline) followed by a multilayer perceptron (MLP). An important but difficult problem in designing such a cascade predictor is to determine the complexity of the networks. We solve this problem by using the predictive minimum description length (PMDL) principle to select the optimal numbers of input and hidden nodes. This approach results in a predictor with both good noise attenuation and excellent generalization capability. The optimized neural networks are used for predictive filtering of very noisy Rayleigh fading signals with 1.8 GHz carrier frequency. Our results show that the optimal neural predictor can provide smoothed in-phase and quadrature signals with signal-to-noise ratio (SNR) gains of about 12 and 7 dB at the urban mobile speeds of 5 and 50 km/h, respectively. The corresponding power signal SNR gains are about 11 and 5 dB. Therefore, the neural predictor is well suitable for power control applications where ldquodelaylessrdquo noise attenuation and efficient reduction of fast fading are required.

  20. Travelling waves in models of neural tissue: from localised structures to periodic waves

    NARCIS (Netherlands)

    Meijer, Hil Gaétan Ellart; Coombes, Stephen

    2014-01-01

    We consider travelling waves (fronts, pulses and periodics) in spatially extended one dimensional neural field models. We demonstrate for an excitatory field with linear adaptation that, in addition to an expected stable pulse solution, a stable anti-pulse can exist. Varying the adaptation strength

  1. dp53 Restrains ectopic neural stem cell formation in the Drosophila brain in a non-apoptotic mechanism involving Archipelago and cyclin E.

    Directory of Open Access Journals (Sweden)

    Yingshi Ouyang

    Full Text Available Accumulating evidence suggests that tumor-initiating stem cells or cancer stem cells (CSCs possibly originating from normal stem cells may be the root cause of certain malignancies. How stem cell homeostasis is impaired in tumor tissues is not well understood, although certain tumor suppressors have been implicated. In this study, we use the Drosophila neural stem cells (NSCs called neuroblasts as a model to study this process. Loss-of-function of Numb, a key cell fate determinant with well-conserved mammalian counterparts, leads to the formation of ectopic neuroblasts and a tumor phenotype in the larval brain. Overexpression of the Drosophila tumor suppressor p53 (dp53 was able to suppress ectopic neuroblast formation caused by numb loss-of-function. This occurred in a non-apoptotic manner and was independent of Dacapo, the fly counterpart of the well-characterized mammalian p53 target p21 involved in cellular senescence. The observation that dp53 affected Edu incorporation into neuroblasts led us to test the hypothesis that dp53 acts through regulation of factors involved in cell cycle progression. Our results show that the inhibitory effect of dp53 on ectopic neuroblast formation was mediated largely through its regulation of Cyclin E (Cyc E. Overexpression of Cyc E was able to abrogate dp53's ability to rescue numb loss-of-function phenotypes. Increasing Cyc E levels by attenuating Archipelago (Ago, a recently identified transcriptional target of dp53 and a negative regulator of Cyc E, had similar effects. Conversely, reducing Cyc E activity by overexpressing Ago blocked ectopic neuroblast formation in numb mutant. Our results reveal an intimate connection between cell cycle progression and NSC self-renewal vs. differentiation control, and indicate that p53-mediated regulation of ectopic NSC self-renewal through the Ago/Cyc E axis becomes particularly important when NSC homeostasis is perturbed as in numb loss-of-function condition. This has

  2. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  3. Neural signature of developmental coordination disorder in the structural connectome independent of comorbid autism.

    Science.gov (United States)

    Caeyenberghs, Karen; Taymans, Tom; Wilson, Peter H; Vanderstraeten, Guy; Hosseini, Hadi; van Waelvelde, Hilde

    2016-07-01

    Children with autism spectrum disorders (ASD) often exhibit motor clumsiness (Developmental Coordination Disorder, DCD), i.e. they struggle with everyday tasks that require motor coordination like dressing, self-care, and participating in sport and leisure activities. Previous studies in these neurodevelopmental disorders have demonstrated functional abnormalities and alterations of white matter microstructural integrity in specific brain regions. These findings suggest that the global organization of brain networks is affected in DCD and ASD and support the hypothesis of a 'dys-connectivity syndrome' from a network perspective. No studies have compared the structural covariance networks between ASD and DCD in order to look for the signature of DCD independent of comorbid autism. Here, we aimed to address the question of whether abnormal connectivity in DCD overlaps that seen in autism or comorbid DCD-autism. Using graph theoretical analysis, we investigated differences in global and regional topological properties of structural brain networks in 53 children: 8 ASD children with DCD (DCD+ASD), 15 ASD children without DCD (ASD), 11 with DCD only, and 19 typically developing (TD) children. We constructed separate structural correlation networks based on cortical thickness derived from Freesurfer. The children were assessed on the Movement-ABC and the Beery Test of Visual Motor Integration. Behavioral results demonstrated that the DCD group and DCD+ASD group scored on average poorer than the TD and ASD groups on various motor measures. Furthermore, although the brain networks of all groups exhibited small-world properties, the topological architecture of the networks was significantly altered in children with ASD compared with DCD and TD. ASD children showed increased normalized path length and higher values of clustering coefficient. Also, paralimbic regions exhibited nodal clustering coefficient alterations in singular disorders. These changes were disorder

  4. Genetic neural networks for quantitative structure-activity relationships: improvements and application of benzodiazepine affinity for benzodiazepine/GABAA receptors.

    Science.gov (United States)

    So, S S; Karplus, M

    1996-12-20

    A novel tool, called a genetic neural network (GNN), has been developed for obtaining quantitative structure-activity relationships (QSAR) for high-dimensional data sets (J. Med. Chem. 1996, 39, 1521-1530). The GNN method uses a neural network to correlate activity with descriptors that are preselected by a genetic algorithm. To provide an extended test of the GNN method, the data on 57 benzodiazepines given by Maddalena and Johnston (MJ; J. Med. Chem. 1995, 38, 715-724) have been examined with an enhanced version of GNN, and the results are compared with the excellent QSAR of MJ. The problematic steepest descent training has been replaced by the scaled conjugate gradient algorithm. This leads to a substantial gain in performance in both robustness of prediction and speed of computation. The cross-validation GNN simulation and the subsequent run based on an unbiased and more efficient protocol led to the discovery of other 10-descriptor QSARs that are superior to the best model of MJ based on backward elimination selection and neural network training. Results from a series of GNNs with a different number of inputs showed that a neural network with fewer inputs can produce QSARs as good as or even better than those with higher dimensions. The top-ranking models from a GNN simulation using only six input descriptors are presented, and the chemical significance of the chosen descriptors is discussed. The statistical significance of these GNN QSARs is validated. The best QSARs are used to provide a graphical tool that aids the design of new drug analogues. By replacing functional groups at the 7- and 2'-positions with ones that have optimal substituent parameters, a number of new benzodiazepines with high potency are predicted.

  5. Regulation of genes involved in cell wall synthesis and structure during Ustilago maydis dimorphism.

    Science.gov (United States)

    Robledo-Briones, Mariana; Ruiz-Herrera, José

    2013-02-01

    The cell wall is the structure that provides the shape to fungal cells and protects them from the difference in osmotic pressure existing between the cytosol and the external medium. Accordingly, changes in structure and composition of the fungal wall must occur during cell differentiation, including the dimorphic transition of fungi. We analyzed, by use of microarrays, the transcriptional regulation of the 639 genes identified to be involved in cell wall synthesis and structure plus the secretome of the Basidiomycota species Ustilago maydis during its dimorphic transition induced by a change in pH. Of these, 189 were differentially expressed during the process, and using as control two monomorphic mutants, one yeast like and the other mycelium constitutive, 66 genes specific of dimorphism were identified. Most of these genes were up-regulated in the mycelial phase. These included CHS genes, genes involved in β-1,6-glucan synthesis, N-glycosylation, and proteins containing a residue of glycosylphosphatidylinositol, and a number of genes from the secretome. The possible significance of these data on cell wall plasticity is discussed. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

  6. In-silico bonding schemes to encode chemical bonds involving sharing of electrons in molecular structures.

    Science.gov (United States)

    Punnaivanam, Sankar; Sathiadhas, Jerome Pastal Raj; Panneerselvam, Vinoth

    2016-05-01

    Encoding of covalent and coordinate covalent bonds in molecular structures using ground state valence electronic configuration is achieved. The bonding due to electron sharing in the molecular structures is described with five fundamental bonding categories viz. uPair-uPair, lPair-uPair, uPair-lPair, vPair-lPair, and lPair-lPair. The involvement of lone pair electrons and the vacant electron orbitals in chemical bonding are explained with bonding schemes namely "target vacant promotion", "source vacant promotion", "target pairing promotion", "source pairing promotion", "source cation promotion", "source pairing double bond", "target vacant occupation", and "double pairing promotion" schemes. The bonding schemes are verified with a chemical structure editor. The bonding in the structures like ylides, PCl5, SF6, IF7, N-Oxides, BF4(-), AlCl4(-) etc. are explained and encoded unambiguously. The encoding of bonding in the structures of various organic compounds, transition metals compounds, coordination complexes and metal carbonyls is accomplished. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Structure of glycerol-3-phosphate dehydrogenase, an essential monotopic membrane enzyme involved in respiration and metabolism

    Energy Technology Data Exchange (ETDEWEB)

    Yeh, Joanne I.; Chinte, Unmesh; Du, Shoucheng (Pitt)

    2008-04-02

    Sn-glycerol-3-phosphate dehydrogenase (GlpD) is an essential membrane enzyme, functioning at the central junction of respiration, glycolysis, and phospholipid biosynthesis. Its critical role is indicated by the multitiered regulatory mechanisms that stringently controls its expression and function. Once expressed, GlpD activity is regulated through lipid-enzyme interactions in Escherichia coli. Here, we report seven previously undescribed structures of the fully active E. coli GlpD, up to 1.75 {angstrom} resolution. In addition to elucidating the structure of the native enzyme, we have determined the structures of GlpD complexed with substrate analogues phosphoenolpyruvate, glyceric acid 2-phosphate, glyceraldehyde-3-phosphate, and product, dihydroxyacetone phosphate. These structural results reveal conformational states of the enzyme, delineating the residues involved in substrate binding and catalysis at the glycerol-3-phosphate site. Two probable mechanisms for catalyzing the dehydrogenation of glycerol-3-phosphate are envisioned, based on the conformational states of the complexes. To further correlate catalytic dehydrogenation to respiration, we have additionally determined the structures of GlpD bound with ubiquinone analogues menadione and 2-n-heptyl-4-hydroxyquinoline N-oxide, identifying a hydrophobic plateau that is likely the ubiquinone-binding site. These structures illuminate probable mechanisms of catalysis and suggest how GlpD shuttles electrons into the respiratory pathway. Glycerol metabolism has been implicated in insulin signaling and perturbations in glycerol uptake and catabolism are linked to obesity in humans. Homologs of GlpD are found in practically all organisms, from prokaryotes to humans, with >45% consensus protein sequences, signifying that these structural results on the prokaryotic enzyme may be readily applied to the eukaryotic GlpD enzymes.

  8. Optics-Only Calibration of a Neural-Net Based Optical NDE Method for Structural Health Monitoring

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    A calibration process is presented that uses optical measurements alone to calibrate a neural-net based NDE method. The method itself detects small changes in the vibration mode shapes of structures. The optics-only calibration process confirms previous work that the sensitivity to vibration-amplitude changes can be as small as 10 nanometers. A more practical value in an NDE service laboratory is shown to be 50 nanometers. Both model-generated and experimental calibrations are demonstrated using two implementations of the calibration technique. The implementations are based on previously published demonstrations of the NDE method and an alternative calibration procedure that depends on comparing neural-net and point sensor measurements. The optics-only calibration method, unlike the alternative method, does not require modifications of the structure being tested or the creation of calibration objects. The calibration process can be used to test improvements in the NDE process and to develop a vibration-mode-independence of damagedetection sensitivity. The calibration effort was intended to support NASA s objective to promote safety in the operations of ground test facilities or aviation safety, in general, by allowing the detection of the gradual onset of structural changes and damage.

  9. Involvement of bacterial migration in the development of complex multicellular structures in Pseudomonas aeruginosa biofilms

    DEFF Research Database (Denmark)

    Klausen, Mikkel; Aaes-Jorgensen, A.; Molin, Søren

    2003-01-01

    development, we have performed an investigation with time-lapse confocal laser scanning microscopy of biofilms formed by various combinations of colour-coded P. aeruginosa wild type and motility mutants. We show that mushroom-shaped multicellular structures in P. aeruginosa biofilms can form in a sequential...... process involving a non-motile bacterial subpopulation and a migrating bacterial subpopulation. The non-motile bacteria form the mushroom stalks by growth in certain foci of the biofilm. The migrating bacteria form the mushroom caps by climbing the stalks and aggregating on the tops in a process which...

  10. Measurement of weld penetration depths in thin structures using transmission coefficients of laser-generated Lamb waves and neural network.

    Science.gov (United States)

    Yang, Lei; Ume, I Charles

    2017-07-01

    The Laser/EMAT ultrasonic (LEU) technique has shown the capability to measure weld penetration depths in thick structures based on ray-tracing of laser-generated bulk and surface waves. The ray-tracing method is not applicable to laser-generated Lamb waves when the LEU technique is used to measure weld penetration depths in thin structures. In this work, transmission coefficients of Lamb waves present in the LEU signals are investigated against varying weld penetration depths. An artificial neural network is developed to use transmission coefficients of sensitive Lamb waves and LEU signal energy to predict weld penetration depths accurately. The developed method is very attractive because it allows a quick inspection of weld penetration depths in thin structures. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Structural domains in NADPH: Protochlorophyllide oxidoreductases involved in catalysis and substrate binding. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Timko, Michael P.

    1999-09-24

    Until recently little direct information was available about specific structural determinants within the light-dependent NADPH: protochlorophyllide oxidoreductases (PORs) required for substrate and cofactor binding, catalytic activity, and thylakoid membrane localization. Based on our previous DOE-funded studies, during the past year we brought to fruition a number of ongoing experiments, initiated several new avenues of investigations, and overall have made considerable progress towards establishing the basic structural parameters governing POR function. Our studies to date have defined residues and domains involved in substrate and cofactor binding and catalysis, and elaborated on the mechanism for membrane localization of POR in developing plastids. Our results and their significance, as well as our work in progress, are detailed.

  12. Large-Scale Deletions and SMADIP1 Truncating Mutations in Syndromic Hirschsprung Disease with Involvement of Midline Structures

    Science.gov (United States)

    Amiel, Jeanne; Espinosa-Parrilla, Yolanda; Steffann, Julie; Gosset, Philippe; Pelet, Anna; Prieur, Marguerite; Boute, Odile; Choiset, Agnès; Lacombe, Didier; Philip, Nicole; Le Merrer, Martine; Tanaka, Hajime; Till, Marianne; Touraine, Renaud; Toutain, Annick; Vekemans, Michel; Munnich, Arnold; Lyonnet, Stanislas

    2001-01-01

    Hirschsprung disease (HSCR) is a common malformation of neural-crest–derived enteric neurons that is frequently associated with other congenital abnormalities. The SMADIP1 gene recently has been recognized as disease causing in some patients with 2q22 chromosomal rearrangement, resulting in syndromic HSCR with mental retardation, with microcephaly, and with facial dysmorphism. We screened 19 patients with HSCR and mental retardation and eventually identified large-scale SMADIP1 deletions or truncating mutations in 8 of 19 patients. These results allow further delineation of the spectrum of malformations ascribed to SMADIP1 haploinsufficiency, which includes frequent features such as hypospadias and agenesis of the corpus callosum. Thus, SMADIP1, which encodes a transcriptional corepressor of Smad target genes, may play a role not only in the patterning of neural-crest–derived cells and of CNS but also in the development of midline structures in humans. PMID:11595972

  13. Modeling Distillation Column Using ARX Model Structure and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Reza Pirmoradi

    2012-04-01

    Full Text Available Distillation is a complex and highly nonlinear industrial process. In general it is not always possible to obtain accurate first principles models for high-purity distillation columns. On the other hand the development of first principles models is usually time consuming and expensive. To overcome these problems, empirical models such as neural networks can be used. One major drawback of empirical models is that the prediction is valid only inside the data domain that is sufficiently covered by measurement data. Modeling distillation columns by means of neural networks is reported in literature by using recursive networks. The recursive networks are proper for modeling purpose, but such models have the problems of high complexity and high computational cost. The objective of this paper is to propose a simple and reliable model for distillation column. The proposed model uses feed forward neural networks which results in a simple model with less parameters and faster training time. Simulation results demonstrate that predictions of the proposed model in all regions are close to outputs of the dynamic model and the error in negligible. This implies that the model is reliable in all regions.

  14. Structural analysis of SgvP involved in carbon-sulfur bond formation during griseoviridin biosynthesis.

    Science.gov (United States)

    Li, Qin; Chen, Yan; Zhang, Guiqin; Zhang, Huaidong

    2017-05-01

    Griseoviridin (GV) is a broad-spectrum antibiotic with antibacterial and antifungal activity. In the GV biosynthetic pathway, SgvP catalyzes formation of the carbon-sulfur bond in GV. Herein, we report the recombinant expression and characterization of SgvP from Streptomyces griseoviridis NRRL2427. We also present the 2.6 Å crystal structure of SgvP, which is the first structure of a cytochrome P450 involved in carbon-sulfur bond formation in GV. Structural analysis indicates that Pro237 in the I-helix of SgvP may play a critical role in dioxygen binding and proton transfer during the catalytic cycle. Of the three channels we observed in SgvP, channel 3 may be essential for substrate ingress and egress from the active site, while channels 1 and 2 may be the solvent and water pathway, respectively. Coordinate and structure factor were deposited in the Protein Data Bank database under the accession number 4MM0. © 2017 Federation of European Biochemical Societies.

  15. Quantitative Live Imaging of Human Embryonic Stem Cell Derived Neural Rosettes Reveals Structure-Function Dynamics Coupled to Cortical Development.

    Science.gov (United States)

    Ziv, Omer; Zaritsky, Assaf; Yaffe, Yakey; Mutukula, Naresh; Edri, Reuven; Elkabetz, Yechiel

    2015-10-01

    Neural stem cells (NSCs) are progenitor cells for brain development, where cellular spatial composition (cytoarchitecture) and dynamics are hypothesized to be linked to critical NSC capabilities. However, understanding cytoarchitectural dynamics of this process has been limited by the difficulty to quantitatively image brain development in vivo. Here, we study NSC dynamics within Neural Rosettes--highly organized multicellular structures derived from human pluripotent stem cells. Neural rosettes contain NSCs with strong epithelial polarity and are expected to perform apical-basal interkinetic nuclear migration (INM)--a hallmark of cortical radial glial cell development. We developed a quantitative live imaging framework to characterize INM dynamics within rosettes. We first show that the tendency of cells to follow the INM orientation--a phenomenon we referred to as radial organization, is associated with rosette size, presumably via mechanical constraints of the confining structure. Second, early forming rosettes, which are abundant with founder NSCs and correspond to the early proliferative developing cortex, show fast motions and enhanced radial organization. In contrast, later derived rosettes, which are characterized by reduced NSC capacity and elevated numbers of differentiated neurons, and thus correspond to neurogenesis mode in the developing cortex, exhibit slower motions and decreased radial organization. Third, later derived rosettes are characterized by temporal instability in INM measures, in agreement with progressive loss in rosette integrity at later developmental stages. Finally, molecular perturbations of INM by inhibition of actin or non-muscle myosin-II (NMII) reduced INM measures. Our framework enables quantification of cytoarchitecture NSC dynamics and may have implications in functional molecular studies, drug screening, and iPS cell-based platforms for disease modeling.

  16. A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure.

    Science.gov (United States)

    Miconi, Thomas; VanRullen, Rufin

    2016-02-01

    Visual attention has many effects on neural responses, producing complex changes in firing rates, as well as modifying the structure and size of receptive fields, both in topological and feature space. Several existing models of attention suggest that these effects arise from selective modulation of neural inputs. However, anatomical and physiological observations suggest that attentional modulation targets higher levels of the visual system (such as V4 or MT) rather than input areas (such as V1). Here we propose a simple mechanism that explains how a top-down attentional modulation, falling on higher visual areas, can produce the observed effects of attention on neural responses. Our model requires only the existence of modulatory feedback connections between areas, and short-range lateral inhibition within each area. Feedback connections redistribute the top-down modulation to lower areas, which in turn alters the inputs of other higher-area cells, including those that did not receive the initial modulation. This produces firing rate modulations and receptive field shifts. Simultaneously, short-range lateral inhibition between neighboring cells produce competitive effects that are automatically scaled to receptive field size in any given area. Our model reproduces the observed attentional effects on response rates (response gain, input gain, biased competition automatically scaled to receptive field size) and receptive field structure (shifts and resizing of receptive fields both spatially and in complex feature space), without modifying model parameters. Our model also makes the novel prediction that attentional effects on response curves should shift from response gain to contrast gain as the spatial focus of attention drifts away from the studied cell.

  17. Quantitative Live Imaging of Human Embryonic Stem Cell Derived Neural Rosettes Reveals Structure-Function Dynamics Coupled to Cortical Development.

    Directory of Open Access Journals (Sweden)

    Omer Ziv

    2015-10-01

    Full Text Available Neural stem cells (NSCs are progenitor cells for brain development, where cellular spatial composition (cytoarchitecture and dynamics are hypothesized to be linked to critical NSC capabilities. However, understanding cytoarchitectural dynamics of this process has been limited by the difficulty to quantitatively image brain development in vivo. Here, we study NSC dynamics within Neural Rosettes--highly organized multicellular structures derived from human pluripotent stem cells. Neural rosettes contain NSCs with strong epithelial polarity and are expected to perform apical-basal interkinetic nuclear migration (INM--a hallmark of cortical radial glial cell development. We developed a quantitative live imaging framework to characterize INM dynamics within rosettes. We first show that the tendency of cells to follow the INM orientation--a phenomenon we referred to as radial organization, is associated with rosette size, presumably via mechanical constraints of the confining structure. Second, early forming rosettes, which are abundant with founder NSCs and correspond to the early proliferative developing cortex, show fast motions and enhanced radial organization. In contrast, later derived rosettes, which are characterized by reduced NSC capacity and elevated numbers of differentiated neurons, and thus correspond to neurogenesis mode in the developing cortex, exhibit slower motions and decreased radial organization. Third, later derived rosettes are characterized by temporal instability in INM measures, in agreement with progressive loss in rosette integrity at later developmental stages. Finally, molecular perturbations of INM by inhibition of actin or non-muscle myosin-II (NMII reduced INM measures. Our framework enables quantification of cytoarchitecture NSC dynamics and may have implications in functional molecular studies, drug screening, and iPS cell-based platforms for disease modeling.

  18. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    In contemporary consciousness studies the phenomenon of neural plasticity has received little attention despite the fact that neural plasticity is of still increased interest in neuroscience. We will, however, argue that neural plasticity could be of great importance to consciousness studies....... If consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather...... a dynamic entity, which physical structure changes according to its use and environment. This change may take the form of growth of new neurons, the creation of new networks and structures, and change within network structures, that is, changes in synaptic strengths. Plasticity raises questions about...

  19. Alveolar Antral Artery: Review of Surgical Techniques Involving this Anatomic Structure

    Directory of Open Access Journals (Sweden)

    Amin Rahpeyma

    2014-04-01

    Full Text Available Introduction: The horizontal bony canal in the lateral maxillary wall is the site of anastomosis between the arterial branches from the posterior superior alveolar artery (PSAa and the infraorbital artery. This anatomic structure is known as the ‘alveolar antral artery’.   Materials and Methods: We performed a literature review. The anatomic location of the alveolar antral artery in the lateral maxillary sinus wall was researched and its importance in surgical procedures routinely performed on this bony wall discussed.   Results: This artery can be accidentally involved during surgical procedures on the lateral maxillary sinus wall, such as open sinus lift surgery, horizontal osteotomy of the maxilla, Le Fort I fracture treatment, and Caldwell-Luc surgeries.   Conclusion: The alveolar antral artery is an important anatomic structure in the lateral maxillary sinus wall. A preoperative cone beam computed tomography (CBCT scan can be used as a good diagnostic procedure to reduce surgical complications in suspected cases as well as conditions that may involve this artery. 

  20. [Mechanism of neural plasticity of acupuncture on chronic migraine].

    Science.gov (United States)

    Xu, Xiaobai; Liu, Lu; Zhao, Luopeng; Qu, Zhengyang; Zhu, Yupu; Zhang, Yajie; Wang, Linpeng

    2017-10-12

    Chronic migraine is one of neurological disorders with high rate of disability, but sufficient attention has not been paid in this field. A large number of clinical studies have shown traditional Chinese acupuncture is a kind of effective treatment with less side effects. Through the analysis of literature regarding acupuncture and migraine published from 1981 to 2017 in CNKI and PubMed databases, the mechanism of neural plasticity of acupuncture on chronic migraine was explored. It was believed the progress of chronic migraine involved the changes of neural plasticity in neural structure and function, and the neural plasticity related with neural sensitization during the process of chronic migraine was discussed from three aspects of electrophysiology, molecular chemistry and radiography. Acupuncture could treat and prevent chronic migraine via the mechanism of neural plasticity, but there was no related literature, hindering the further spreading and development of acupuncture for chronic migraine.

  1. Autonomic neural control of the cardiovascular system in patients with Behçet's disease in the absence of neurological involvement.

    Science.gov (United States)

    Erol, Tansel; Tekin, Abdullah; Tufan, Müge; Altay, Hakan; Tekin, Göknur; Bilgi, Muhammet; Özin, Bülent; Yücel, Eftal; Müderrisoğlu, Haldun

    2012-10-01

    Behçet's disease (BD) is a chronic multi-system disease presenting with recurrent oral and genital ulceration, and relapsing uveitis. Heart rate recovery (HRR) after exercise is a marker of parasympathetic activity. A delayed recovery of systolic blood pressure (SBP) after exercise might reflect sympathetic hyperactivity. The analysis of variations in heart rate has also been used to determine the balance between sympathetic and vagal nerve activities in the heart. Our objective was to determine HRR, the SBP response to exercise and heart rate variability (HRV) in patients with BD in the absence of neurological involvement. The study population consisted of 32 patients with BD and 30 healthy controls who were matched with respect to age, sex, and physical activity. Heart rate recovery was calculated as the difference between heart rate at peak exercise and heart rate at 1, 2, and 3 min of recovery. Blood pressure recovery indexes were determined by dividing the systolic blood pressure at 2 and 3 min in recovery to the systolic blood pressure at peak exercise. In patients with BD, mean HRR at 1 min (HRR1) were not significantly different than that of controls (21 ± 7 vs 20 ± 7 bpm, p = 0.50). Although, resting mean SBP of patients with BD was higher than controls (121 ± 13 vs 115 ± 12 mmHg, p = 0.039), the SBP recovery indices of the patients with BD at 2 and 3 min were similar to those of controls (0.84 ± 0.07 vs 0.84 ± 0.09, p = 0.89 and 0.78 ± 0.09 vs 0.78 ± 0.08, p = 0.93, respectively). Both time domain and frequency domain parameters of patients with BD were similar to that of controls. This study shows that the patients with BD have normal HRR1 and normal SBP response to exercise and normal HRV. These findings might suggest unaltered autonomic neural control of the cardiovascular system in this disorder in the absence of neurological involvement.

  2. Basement-involved faults and deep structures in the West Philippine Basin: constrains from gravity field

    Science.gov (United States)

    Wang, Gang; Jiang, Suhua; Li, Sanzhong; Zhang, Huixuan; Lei, Jianping; Gao, Song; Zhao, Feiyu

    2017-06-01

    To reveal the basement-involved faults and deep structures of the West Philippine Basin (WPB), the gravitational responses caused by these faults are observed and analyzed based on the latest spherical gravity model: WGM2012 Model. By mapping the free-air and Bouguer gravity anomalies, several main faults and some other linear structures are located and observed in the WPB. Then, by conducting a 2D discrete multi-scale wavelet decomposition, the Bouguer anomalies are decomposed into the first- to eighth-order detail and approximation fields (the first- to eighth-order Details and Approximations). The first- to third-order Details reflect detailed and localized geological information of the crust at different depths, and of which the higher-order reflects gravity field of the deeper depth. The first- to fourth-order Approximations represent the regional gravity fields at different depths of the crust, respectively. The fourth-order Approximation represents the regional gravity fluctuation caused by the density inhomogeneity of Moho interface. Therefore, taking the fourth-order Approximation as input, and adopting Parker-Oldenburg interactive inversion, We calculated the depth of Moho interface in the WPB. Results show that the Moho interface depth in the WPB ranges approximately from 8 to 12 km, indicating that there is typical oceanic crust in the basin. In the Urdaneta Plateau and the Benham Rise, the Moho interface depths are about 14 and 16 km, respectively, which provides a piece of evidence to support that the Banham Rise could be a transitional crust caused by a large igneous province. The second-order vertical derivative and the horizontal derivatives in direction 0° and 90° are computed based on the data of the third-order Detail, and most of the basement-involved faults and structures in the WPB, such as the Central Basin Fault Zone, the Gagua Ridge, the Luzon-Okinawa Fault Zone, and the Mindanao Fault Zone are interpreted by the gravity derivatives.

  3. Neural plasticity expressed in central auditory structures with and without tinnitus

    Directory of Open Access Journals (Sweden)

    Larry E Roberts

    2012-05-01

    Full Text Available Sensory training therapies for tinnitus are based on the assumption that, notwithstanding neural changes related to tinnitus, auditory training can alter the response properties of neurons in auditory pathways. To address this question, we investigated whether brain changes induced by sensory training in tinnitus sufferers and measured by EEG are similar to those induced in age and hearing loss matched individuals without tinnitus trained on the same auditory task. Auditory training was given using a 5 kHz 40-Hz amplitude-modulated sound that was in the tinnitus frequency region of the tinnitus subjects and enabled extraction of the 40-Hz auditory steady-state response (ASSR and P2 transient response known to localize to primary and nonprimary auditory cortex, respectively. P2 amplitude increased with training equally in participants with tinnitus and in control subjects, suggesting normal remodeling of nonprimary auditory regions in tinnitus. However, training-induced changes in the ASSR differed between the tinnitus and control groups. In controls ASSR phase advanced toward the stimulus waveform by about ten degrees over training, in agreement with previous results obtained in young normal hearing individuals. However, ASSR phase did not change significantly with training in the tinnitus group, although some participants showed phase shifts resembling controls. On the other hand, ASSR amplitude increased with training in the tinnitus group, whereas in controls this response (which is difficult to remodel in young normal hearing subjects did not change with training. These results suggest that neural changes related to tinnitus altered how neural plasticity was expressed in the region of primary but not nonprimary auditory cortex. Auditory training did not reduce tinnitus loudness although a small effect on the tinnitus spectrum was detected.

  4. Neural reuse: a fundamental organizational principle of the brain.

    Science.gov (United States)

    Anderson, Michael L

    2010-08-01

    An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design.

  5. Weighted spiking neural P systems with structural plasticity working in sequential mode based on maximum spike number

    Science.gov (United States)

    Sun, Mingming; Qu, Jianhua

    2017-10-01

    Spiking neural P systems (SNP systems, in short) are a group of parallel and distributed computing devices inspired by the function and structure of spiking neurons. Recently, a new variant of SNP systems, called SNP systems with structural plasticity (SNPSP systems, in short) was proposed. In SNPSP systems, neuron can use plasticity ru les to create and delete synapses. In this work, we consider many restrictions sequentiality on SNPSP systems: (1) neuron with the maximum number of spikes is chosen to fire; (2) we use the weighted synapses. Specifically, we investigate the computational power of weighted SNPSP systems working in the sequential mode based on maximum spike number (WSNPSPM systems, in short) and we proved that SNPSP systems with these new restrictions are universal as generating devices.

  6. Crystal structure of the Ig1 domain of the neural cell adhesion molecule NCAM2 displays domain swapping.

    Science.gov (United States)

    Rasmussen, Kim K; Kulahin, Nikolaj; Kristensen, Ole; Poulsen, Jens-Christian N; Sigurskjold, Bent W; Kastrup, Jette S; Berezin, Vladimir; Bock, Elisabeth; Walmod, Peter S; Gajhede, Michael

    2008-10-24

    The crystal structure of the first immunoglobulin (Ig1) domain of neural cell adhesion molecule 2 (NCAM2/OCAM/RNCAM) is presented at a resolution of 2.7 A. NCAM2 is a member of the immunoglobulin superfamily of cell adhesion molecules (IgCAMs). In the structure, two Ig domains interact by domain swapping, as the two N-terminal beta-strands are interchanged. beta-Strand swapping at the terminal domain is the accepted mechanism of homophilic interactions amongst the cadherins, another class of CAMs, but it has not been observed within the IgCAM superfamily. Gel-filtration chromatography demonstrated the ability of NCAM2 Ig1 to form dimers in solution. Taken together, these observations suggest that beta-strand swapping could have a role in the molecular mechanism of homophilic binding for NCAM2.

  7. Neural substrates of decision-making.

    Science.gov (United States)

    Broche-Pérez, Y; Herrera Jiménez, L F; Omar-Martínez, E

    2016-06-01

    Decision-making is the process of selecting a course of action from among 2 or more alternatives by considering the potential outcomes of selecting each option and estimating its consequences in the short, medium and long term. The prefrontal cortex (PFC) has traditionally been considered the key neural structure in decision-making process. However, new studies support the hypothesis that describes a complex neural network including both cortical and subcortical structures. The aim of this review is to summarise evidence on the anatomical structures underlying the decision-making process, considering new findings that support the existence of a complex neural network that gives rise to this complex neuropsychological process. Current evidence shows that the cortical structures involved in decision-making include the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). This process is assisted by subcortical structures including the amygdala, thalamus, and cerebellum. Findings to date show that both cortical and subcortical brain regions contribute to the decision-making process. The neural basis of decision-making is a complex neural network of cortico-cortical and cortico-subcortical connections which includes subareas of the PFC, limbic structures, and the cerebellum. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

  8. Classification of Forest Vertical Structure in South Korea from Aerial Orthophoto and Lidar Data Using an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Soo-Kyung Kwon

    2017-10-01

    Full Text Available Every vegetation colony has its own vertical structure. Forest vertical structure is considered as an important indicator of a forest’s diversity and vitality. The vertical structure of a forest has typically been investigated by field survey, which is the traditional method of forest inventory. However, this method is very time- and cost-consuming due to poor accessibility. Remote sensing data such as satellite imagery, aerial photography, and lidar data can be a viable alternative to the traditional field-based forestry survey. In this study, we classified forest vertical structures from red-green-blue (RGB aerial orthophotos and lidar data using an artificial neural network (ANN, which is a powerful machine learning technique. The test site was Gongju province in South Korea, which contains single-, double-, and triple-layered forest structures. The performance of the proposed method was evaluated by comparing the results with field survey data. The overall accuracy achieved was about 70%. It means that the proposed approach can classify the forest vertical structures from the aerial orthophotos and lidar data.

  9. Crystal structure of a bicupin protein HutD involved in histidine utilization in Pseudomonas.

    Science.gov (United States)

    Gerth, M L; Liu, Y; Jiao, W; Zhang, X-X; Baker, E N; Lott, J S; Rainey, P B; Johnston, J M

    2017-08-01

    Cupins form one of the most functionally diverse superfamilies of proteins, with members performing a wide range of catalytic, non-catalytic, and regulatory functions. HutD is a predicted bicupin protein that is involved in histidine utilization (Hut) in Pseudomonas species. Previous genetic analyses have suggested that it limits the upper level of Hut pathway expression, but its mechanism of action is unknown. Here, we have determined the structure of PfluHutD at 1.74 Å resolution in several crystallization conditions, and identified N-formyl-l-glutamate (FG, a Hut pathway intermediate) as a potential ligand in vivo. Proteins 2017; 85:1580-1588. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  10. Segmentation of Bone Structure in X-ray Images using Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    CERNAZANU-GLAVAN, C.

    2013-02-01

    Full Text Available The segmentation process represents a first step necessary for any automatic method of extracting information from an image. In the case of X-ray images, through segmentation we can differentiate the bone tissue from the rest of the image. There are nowadays several segmentation techniques, but in general, they all require the human intervention in the segmentation process. Consequently, this article proposes a new segmentation method for the X-ray images using a Convolutional Neural Network (CNN. In present, the convolutional networks are the best techniques for image segmentation. This fact is demonstrated by their wide usage in all the fields, including the medical one. As the X-ray images have large dimensions, for reducing the training time, the method proposed by the present article selects only certain areas (maximum interest areas from the entire image. The neural network is used as pixel classifier thus causing the label of each pixel (bone or none-bone from a raw pixel values in a square area. We will also present the method through which the network final configuration was chosen and we will make a comparative analysis with other 3 CNN configurations. The network chosen by us obtained the best results for all the evaluation metrics used, i.e. warping error, rand error and pixel error.

  11. Structural Health Monitoring and Impact Detection Using Neural Networks for Damage Characterization

    Science.gov (United States)

    Ross, Richard W.

    2006-01-01

    Detection of damage due to foreign object impact is an important factor in the development of new aerospace vehicles. Acoustic waves generated on impact can be detected using a set of piezoelectric transducers, and the location of impact can be determined by triangulation based on the differences in the arrival time of the waves at each of the sensors. These sensors generate electrical signals in response to mechanical motion resulting from the impact as well as from natural vibrations. Due to electrical noise and mechanical vibration, accurately determining these time differentials can be challenging, and even small measurement inaccuracies can lead to significant errors in the computed damage location. Wavelet transforms are used to analyze the signals at multiple levels of detail, allowing the signals resulting from the impact to be isolated from ambient electromechanical noise. Data extracted from these transformed signals are input to an artificial neural network to aid in identifying the moment of impact from the transformed signals. By distinguishing which of the signal components are resultant from the impact and which are characteristic of noise and normal aerodynamic loads, the time differentials as well as the location of damage can be accurately assessed. The combination of wavelet transformations and neural network processing results in an efficient and accurate approach for passive in-flight detection of foreign object damage.

  12. Structured chaos shapes spike-response noise entropy in balanced neural networks

    Directory of Open Access Journals (Sweden)

    Guillaume eLajoie

    2014-10-01

    Full Text Available Large networks of sparsely coupled, excitatory and inhibitory cells occur throughout the brain. For many models of these networks, a striking feature is that their dynamics are chaotic and thus, are sensitive to small perturbations. How does this chaos manifest in the neural code? Specifically, how variable are the spike patterns that such a network produces in response to an input signal? To answer this, we derive a bound for a general measure of variability -- spike-train entropy. This leads to important insights on the variability of multi-cell spike pattern distributions in large recurrent networks of spiking neurons responding to fluctuating inputs. The analysis is based on results from random dynamical systems theory and is complemented by detailed numerical simulations. We find that the spike pattern entropy is an order of magnitude lower than what would be extrapolated from single cells. This holds despite the fact that network coupling becomes vanishingly sparse as network size grows -- a phenomenon that depends on ``extensive chaos, as previously discovered for balanced networks without stimulus drive. Moreover, we show how spike pattern entropy is controlled by temporal features of the inputs. Our findings provide insight into how neural networks may encode stimuli in the presence of inherently chaotic dynamics.

  13. Reprogramming fibroblasts to neural-precursor-like cells by structured overexpression of pallial patterning genes.

    Science.gov (United States)

    Raciti, Marilena; Granzotto, Marilena; Duc, Minh Do; Fimiani, Cristina; Cellot, Giada; Cherubini, Enrico; Mallamaci, Antonello

    2013-11-01

    In this study, we assayed the capability of four genes implicated in embryonic specification of the cortico-cerebral field, Foxg1, Pax6, Emx2 and Lhx2, to reprogramme mouse embryonic fibroblasts towards neural identities. Lentivirus-mediated, TetON-dependent overexpression of Pax6 and Foxg1 transgenes specifically activated the neural stem cell (NSC) reporter Sox1-EGFP in a substantial fraction of engineered cells. The efficiency of this process was enhanced up to ten times by simultaneous inactivation of Trp53 and co-administration of a specific drug mix inhibiting HDACs, H3K27-HMTase and H3K4m2-demethylase. Remarkably, a fraction of the reprogrammed population expressed other NSC markers and retained its new identity, even after switching off the reprogramming transgenes. When transferred into a pro-differentiative environment, Pax6/Foxg1-overexpressing cells activated the neuronal marker Tau-EGFP. Frequency of Tau-EGFP positive cells was almost doubled upon delayed delivery of Emx2 and Lhx2 transgenes. A further improvement of the neuron-like cell output was achieved by inhibition of the BMP and TGFβ pathways. Tau-EGFP positive cells were able to generate action potentials upon injection of depolarizing current pulses, further indicating their neuron-like phenotype. © 2013.

  14. Neural Networks in Mobile Robot Motion

    Directory of Open Access Journals (Sweden)

    Danica Janglová

    2004-03-01

    Full Text Available This paper deals with a path planning and intelligent control of an autonomous robot which should move safely in partially structured environment. This environment may involve any number of obstacles of arbitrary shape and size; some of them are allowed to move. We describe our approach to solving the motion-planning problem in mobile robot control using neural networks-based technique. Our method of the construction of a collision-free path for moving robot among obstacles is based on two neural networks. The first neural network is used to determine the “free” space using ultrasound range finder data. The second neural network “finds” a safe direction for the next robot section of the path in the workspace while avoiding the nearest obstacles. Simulation examples of generated path with proposed techniques will be presented.

  15. Neural Networks in Mobile Robot Motion

    Directory of Open Access Journals (Sweden)

    Danica Janglova

    2008-11-01

    Full Text Available This paper deals with a path planning and intelligent control of an autonomous robot which should move safely in partially structured environment. This environment may involve any number of obstacles of arbitrary shape and size; some of them are allowed to move. We describe our approach to solving the motion-planning problem in mobile robot control using neural networks-based technique. Our method of the construction of a collision-free path for moving robot among obstacles is based on two neural networks. The first neural network is used to determine the "free" space using ultrasound range finder data. The second neural network "finds" a safe direction for the next robot section of the path in the workspace while avoiding the nearest obstacles. Simulation examples of generated path with proposed techniques will be presented.

  16. Fluid-structure interaction involving large deformations: 3D simulations and applications to biological systems

    Science.gov (United States)

    Tian, Fang-Bao; Dai, Hu; Luo, Haoxiang; Doyle, James F.; Rousseau, Bernard

    2014-02-01

    Three-dimensional fluid-structure interaction (FSI) involving large deformations of flexible bodies is common in biological systems, but accurate and efficient numerical approaches for modeling such systems are still scarce. In this work, we report a successful case of combining an existing immersed-boundary flow solver with a nonlinear finite-element solid-mechanics solver specifically for three-dimensional FSI simulations. This method represents a significant enhancement from the similar methods that are previously available. Based on the Cartesian grid, the viscous incompressible flow solver can handle boundaries of large displacements with simple mesh generation. The solid-mechanics solver has separate subroutines for analyzing general three-dimensional bodies and thin-walled structures composed of frames, membranes, and plates. Both geometric nonlinearity associated with large displacements and material nonlinearity associated with large strains are incorporated in the solver. The FSI is achieved through a strong coupling and partitioned approach. We perform several validation cases, and the results may be used to expand the currently limited database of FSI benchmark study. Finally, we demonstrate the versatility of the present method by applying it to the aerodynamics of elastic wings of insects and the flow-induced vocal fold vibration.

  17. Protein Machineries Involved in the Attachment of Heme to Cytochrome c: Protein Structures and Molecular Mechanisms

    Directory of Open Access Journals (Sweden)

    Carlo Travaglini-Allocatelli

    2013-01-01

    Full Text Available Cytochromes c (Cyt c are ubiquitous heme-containing proteins, mainly involved in electron transfer processes, whose structure and functions have been and still are intensely studied. Surprisingly, our understanding of the molecular mechanism whereby the heme group is covalently attached to the apoprotein (apoCyt in the cell is still largely unknown. This posttranslational process, known as Cyt c biogenesis or Cyt c maturation, ensures the stereospecific formation of the thioether bonds between the heme vinyl groups and the cysteine thiols of the apoCyt heme binding motif. To accomplish this task, prokaryotic and eukaryotic cells have evolved distinctive protein machineries composed of different proteins. In this review, the structural and functional properties of the main maturation apparatuses found in gram-negative and gram-positive bacteria and in the mitochondria of eukaryotic cells will be presented, dissecting the Cyt c maturation process into three functional steps: (i heme translocation and delivery, (ii apoCyt thioreductive pathway, and (iii apoCyt chaperoning and heme ligation. Moreover, current hypotheses and open questions about the molecular mechanisms of each of the three steps will be discussed, with special attention to System I, the maturation apparatus found in gram-negative bacteria.

  18. A new structural arrangement in proteins involving lysine NH3+ group and carbonyl.

    Science.gov (United States)

    Rogacheva, Olga N; Izmailov, Sergei A; Slipchenko, Lyudmila V; Skrynnikov, Nikolai R

    2017-11-27

    Screening of the Protein Data Bank led to identification of a recurring structural motif where lysine NH3+ group interacts with backbone carbonyl. This interaction is characterized by linear atom arrangement, with carbonyl O atom positioned on the three-fold symmetry axis of the NH3+ group (angle Cε-Nζ-O close to 180°, distance Nζ-O ca. 2.7-3.0 Å). Typically, this linear arrangement coexists with three regular hydrogen bonds formed by lysine NH3+ group (angle Cε-Nζ-acceptor atom close to 109°, distance Nζ-acceptor atom ca. 2.7-3.0 Å). Our DFT calculations using polarizable continuum environment suggest that this newly identified linear interaction makes an appreciable contribution to protein's energy balance, up to 2 kcal/mol. In the context of protein structure, linear interactions play a role in capping the C-termini of α-helices and 310-helices. Of note, linear interaction involving conserved lysine is consistently found in the P-loop of numerous NTPase domains, where it stabilizes the substrate-binding conformation of the P-loop. Linear interaction NH3+ - carbonyl represents an interesting example of ion-dipole interactions that has so far received little attention compared to ion-ion interactions (salt bridges) and dipole-dipole interactions (hydrogen bonds), but nevertheless represents a distinctive element of protein architecture.

  19. Eigenspectrum bounds for semirandom matrices with modular and spatial structure for neural networks.

    Science.gov (United States)

    Muir, Dylan R; Mrsic-Flogel, Thomas

    2015-04-01

    The eigenvalue spectrum of the matrix of directed weights defining a neural network model is informative of several stability and dynamical properties of network activity. Existing results for eigenspectra of sparse asymmetric random matrices neglect spatial or other constraints in determining entries in these matrices, and so are of partial applicability to cortical-like architectures. Here we examine a parameterized class of networks that are defined by sparse connectivity, with connection weighting modulated by physical proximity (i.e., asymmetric Euclidean random matrices), modular network partitioning, and functional specificity within the excitatory population. We present a set of analytical constraints that apply to the eigenvalue spectra of associated weight matrices, highlighting the relationship between connectivity rules and classes of network dynamics.

  20. Dynamic Changes in Ezh2 Gene Occupancy Underlie Its Involvement in Neural Stem Cell Self-Renewal and Differentiation towards Oligodendrocytes

    NARCIS (Netherlands)

    Sher, Falak; Boddeke, Erik; Olah, Marta; Copray, Sjef

    2012-01-01

    Background: The polycomb group protein Ezh2 is an epigenetic repressor of transcription originally found to prevent untimely differentiation of pluripotent embryonic stem cells. We previously demonstrated that Ezh2 is also expressed in multipotent neural stem cells (NSCs). We showed that Ezh2

  1. The neural crest and neural crest cells: discovery and significance ...

    Indian Academy of Sciences (India)

    In this paper I provide a brief overview of the major phases of investigation into the neural crest and the major players involved, discuss how the origin of the neural crest relates to the origin of the nervous system in vertebrate embryos, discuss the impact on the germ-layer theory of the discovery of the neural crest and of ...

  2. Evaluation of hierarchical structured representations for QSPR studies of small molecules and polymers by recursive neural networks.

    Science.gov (United States)

    Bertinetto, Carlo; Duce, Celia; Micheli, Alessio; Solaro, Roberto; Starita, Antonina; Tiné, Maria Rosaria

    2009-04-01

    This paper reports some recent results from the empirical evaluation of different types of structured molecular representations used in QSPR analysis through a recursive neural network (RNN) model, which allows for their direct use without the need for measuring or computing molecular descriptors. This RNN methodology has been applied to the prediction of the properties of small molecules and polymers. In particular, three different descriptions of cyclic moieties, namely group, template and cyclebreak have been proposed. The effectiveness of the proposed method in dealing with different representations of chemical structures, either specifically designed or of more general use, has been demonstrated by its application to data sets encompassing various types of cyclic structures. For each class of experiments a test set with data that were not used for the development of the model was used for validation, and the comparisons have been based on the test results. The reported results highlight the flexibility of the RNN in directly treating different classes of structured input data without using input descriptors.

  3. Fluid-structure interaction involving dynamic wetting: 2D modeling and simulations

    Science.gov (United States)

    Liu, Hao-Ran; Gao, Peng; Ding, Hang

    2017-11-01

    In this paper, we propose a hybrid model to compute the capillary force acting on moving solid objects, and combine it with the diffuse-interface immersed-boundary method in Liu and Ding (2015) [18] to simulate fluid-structure interaction (FSI) involving dynamic wetting. Dynamic wetting is very important in the dynamic interaction between fluid-fluid interfaces and small moving objects. Numerical simulations of these flow problems require accurate computation of the capillary force acting on the structure, which depends on the instantaneous position of and the effective surface tension at the moving contact line. In order to achieve this, we use the diffuse-interface immersed-boundary method to simulate the dynamic wetting on moving objects, and propose a hybrid model to compute the effective surface tension at the contact line. Specifically, a diffuse interface model is used for the interface profile out of equilibrium, e.g. at the onset of formation or detachment of contact lines, and a sharp interface model is used for the interface profile at equilibrium. The performance of the method is examined by a variety of numerical experiments. We simulate the sinking of a circular cylinder due to gravity, and study the capillarity-dominated impact dynamics of a solid sphere on a water pool. In both cases the numerical results are quantitatively compared against the experimental data, and good agreements have been achieved. The momentum conservation of the system is carefully checked by studying head-on collision between a drop and a solid sphere. Finally, we apply the method to the self-assembly process of multiple floating cylinders on water surface.

  4. SEORious business: structural proteins in sieve tubes and their involvement in sieve element occlusion.

    Science.gov (United States)

    Knoblauch, Michael; Froelich, Daniel R; Pickard, William F; Peters, Winfried S

    2014-04-01

    The phloem provides a network of sieve tubes for long-distance translocation of photosynthates. For over a century, structural proteins in sieve tubes have presented a conundrum since they presumably increase the hydraulic resistance of the tubes while no potential function other than sieve tube or wound sealing in the case of injury has been suggested. Here we summarize and critically evaluate current speculations regarding the roles of these proteins. Our understanding suffers from the suggestive power of images; what looks like a sieve tube plug on micrographs may not actually impede translocation very much. Recent reports of an involvement of SEOR (sieve element occlusion-related) proteins, a class of P-proteins, in the sealing of injured sieve tubes are inconclusive; various lines of evidence suggest that, in neither intact nor injured plants, are SEORs determinative of translocation stoppage. Similarly, the popular notion that P-proteins serve in the defence against phloem sap-feeding insects is unsupported by empirical facts; it is conceivable that in functional sieve tubes, aphids actually could benefit from inducing a plug. The idea that rising cytosolic Ca(2+) generally triggers sieve tube blockage by P-proteins appears widely accepted, despite lacking experimental support. Even in forisomes, P-protein assemblages restricted to one single plant family and the only Ca(2+)-responsive P-proteins known, the available evidence does not unequivocally suggest that plug formation is the cause rather than a consequence of translocation stoppage. We conclude that the physiological roles of structural P-proteins remain elusive, and that in vivo studies of their dynamics in continuous sieve tube networks combined with flow velocity measurements will be required to (hopefully) resolve this scientific roadblock.

  5. Enhanced expression of FNDC5 in human embryonic stem cell-derived neural cells along with relevant embryonic neural tissues.

    Science.gov (United States)

    Ghahrizjani, Fatemeh Ahmadi; Ghaedi, Kamran; Salamian, Ahmad; Tanhaei, Somayeh; Nejati, Alireza Shoaraye; Salehi, Hossein; Nabiuni, Mohammad; Baharvand, Hossein; Nasr-Esfahani, Mohammad Hossein

    2015-02-25

    Availability of human embryonic stem cells (hESCs) has enhanced the capability of basic and clinical research in the context of human neural differentiation. Derivation of neural progenitor (NP) cells from hESCs facilitates the process of human embryonic development through the generation of neuronal subtypes. We have recently indicated that fibronectin type III domain containing 5 protein (FNDC5) expression is required for appropriate neural differentiation of mouse embryonic stem cells (mESCs). Bioinformatics analyses have shown the presence of three isoforms for human FNDC5 mRNA. To differentiate which isoform of FNDC5 is involved in the process of human neural differentiation, we have used hESCs as an in vitro model for neural differentiation by retinoic acid (RA) induction. The hESC line, Royan H5, was differentiated into a neural lineage in defined adherent culture treated by RA and basic fibroblast growth factor (bFGF). We collected all cell types that included hESCs, rosette structures, and neural cells in an attempt to assess the expression of FNDC5 isoforms. There was a contiguous increase in all three FNDC5 isoforms during the neural differentiation process. Furthermore, the highest level of expression of the isoforms was significantly observed in neural cells compared to hESCs and the rosette structures known as neural precursor cells (NPCs). High expression levels of FNDC5 in human fetal brain and spinal cord tissues have suggested the involvement of this gene in neural tube development. Additional research is necessary to determine the major function of FDNC5 in this process. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Association of father involvement and neighborhood quality with kindergartners' physical activity: a multilevel structural equation model.

    Science.gov (United States)

    Beets, Michael W; Foley, John T

    2008-01-01

    Examine the effects of father-child involvement and neighborhood characteristics with young children's physical activity (PA) within a multilevel framework. Cross-sectional analysis of the Early Childhood Longitudinal Study-Kindergarten Cohort 1998. Nationally representative sample. Data were available for 10,694 kindergartners (5-6 years; 5240 girls) living in 1053 neighborhoods. Parental report of child's PA level, father characteristics (e.g., time spent with child, age, education, socioeconomic status, hours worked), family time spent doing sports/ activities together, and neighborhood quality (e.g., safety, presence of crime violence, garbage). Child weight status, motor skills, ethnicity, and television viewing were used as covariates. Multilevel structural equation modeling with children nested within neighborhoods. At the child level father-child time and family time doing sports together were positively associated with children's PA. At the neighborhood level parental perception of a neighborhood's safety for children to play outside fully mediated the effect of neighborhood quality on children's PA. Overall 19.1% and 7.6% of the variance in PA was explained at the child and neighborhood levels, respectively. Family-based interventions for PA should consider father-child time, with this contributing to a child's overall PA level. Further, neighborhood quality is an important predictor of PA only to the extent by which parents perceive it to be unsafe for their child to play outdoors.

  7. A structural model of customer satisfaction and trust in vendors involved in mobile commerce

    Directory of Open Access Journals (Sweden)

    Suki, N.M.

    2011-01-01

    Full Text Available The purpose of this paper is to provide an explanation of factors influencing customer satisfaction and trust in vendors involved in mobile commerce (m-commerce. The study sample consists of 200 respondents. Data were analyzed by employing structural equation modelling (SEM supported by AMOS 5.0 with maximum likelihood estimation in order to test the proposed hypotheses. The proposed model was empirically tested and results confirmed that users’ satisfaction with vendors in m-commerce was not significantly influenced by two antecedents of the vendor’s website quality: interactivity and customisation, and also two antecedents of mobile technology quality: usefulness and ease-of-use. Meanwhile, users’ trust towards the vendor in m-commerce is affected by users’ satisfaction with the vendor. Interestingly, vendor quality dimensions such as responsiveness and brand image influence customer satisfaction with vendors in m-commerce. Based on the findings, vendors in m-commerce should focus on the factors which generate more satisfaction and trust among customers. For vendors in general, the results can help them to better develop customer trust in m-commerce. Vendors of m-commerce can provide a more satisfying experience for customers.

  8. Structural myocardial involvement in adult patients with type 1 myotonic dystrophy

    Directory of Open Access Journals (Sweden)

    Upinder K. Dhand

    2013-03-01

    Full Text Available Myotonic dystrophy type 1 (DM1 is the commonest muscular dystrophy in adults, affecting multiple organs in addition to skeletal muscles. Cardiac conduction system abnormalities are well recognized as an important component of DM1 phenotype; however, primary structural myocardial abnormalities, which may predispose these patients to congestive heart failure, are not as well characterized. We reviewed the retrospective analysis of the clinical and echocardiographic findings in adult patients with DM1. Among 27 patients (16 male; age 19-61 years with DM1, the echocardiogram (ECHO was abnormal in 10 (37% including one of 6 patients (16% with congenital myotonic dystrophy. Reduced left ventricular ejection fraction (LVEF ≤50% was noted in 5, diastolic dysfunction in 4, left atrial dilatation in 3, left ventricular hypertrophy in 2, apical hypokinesia in 1 and mitral valve prolapse in 3 patients. One patient had paradoxical septal movement in the setting of left bundle branch block. Echocardiographic abnormalities significantly correlated with older age; however, patients with systolic dysfunction on echocardiogram ranged in age from 27 to 52 years including 2 patients aged 27 and 34 years. We can conclude that echocardiographic abnormalities are frequent in adult patients with DM1. The incidence is similar in the classical and congenital type of DM1. Overall, echocardiographic abnormalities in DM1 correlate with increasing age; however, reduced LVEF is observed even at young age. Cardiac assessment and monitoring in adult patients with DM1 should include evaluation for primary myocardial involvement.

  9. Neural Network Enhanced Structure Determination of Osteoporosis, Immune System, and Radiation Repair Proteins Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose a dual objective innovation that has valuable NASA applicability and tremendous commercial potential. The first innovation is the structure determination...

  10. Systematic analysis of non-structural protein features for the prediction of PTM function potential by artificial neural networks.

    Science.gov (United States)

    Dewhurst, Henry M; Torres, Matthew P

    2017-01-01

    Post-translational modifications (PTMs) provide an extensible framework for regulation of protein behavior beyond the diversity represented within the genome alone. While the rate of identification of PTMs has rapidly increased in recent years, our knowledge of PTM functionality encompasses less than 5% of this data. We previously developed SAPH-ire (Structural Analysis of PTM Hotspots) for the prioritization of eukaryotic PTMs based on function potential of discrete modified alignment positions (MAPs) in a set of 8 protein families. A proteome-wide expansion of the dataset to all families of PTM-bearing, eukaryotic proteins with a representational crystal structure and the application of artificial neural network (ANN) models demonstrated the broader applicability of this approach. Although structural features of proteins have been repeatedly demonstrated to be predictive of PTM functionality, the availability of adequately resolved 3D structures in the Protein Data Bank (PDB) limits the scope of these methods. In order to bridge this gap and capture the larger set of PTM-bearing proteins without an available, homologous structure, we explored all available MAP features as ANN inputs to identify predictive models that do not rely on 3D protein structural data. This systematic, algorithmic approach explores 8 available input features in exhaustive combinations (247 models; size 2-8). To control for potential bias in random sampling for holdback in training sets, we iterated each model across 100 randomized, sample training and testing sets-yielding 24,700 individual ANNs. The size of the analyzed dataset and iterative generation of ANNs represents the largest and most thorough investigation of predictive models for PTM functionality to date. Comparison of input layer combinations allows us to quantify ANN performance with a high degree of confidence and subsequently select a top-ranked, robust fit model which highlights 3,687 MAPs, including 10,933 PTMs with a high

  11. Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au147 nanocluster

    Science.gov (United States)

    Jindal, Shweta; Chiriki, Siva; Bulusu, Satya S.

    2017-05-01

    We propose a highly efficient method for fitting the potential energy surface of a nanocluster using a spherical harmonics based descriptor integrated with an artificial neural network. Our method achieves the accuracy of quantum mechanics and speed of empirical potentials. For large sized gold clusters (Au147), the computational time for accurate calculation of energy and forces is about 1.7 s, which is faster by several orders of magnitude compared to density functional theory (DFT). This method is used to perform the global minimum optimizations and molecular dynamics simulations for Au147, and it is found that its global minimum is not an icosahedron. The isomer that can be regarded as the global minimum is found to be 4 eV lower in energy than the icosahedron and is confirmed from DFT. The geometry of the obtained global minimum contains 105 atoms on the surface and 42 atoms in the core. A brief study on the fluxionality in Au147 is performed, and it is concluded that Au147 has a dynamic surface, thus opening a new window for studying its reaction dynamics.

  12. Human neural progenitor cells decrease photoreceptor degeneration, normalize opsin distribution and support synapse structure in cultured porcine retina.

    Science.gov (United States)

    Mollick, Tanzina; Mohlin, Camilla; Johansson, Kjell

    2016-09-01

    Retinal neurodegenerative disorders like retinitis pigmentosa, age-related macular degeneration, diabetic retinopathy and retinal detachment decrease retinal functionality leading to visual impairment. The pathological events are characterized by photoreceptor degeneration, synaptic disassembly, remodeling of postsynaptic neurons and activation of glial cells. Despite intense research, no effective treatment has been found for these disorders. The current study explores the potential of human neural progenitor cell (hNPC) derived factors to slow the degenerative processes in adult porcine retinal explants. Retinas were cultured for 3 days with or without hNPCs as a feeder layer and investigated by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), immunohistochemical, western blot and quantitative real time-polymerase chain reaction (qRT-PCR) techniques. TUNEL showed that hNPCs had the capacity to limit photoreceptor cell death. Among cone photoreceptors, hNPC coculture resulted in better maintenance of cone outer segments and reduced opsin mislocalization. Additionally, maintained synaptic structural integrity and preservation of second order calbindin positive horizontal cells was also observed. However, Müller cell gliosis only seemed to be alleviated in terms of reduced Müller cell density. Our observations indicate that at 3 days of coculture, hNPC derived factors had the capacity to protect photoreceptors, maintain synaptic integrity and support horizontal cell survival. Human neural progenitor cell applied treatment modalities may be an effective strategy to help maintain retinal functionality in neurodegenerative pathologies. Whether hNPCs can independently hinder Müller cell gliosis by utilizing higher concentrations or by combination with other pharmacological agents still needs to be determined. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. What Is Neural Plasticity?

    Science.gov (United States)

    von Bernhardi, Rommy; Bernhardi, Laura Eugenín-von; Eugenín, Jaime

    2017-01-01

    "Neural plasticity" refers to the capacity of the nervous system to modify itself, functionally and structurally, in response to experience and injury. As the various chapters in this volume show, plasticity is a key component of neural development and normal functioning of the nervous system, as well as a response to the changing environment, aging, or pathological insult. This chapter discusses how plasticity is necessary not only for neural networks to acquire new functional properties, but also for them to remain robust and stable. The article also reviews the seminal proposals developed over the years that have driven experiments and strongly influenced concepts of neural plasticity.

  14. Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks

    Science.gov (United States)

    Buiu, Cătălin; Putz, Mihai V.; Avram, Speranta

    2016-01-01

    The dependency between the primary structure of HIV envelope glycoproteins (ENV) and the neutralization data for given antibodies is very complicated and depends on a large number of factors, such as the binding affinity of a given antibody for a given ENV protein, and the intrinsic infection kinetics of the viral strain. This paper presents a first approach to learning these dependencies using an artificial feedforward neural network which is trained to learn from experimental data. The results presented here demonstrate that the trained neural network is able to generalize on new viral strains and to predict reliable values of neutralizing activities of given antibodies against HIV-1. PMID:27727189

  15. Musical intervention enhances infants' neural processing of temporal structure in music and speech

    National Research Council Canada - National Science Library

    Zhao, T Christina; Kuhl, Patricia K

    2016-01-01

    .... The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize...

  16. Musical intervention enhances infants' neural processing of temporal structure in music and speech

    National Research Council Canada - National Science Library

    Zhao, T Christina; Kuhl, Patricia K

    2016-01-01

    .... The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize learning (e.g...

  17. The Impact of Parental Involvement on a Structured Youth Program Experience: A Qualitative Inquiry

    Directory of Open Access Journals (Sweden)

    Mat D. Duerden

    2013-12-01

    Full Text Available Parental involvement is an often proposed, but rarely researched, key element of youth programs. Questions remain regarding the impact of parental involvement on program processes and outcomes. Qualitative data were collected over a one-year period with youth participants (n=46, parents (n=26, and teachers (n=5 associated with an international immersion/service learning program for adolescents. Three main research questions guided the data analysis: (1 what role does parental involvement play in the youths’ experience in the program; (2 how does parental involvement in the program influence the parent/child relationship; and (3 what role does parental involvement play in terms of the program’s long-term impact on the youth participants? Findings suggest a relationship between parental involvement in youth programs and improved parent/child communication, bonding, and perceptions of one another. Findings also suggest that having a common ground experience prolonged the experience’s positive post-participation effects.

  18. GIAO C-H COSY Simulations Merged with Artificial Neural Networks Pattern Recognition Analysis. Pushing the Structural Validation a Step Forward.

    Science.gov (United States)

    Zanardi, María M; Sarotti, Ariel M

    2015-10-02

    The structural validation problem using quantum chemistry approaches (confirm or reject a candidate structure) has been tackled with artificial neural network (ANN) mediated multidimensional pattern recognition from experimental and calculated 2D C-H COSY. In order to identify subtle errors (such as regio- or stereochemical), more than 400 ANNs have been built and trained, and the most efficient in terms of classification ability were successfully validated in challenging real examples of natural product misassignments.

  19. Structure Crack Identification Based on Surface-mounted Active Sensor Network with Time-Domain Feature Extraction and Neural Network

    Directory of Open Access Journals (Sweden)

    Chunling DU

    2012-03-01

    Full Text Available In this work the condition of metallic structures are classified based on the acquired sensor data from a surface-mounted piezoelectric sensor/actuator network. The structures are aluminum plates with riveted holes and possible crack damage at these holes. A 400 kHz sine wave burst is used as diagnostic signals. The combination of time-domain S0 waves from received sensor signals is directly used as features and preprocessing is not needed for the dam age detection. Since the time sequence of the extracted S0 has a high dimension, principal component estimation is applied to reduce its dimension before entering NN (neural network training for classification. An LVQ (learning vector quantization NN is used to classify the conditions as healthy or damaged. A number of FEM (finite element modeling results are taken as inputs to the NN for training, since the simulated S0 waves agree well with the experimental results on real plates. The performance of the classification is then validated by using these testing results.

  20. Structural Basis for Partial Redundancy in a Class of Transcription Factors, the LIM Homeodomain Proteins, in Neural Cell Type Specification*

    Science.gov (United States)

    Gadd, Morgan S.; Bhati, Mugdha; Jeffries, Cy M.; Langley, David B.; Trewhella, Jill; Guss, J. Mitchell; Matthews, Jacqueline M.

    2011-01-01

    Combinations of LIM homeodomain proteins form a transcriptional “LIM code” to direct the specification of neural cell types. Two paralogous pairs of LIM homeodomain proteins, LIM homeobox protein 3/4 (Lhx3/Lhx4) and Islet-1/2 (Isl1/Isl2), are expressed in developing ventral motor neurons. Lhx3 and Isl1 interact within a well characterized transcriptional complex that triggers motor neuron development, but it was not known whether Lhx4 and Isl2 could participate in equivalent complexes. We have identified an Lhx3-binding domain (LBD) in Isl2 based on sequence homology with the Isl1LBD and show that both Isl2LBD and Isl1LBD can bind each of Lhx3 and Lhx4. X-ray crystal- and small-angle x-ray scattering-derived solution structures of an Lhx4·Isl2 complex exhibit many similarities with that of Lhx3·Isl1; however, structural differences supported by mutagenic studies reveal differences in the mechanisms of binding. Differences in binding have implications for the mode of exchange of protein partners in transcriptional complexes and indicate a divergence in functions of Lhx3/4 and Isl1/2. The formation of weaker Lhx·Isl complexes would likely be masked by the availability of the other Lhx·Isl complexes in postmitotic motor neurons. PMID:22025611

  1. Structure and Mutagenesis of Neural Cell Adhesion Molecule Domains Evidence for Flexibility in the Placement of Polysialic Acid Attachment Sites

    Energy Technology Data Exchange (ETDEWEB)

    Foley, Deirdre A.; Swartzentruber, Kristin G.; Lavie, Arnon; Colley, Karen J. (UICM)

    2010-11-09

    The addition of {alpha}2,8-polysialic acid to the N-glycans of the neural cell adhesion molecule, NCAM, is critical for brain development and plays roles in synaptic plasticity, learning and memory, neuronal regeneration, and the growth and invasiveness of cancer cells. Our previous work indicates that the polysialylation of two N-glycans located on the fifth immunoglobulin domain (Ig5) of NCAM requires the presence of specific sequences in the adjacent fibronectin type III repeat (FN1). To understand the relationship of these two domains, we have solved the crystal structure of the NCAM Ig5-FN1 tandem. Unexpectedly, the structure reveals that the sites of Ig5 polysialylation are on the opposite face from the FN1 residues previously found to be critical for N-glycan polysialylation, suggesting that the Ig5-FN1 domain relationship may be flexible and/or that there is flexibility in the placement of Ig5 glycosylation sites for polysialylation. To test the latter possibility, new Ig5 glycosylation sites were engineered and their polysialylation tested. We observed some flexibility in glycosylation site location for polysialylation and demonstrate that the lack of polysialylation of a glycan attached to Asn-423 may be in part related to a lack of terminal processing. The data also suggest that, although the polysialyltransferases do not require the Ig5 domain for NCAM recognition, their ability to engage with this domain is necessary for polysialylation to occur on Ig5 N-glycans.

  2. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  3. Functional and structural aging of the speech sensorimotor neural system: fMRI evidence

    Science.gov (United States)

    Tremblay, Pascale; Dick, Anthony Steven; Small, Steven L.

    2013-01-01

    The ability to perceive and produce speech undergoes important changes in late adulthood. The goal of the present study was to characterize functional and structural age-related differences in the cortical network supporting speech perception and production using magnetic resonance imaging, as well as the relationship between functional and structural age-related changes occurring in this network. We asked young and older adults to (1) observe videos of a speaker producing single words (perception), and (B) observe and repeat the words produced (production). Results show a widespread bilateral network of brain activation for Perception and Production that was uncorrelated with age. In addition, several regions did show age-related change (auditory cortex, planum temporale, superior temporal sulcus, premotor cortices, SMA-proper). Examination of the relationship between brain signal and regional and global gray matter volume and cortical thickness revealed a complex set of relationships between structure and function, with some regions showing a relationship between structure and function and not. The present results provide novel findings about the neurobiology of aging and verbal communication. PMID:23523270

  4. Prediction of protein structural features by use of artificial neural networks

    DEFF Research Database (Denmark)

    Petersen, Bent

    . There is a huge over-representation of DNA sequences when comparing the amount of experimentally verified proteins with the amount of DNA sequences. The academic and industrial research community therefore has to rely on structure predictions instead of waiting for the time consuming experimentally determined...

  5. Learning to Perceive Structure from Motion and Neural Plasticity in Patients with Alzheimer's Disease

    Science.gov (United States)

    Kim, Nam-Gyoon; Park, Jong-Hee

    2010-01-01

    Recent research has demonstrated that Alzheimer's disease (AD) affects the visual sensory pathways, producing a variety of visual deficits, including the capacity to perceive structure-from-motion (SFM). Because the sensory areas of the adult brain are known to retain a large degree of plasticity, the present study was conducted to explore whether…

  6. Bayesian inference of Earth's radial seismic structure from body-wave traveltimes using neural networks

    NARCIS (Netherlands)

    de Wit, R.W.L.; Valentine, A.P.; Trampert, J.

    2013-01-01

    How do body-wave traveltimes constrain the Earth's radial (1-D) seismic structure? Existing 1-D seismological models underpin 3-D seismic tomography and earthquake location algorithms. It is therefore crucial to assess the quality of such 1-D models, yet quantifying uncertainties in seismological

  7. Revisiting Earth's radial seismic structure using a Bayesian neural network approach

    NARCIS (Netherlands)

    de Wit, R.W.L.

    2015-01-01

    The gross features of seismic observations can be explained by relatively simple spherically symmetric (1-D) models of wave velocities, density and attenuation, which describe the Earth's average(radial) structure. 1-D earth models are often used as a reference for studies on Earth's thermo-chemical

  8. Functional and structural aging of the speech sensorimotor neural system: functional magnetic resonance imaging evidence.

    Science.gov (United States)

    Tremblay, Pascale; Dick, Anthony S; Small, Steven L

    2013-08-01

    The ability to perceive and produce speech undergoes important changes in late adulthood. The goal of the present study was to characterize functional and structural age-related differences in the cortical network that support speech perception and production, using magnetic resonance imaging, as well as the relationship between functional and structural age-related changes occurring in this network. We asked young and older adults to observe videos of a speaker producing single words (perception), and to observe and repeat the words produced (production). Results show a widespread bilateral network of brain activation for Perception and Production that was not correlated with age. In addition, several regions did show age-related change (auditory cortex, planum temporale, superior temporal sulcus, premotor cortices, SMA-proper). Examination of the relationship between brain signal and regional and global gray matter volume and cortical thickness revealed a complex set of relationships between structure and function, with some regions showing a relationship between structure and function and some not. The present results provide novel findings about the neurobiology of aging and verbal communication. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. Neural Correlates of Predictive Saccades.

    Science.gov (United States)

    Lee, Stephen M; Peltsch, Alicia; Kilmade, Maureen; Brien, Donald C; Coe, Brian C; Johnsrude, Ingrid S; Munoz, Douglas P

    2016-08-01

    Every day we generate motor responses that are timed with external cues. This phenomenon of sensorimotor synchronization has been simplified and studied extensively using finger tapping sequences that are executed in synchrony with auditory stimuli. The predictive saccade paradigm closely resembles the finger tapping task. In this paradigm, participants follow a visual target that "steps" between two fixed locations on a visual screen at predictable ISIs. Eventually, the time from target appearance to saccade initiation (i.e., saccadic RT) becomes predictive with values nearing 0 msec. Unlike the finger tapping literature, neural control of predictive behavior described within the eye movement literature has not been well established and is inconsistent, especially between neuroimaging and patient lesion studies. To resolve these discrepancies, we used fMRI to investigate the neural correlates of predictive saccades by contrasting brain areas involved with behavior generated from the predictive saccade task with behavior generated from a reactive saccade task (saccades are generated toward targets that are unpredictably timed). We observed striking differences in neural recruitment between reactive and predictive conditions: Reactive saccades recruited oculomotor structures, as predicted, whereas predictive saccades recruited brain structures that support timing in motor responses, such as the crus I of the cerebellum, and structures commonly associated with the default mode network. Therefore, our results were more consistent with those found in the finger tapping literature.

  10. The neural processing of hierarchical structure in music and speech at different timescales.

    Science.gov (United States)

    Farbood, Morwaread M; Heeger, David J; Marcus, Gary; Hasson, Uri; Lerner, Yulia

    2015-01-01

    Music, like speech, is a complex auditory signal that contains structures at multiple timescales, and as such is a potentially powerful entry point into the question of how the brain integrates complex streams of information. Using an experimental design modeled after previous studies that used scrambled versions of a spoken story (Lerner et al., 2011) and a silent movie (Hasson et al., 2008), we investigate whether listeners perceive hierarchical structure in music beyond short (~6 s) time windows and whether there is cortical overlap between music and language processing at multiple timescales. Experienced pianists were presented with an extended musical excerpt scrambled at multiple timescales-by measure, phrase, and section-while measuring brain activity with functional magnetic resonance imaging (fMRI). The reliability of evoked activity, as quantified by inter-subject correlation of the fMRI responses, was measured. We found that response reliability depended systematically on musical structure coherence, revealing a topographically organized hierarchy of processing timescales. Early auditory areas (at the bottom of the hierarchy) responded reliably in all conditions. For brain areas at the top of the hierarchy, the original (unscrambled) excerpt evoked more reliable responses than any of the scrambled excerpts, indicating that these brain areas process long-timescale musical structures, on the order of minutes. The topography of processing timescales was analogous with that reported previously for speech, but the timescale gradients for music and speech overlapped with one another only partially, suggesting that temporally analogous structures-words/measures, sentences/musical phrases, paragraph/sections-are processed separately.

  11. Embryonic neural inducing factor churchill is not a DNA-binding zinc finger protein: solution structure reveals a solvent-exposed beta-sheet and zinc binuclear cluster.

    Science.gov (United States)

    Lee, Brian M; Buck-Koehntop, Bethany A; Martinez-Yamout, Maria A; Dyson, H Jane; Wright, Peter E

    2007-08-31

    Churchill is a zinc-containing protein that is involved in neural induction during embryogenesis. At the time of its discovery, it was thought on the basis of sequence alignment to contain two zinc fingers of the C4 type. Further, binding of an N-terminal GST-Churchill fusion protein to a particular DNA sequence was demonstrated by immunoprecipitation selection assay, suggesting that Churchill may function as a transcriptional regulator by sequence-specific DNA binding. We show by NMR solution structure determination that, far from containing canonical C4 zinc fingers, the protein contains three bound zinc ions in novel coordination sites, including an unusual binuclear zinc cluster. The secondary structure of Churchill is also unusual, consisting of a highly solvent-exposed single-layer beta-sheet. Hydrogen-deuterium exchange and backbone relaxation measurements reveal that Churchill is unusually dynamic on a number of time scales, with the exception of regions surrounding the zinc coordinating sites, which serve to stabilize the otherwise unstructured N terminus and the single-layer beta-sheet. No binding of Churchill to the previously identified DNA sequence could be detected, and extensive searches using DNA sequence selection techniques could find no other DNA sequence that was bound by Churchill. Since the N-terminal amino acids of Churchill form part of the zinc-binding motif, the addition of a fusion protein at the N terminus causes loss of zinc and unfolding of Churchill. This observation most likely explains the published DNA-binding results, which would arise due to non-specific interaction of the unfolded protein in the immunoprecipitation selection assay. Since Churchill does not appear to bind DNA, we suggest that it may function in embryogenesis as a protein-interaction factor.

  12. The neural processing of hierarchical structure in music and speech at different timescales

    Directory of Open Access Journals (Sweden)

    Morwaread Mary Farbood

    2015-05-01

    Full Text Available Music, like speech, is a complex auditory signal that contains structures at multiple timescales, and as such a potentially powerful entry point into the question of how the brain integrates complex streams of information. Using an experimental design modeled after previous studies that used scrambled versions of a spoken story (Lerner, Honey, Silbert, & Hasson, 2011 and a silent movie (Hasson, Yang, Vallines, Heeger, & Rubin, 2008, we investigate whether listeners perceive hierarchical structure in music beyond short (~6 sec time windows and whether there is cortical overlap between music and language processing at multiple timescales. Experienced pianists were presented with an extended musical excerpt scrambled at multiple timescales––by measure, phrase, and section––while measuring brain activity with functional magnetic resonance imaging (fMRI. The reliability of evoked activity, as quantified by inter-subject correlation of the fMRI responses was measured. We found that response reliability depended systematically on musical structural coherence, revealing a topographically organized hierarchy of processing timescales. Early auditory areas (at the bottom of the hierarchy responded reliably in all conditions. For brain areas at the top of the hierarchy, the original (unscrambled excerpt evoked more reliable responses than any of the scrambled excerpts, indicating that these brain areas process long-timescale musical structures, on the order of minutes. The topography of processing timescales was analogous with that reported previously for speech, but the timescale gradients for music and speech overlapped with one another only partially, suggesting that temporally analogous structures––words/measures, sentences/musical phrases, paragraph/sections––are processed separately.

  13. The neural processing of hierarchical structure in music and speech at different timescales

    Science.gov (United States)

    Farbood, Morwaread M.; Heeger, David J.; Marcus, Gary; Hasson, Uri; Lerner, Yulia

    2015-01-01

    Music, like speech, is a complex auditory signal that contains structures at multiple timescales, and as such is a potentially powerful entry point into the question of how the brain integrates complex streams of information. Using an experimental design modeled after previous studies that used scrambled versions of a spoken story (Lerner et al., 2011) and a silent movie (Hasson et al., 2008), we investigate whether listeners perceive hierarchical structure in music beyond short (~6 s) time windows and whether there is cortical overlap between music and language processing at multiple timescales. Experienced pianists were presented with an extended musical excerpt scrambled at multiple timescales—by measure, phrase, and section—while measuring brain activity with functional magnetic resonance imaging (fMRI). The reliability of evoked activity, as quantified by inter-subject correlation of the fMRI responses, was measured. We found that response reliability depended systematically on musical structure coherence, revealing a topographically organized hierarchy of processing timescales. Early auditory areas (at the bottom of the hierarchy) responded reliably in all conditions. For brain areas at the top of the hierarchy, the original (unscrambled) excerpt evoked more reliable responses than any of the scrambled excerpts, indicating that these brain areas process long-timescale musical structures, on the order of minutes. The topography of processing timescales was analogous with that reported previously for speech, but the timescale gradients for music and speech overlapped with one another only partially, suggesting that temporally analogous structures—words/measures, sentences/musical phrases, paragraph/sections—are processed separately. PMID:26029037

  14. Age-Related Cognitive Impairments in Mice with a Conditional Ablation of the Neural Cell Adhesion Molecule

    Science.gov (United States)

    Bisaz, Reto; Boadas-Vaello, Pere; Genoux, David; Sandi, Carmen

    2013-01-01

    Most of the mechanisms involved in neural plasticity support cognition, and aging has a considerable effect on some of these processes. The neural cell adhesion molecule (NCAM) of the immunoglobulin superfamily plays a pivotal role in structural and functional plasticity and is required to modulate cognitive and emotional behaviors. However,…

  15. Impaired Neural Structure and Function Contributing to Autonomic Symptoms in Congenital Central Hypoventilation Syndrome

    Directory of Open Access Journals (Sweden)

    Ronald M Harper

    2015-10-01

    Full Text Available Congenital central hypoventilation syndrome (CCHS patients show major autonomic alterations in addition to their better-known breathing deficiencies. The processes underlying CCHS, mutations in the PHOX2B gene, target autonomic neuronal development, with frame shift extent contributing to symptom severity. Many autonomic characteristics, such as impaired pupillary constriction and poor temperature regulation, reflect parasympathetic alterations, and can include disturbed alimentary processes, with malabsorption and intestinal motility dyscontrol. The sympathetic nervous system changes can exert life-threatening outcomes, with dysregulation of sympathetic outflow leading to high blood pressure, time-altered and dampened heart rate and breathing responses to challenges, cardiac arrhythmia, profuse sweating, and poor fluid regulation. The central mechanisms contributing to failed autonomic processes are readily apparent from structural and functional magnetic resonance imaging studies, which reveal substantial cortical thinning, tissue injury, and disrupted functional responses in hypothalamic, hippocampal, posterior thalamic, and basal ganglia sites and their descending projections, as well as insular, cingulate, and medial frontal cortices, which influence subcortical autonomic structures. Midbrain structures are also compromised, including the raphe system and its projections to cerebellar and medullary sites, the locus coeruleus, and medullary reflex integrating sites, including the dorsal and ventrolateral medullary nuclei. The damage to rostral autonomic sites overlaps metabolic, affective and cognitive regulatory regions, leading to hormonal disruption, anxiety, depression, behavioral control, and sudden death concerns. The injuries suggest that interventions for mitigating hypoxic exposure and nutrient loss may provide cellular protection, in the same fashion as interventions in other conditions with similar malabsorption, fluid turnover

  16. Neural responses to nostalgia-evoking music modeled by elements of dynamic musical structure and individual differences in affective traits.

    Science.gov (United States)

    Barrett, Frederick S; Janata, Petr

    2016-10-01

    Nostalgia is an emotion that is most commonly associated with personally and socially relevant memories. It is primarily positive in valence and is readily evoked by music. It is also an idiosyncratic experience that varies between individuals based on affective traits. We identified frontal, limbic, paralimbic, and midbrain brain regions in which the strength of the relationship between ratings of nostalgia evoked by music and blood-oxygen-level-dependent (BOLD) signal was predicted by affective personality measures (nostalgia proneness and the sadness scale of the Affective Neuroscience Personality Scales) that are known to modulate the strength of nostalgic experiences. We also identified brain areas including the inferior frontal gyrus, substantia nigra, cerebellum, and insula in which time-varying BOLD activity correlated more strongly with the time-varying tonal structure of nostalgia-evoking music than with music that evoked no or little nostalgia. These findings illustrate one way in which the reward and emotion regulation networks of the brain are recruited during the experiencing of complex emotional experiences triggered by music. These findings also highlight the importance of considering individual differences when examining the neural responses to strong and idiosyncratic emotional experiences. Finally, these findings provide a further demonstration of the use of time-varying stimulus-specific information in the investigation of music-evoked experiences. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Neural structure and social dysfunction in individuals at clinical high risk for psychosis.

    Science.gov (United States)

    Lincoln, Sarah Hope; Hooker, Christine I'Lee

    2014-12-30

    Individuals at a clinical high risk (CHR) for psychosis have gray matter volume (GMV) abnormalities that are similar to, though less severe than, those in individuals with schizophrenia. Less GMV in schizophrenia is related to worse social cognition and social functioning, but the relationship between GMV and social functioning in CHR individuals has yet to be investigated. The aim of this study was to (1) investigate differences in GMV between healthy controls (HC) and CHR individuals, and (2) evaluate the relationship between GMV and social functioning in these two groups. Participants comprised 22 CHR and 21 HC individuals who completed a structural magnetic resonance imaging (MRI) scan as well as self-reported and interviewer-rated measures of social functioning. Processing and analysis of structural images were completed using voxel based morphometry (VBM). Results showed that the CHR group had less GMV in the left postcentral gyrus, bilateral parahippocampual gyri, and left anterior cingulate cortex. Reduced GMV in the postcentral gyrus and the anterior cingulate was related to self-reported social impairment across the whole group. This study has implications for the neurobiological basis of social dysfunction present before the onset of psychosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Immediate Neural Plasticity Involving Reaction Time in a Saccadic Eye Movement Task is Intact in Children With Fetal Alcohol Spectrum Disorder.

    Science.gov (United States)

    Paolozza, Angelina; Munoz, Douglas P; Brien, Donald; Reynolds, James N

    2016-11-01

    Saccades are rapid eye movements that bring an image of interest onto the retina. Previous research has found that in healthy individuals performing eye movement tasks, the location of a previous visual target can influence performance of the saccade on the next trial. This rapid behavioral adaptation represents a form of immediate neural plasticity within the saccadic circuitry. Our studies have shown that children with fetal alcohol spectrum disorder (FASD) are impaired on multiple saccade measures. We therefore investigated these previous trial effects in typically developing children and children with FASD to measure sensory neural plasticity and how these effects vary with age and pathology. Both typically developing control children (n = 102; mean age = 10.54 ± 3.25; 48 males) and children with FASD (n = 66; mean age = 11.85 ± 3.42; 35 males) were recruited from 5 sites across Canada. Each child performed a visually guided saccade task. Reaction time and saccade amplitude were analyzed and then assessed based on the previous trial. There was a robust previous trial effect for both reaction time and amplitude, with both the control and FASD groups displaying faster reaction times and smaller saccades during alternation trials (visual target presented on the opposite side to the previous trial). Children with FASD exhibited smaller overall mean amplitude and smaller amplitude selectively on alternation trials compared with controls. The effect of the previous trial on reaction time and amplitude did not differ across childhood and adolescent development. Children with FASD did not display any significant reaction time differences, despite exhibiting numerous deficits in motor and higher level cognitive control over saccades in other studies. These results suggest that this form of immediate neural plasticity in response to sensory information before saccade initiation remains intact in children with FASD. In contrast, the previous trial effect on

  19. Structures of the first representatives of Pfam family PF06938 (DUF1285) reveal a new fold with repeated structural motifs and possible involvement in signal transduction.

    Science.gov (United States)

    Han, Gye Won; Bakolitsa, Constantina; Miller, Mitchell D; Kumar, Abhinav; Carlton, Dennis; Najmanovich, Rafael J; Abdubek, Polat; Astakhova, Tamara; Axelrod, Herbert L; Chen, Connie; Chiu, Hsiu Ju; Clayton, Thomas; Das, Debanu; Deller, Marc C; Duan, Lian; Ernst, Dustin; Feuerhelm, Julie; Grant, Joanna C; Grzechnik, Anna; Jaroszewski, Lukasz; Jin, Kevin K; Johnson, Hope A; Klock, Heath E; Knuth, Mark W; Kozbial, Piotr; Krishna, S Sri; Marciano, David; McMullan, Daniel; Morse, Andrew T; Nigoghossian, Edward; Okach, Linda; Reyes, Ron; Rife, Christopher L; Sefcovic, Natasha; Tien, Henry J; Trame, Christine B; van den Bedem, Henry; Weekes, Dana; Xu, Qingping; Hodgson, Keith O; Wooley, John; Elsliger, Marc André; Deacon, Ashley M; Godzik, Adam; Lesley, Scott A; Wilson, Ian A

    2010-10-01

    The crystal structures of SPO0140 and Sbal_2486 were determined using the semiautomated high-throughput pipeline of the Joint Center for Structural Genomics (JCSG) as part of the NIGMS Protein Structure Initiative (PSI). The structures revealed a conserved core with domain duplication and a superficial similarity of the C-terminal domain to pleckstrin homology-like folds. The conservation of the domain interface indicates a potential binding site that is likely to involve a nucleotide-based ligand, with genome-context and gene-fusion analyses additionally supporting a role for this family in signal transduction, possibly during oxidative stress.

  20. A structured PBL tutorial involving small teams for teaching the human nervous system.

    Science.gov (United States)

    Cardozo, David Lopes; Raymond, Laurie; White, Benjamin

    2012-01-01

    The Human Nervous System and Behavior course at Harvard Medical School (HMS) incorporates a hybrid model of problem-based learning. Student preparation for and participation in the tutorial seemed to be insufficient. We sought to increase student engagement in tutorial by creating a structured approach, which included assigned roles for students, weekly testing, formal cornerstone presentations, and a weekly self-assessment exercise. We wished to determine the students' and tutors' satisfaction with this structured approach as compared with the more traditional tutorial experienced in other courses at HMS. For the first 4 years of the course, students (n = 160) were surveyed concerning their impressions of the quality of the structured approach in comparison with the traditional tutorial. In addition, they were surveyed concerning the cornerstone presentations and the self-assessment exercise. Tutors (n = 10) who had taught in both the traditional and structured tutorial formats were surveyed about their impressions of student performance as well as their own enjoyment in the structured format. Students and tutors found the structured approach superior to the previous method. Both groups noted increased student preparation, participation, and accountability. Tutors preferred teaching in the structured format. The structured approach increased student accountability, preparation, and participation. Students and tutors preferred this tutorial experience over the previous approach.

  1. Neuroadaptive changes associated with smoking: structural and functional neural changes in nicotine dependence.

    Science.gov (United States)

    Martin-Soelch, Chantal

    2013-02-15

    Tobacco smoking is the most frequent form of substance abuse. We provide a review of the neuroadaptive changes evidenced in human smokers with regard to the current neurobiological models of addiction. Addiction is thought to result from an interplay between positive and negative reinforcement. Positive reinforcing effects of the drugs are mediated by striatal dopamine release, while negative reinforcement involves the relief of withdrawal symptoms and neurobiological stress systems. In addition, drug-related stimuli are attributed with excessive motivational value and are thought to exert a control on the behavior. This mechanism plays a central role in drug maintenance and relapse. Further neuroadaptive changes associated with chronic use of the drug consist of reduced responses to natural rewards and in the activation of an antireward system, related to neurobiological stress systems. Reduced inhibitory cognitive control is believed to support the development and the maintenance of addiction. The findings observed in human nicotine dependence are generally in line with these models. The current state of the research indicates specific neuroadaptive changes associated with nicotine addiction that need to be further elucidated with regard to their role in the treatment of nicotine dependence.

  2. Neuroadaptive Changes Associated with Smoking: Structural and Functional Neural Changes in Nicotine Dependence

    Directory of Open Access Journals (Sweden)

    Chantal Martin-Soelch

    2013-02-01

    Full Text Available Tobacco smoking is the most frequent form of substance abuse. We provide a review of the neuroadaptive changes evidenced in human smokers with regard to the current neurobiological models of addiction. Addiction is thought to result from an interplay between positive and negative reinforcement. Positive reinforcing effects of the drugs are mediated by striatal dopamine release, while negative reinforcement involves the relief of withdrawal symptoms and neurobiological stress systems. In addition, drug-related stimuli are attributed with excessive motivational value and are thought to exert a control on the behavior. This mechanism plays a central role in drug maintenance and relapse. Further neuroadaptive changes associated with chronic use of the drug consist of reduced responses to natural rewards and in the activation of an antireward system, related to neurobiological stress systems. Reduced inhibitory cognitive control is believed to support the development and the maintenance of addiction. The findings observed in human nicotine dependence are generally in line with these models. The current state of the research indicates specific neuroadaptive changes associated with nicotine addiction that need to be further elucidated with regard to their role in the treatment of nicotine dependence.

  3. The effect of pulsed electric fields on the electrotactic migration of human neural progenitor cells through the involvement of intracellular calcium signaling.

    Science.gov (United States)

    Hayashi, Hisamitsu; Edin, Fredrik; Li, Hao; Liu, Wei; Rask-Andersen, Helge

    2016-12-01

    Endogenous electric fields (EFs) are required for the physiological control of the central nervous system development. Application of the direct current EFs to neural stem cells has been studied for the possibility of stem cell transplantation as one of the therapies for brain injury. EFs generated within the nervous system are often associated with action potentials and synaptic activity, apparently resulting in a pulsed current in nature. The aim of this study is to investigate the effect of pulsed EF, which can reduce the cytotoxicity, on the migration of human neural progenitor cells (hNPCs). We applied the mono-directional pulsed EF with a strength of 250mV/mm to hNPCs for 6h. The migration distance of the hNPCs exposed to pulsed EF was significantly greater compared with the control not exposed to the EF. Pulsed EFs, however, had less of an effect on the migration of the differentiated hNPCs. There was no significant change in the survival of hNPCs after exposure to the pulsed EF. To investigate the role of Ca 2+ signaling in electrotactic migration of hNPCs, pharmacological inhibition of Ca 2+ channels in the EF-exposed cells revealed that the electrotactic migration of hNPCs exposed to Ca 2+ channel blockers was significantly lower compared to the control group. The findings suggest that the pulsed EF induced migration of hNPCs is partly influenced by intracellular Ca 2+ signaling. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Neural progenitor cell proliferation in the hypothalamus is involved in acquired heat tolerance in long-term heat-acclimated rats.

    Science.gov (United States)

    Matsuzaki, Kentaro; Katakura, Masanori; Sugimoto, Naotoshi; Hara, Toshiko; Hashimoto, Michio; Shido, Osamu

    2017-01-01

    Constant exposure to moderate heat facilitates progenitor cell proliferation and neuronal differentiation in the hypothalamus of heat-acclimated (HA) rats. In this study, we investigated neural phenotype and responsiveness to heat in HA rats' hypothalamic newborn cells. Additionally, the effect of hypothalamic neurogenesis on heat acclimation in rats was evaluated. Male Wistar rats (5 weeks old) were housed at an ambient temperature (Ta) of 32°C for 6 days (STHA) or 40 days (LTHA), while control (CN) rats were kept at a Ta of 24°C for 6 days (STCN) or 40 days (LTCN). Bromodeoxyuridine (BrdU) was intraperitoneally injected daily for five consecutive days (50 mg/kg/day) after commencing heat exposure. The number of hypothalamic BrdU-immunopositive (BrdU+) cells in STHA and LTHA rats was determined immunohistochemically in brain samples and found to be significantly greater than those in respective CN groups. In LTHA rats, approximately 32.6% of BrdU+ cells in the preoptic area (POA) of the anterior hypothalamus were stained by GAD67, a GABAergic neuron marker, and 15.2% of BrdU+ cells were stained by the glutamate transporter, a glutamatergic neuron marker. In addition, 63.2% of BrdU+ cells in the POA were immunolabeled with c-Fos. Intracerebral administration of the mitosis inhibitor, cytosine arabinoside (AraC), interfered with the proliferation of neural progenitor cells and acquired heat tolerance in LTHA rats, whereas the selected ambient temperature was not changed. These results demonstrate that heat exposure generates heat responsive neurons in the POA, suggesting a pivotal role in autonomic thermoregulation in long-term heat-acclimated rats.

  5. Common neural structures activated by epidural and transcutaneous lumbar spinal cord stimulation: Elicitation of posterior root-muscle reflexes.

    Science.gov (United States)

    Hofstoetter, Ursula S; Freundl, Brigitta; Binder, Heinrich; Minassian, Karen

    2018-01-01

    Epidural electrical stimulation of the lumbar spinal cord is currently regaining momentum as a neuromodulation intervention in spinal cord injury (SCI) to modify dysregulated sensorimotor functions and augment residual motor capacity. There is ample evidence that it engages spinal circuits through the electrical stimulation of large-to-medium diameter afferent fibers within lumbar and upper sacral posterior roots. Recent pilot studies suggested that the surface electrode-based method of transcutaneous spinal cord stimulation (SCS) may produce similar neuromodulatory effects as caused by epidural SCS. Neurophysiological and computer modeling studies proposed that this noninvasive technique stimulates posterior-root fibers as well, likely activating similar input structures to the spinal cord as epidural stimulation. Here, we add a yet missing piece of evidence substantiating this assumption. We conducted in-depth analyses and direct comparisons of the electromyographic (EMG) characteristics of short-latency responses in multiple leg muscles to both stimulation techniques derived from ten individuals with SCI each. Post-activation depression of responses evoked by paired pulses applied either epidurally or transcutaneously confirmed the reflex nature of the responses. The muscle responses to both techniques had the same latencies, EMG peak-to-peak amplitudes, and waveforms, except for smaller responses with shorter onset latencies in the triceps surae muscle group and shorter offsets of the responses in the biceps femoris muscle during epidural stimulation. Responses obtained in three subjects tested with both methods at different time points had near-identical waveforms per muscle group as well as same onset latencies. The present results strongly corroborate the activation of common neural input structures to the lumbar spinal cord-predominantly primary afferent fibers within multiple posterior roots-by both techniques and add to unraveling the basic mechanisms

  6. Modified feed-forward neural network structures and combined-function-derivative approximations incorporating exchange symmetry for potential energy surface fitting.

    Science.gov (United States)

    Nguyen, Hieu T T; Le, Hung M

    2012-05-10

    The classical interchange (permutation) of atoms of similar identity does not have an effect on the overall potential energy. In this study, we present feed-forward neural network structures that provide permutation symmetry to the potential energy surfaces of molecules. The new feed-forward neural network structures are employed to fit the potential energy surfaces for two illustrative molecules, which are H(2)O and ClOOCl. Modifications are made to describe the symmetric interchange (permutation) of atoms of similar identity (or mathematically, the permutation of symmetric input parameters). The combined-function-derivative approximation algorithm (J. Chem. Phys. 2009, 130, 134101) is also implemented to fit the neural-network potential energy surfaces accurately. The combination of our symmetric neural networks and the function-derivative fitting effectively produces PES fits using fewer numbers of training data points. For H(2)O, only 282 configurations are employed as the training set; the testing root-mean-squared and mean-absolute energy errors are respectively reported as 0.0103 eV (0.236 kcal/mol) and 0.0078 eV (0.179 kcal/mol). In the ClOOCl case, 1693 configurations are required to construct the training set; the root-mean-squared and mean-absolute energy errors for the ClOOCl testing set are 0.0409 eV (0.943 kcal/mol) and 0.0269 eV (0.620 kcal/mol), respectively. Overall, we find good agreements between ab initio and NN prediction in term of energy and gradient errors, and conclude that the new feed-forward neural-network models advantageously describe the molecules with excellent accuracy.

  7. Error and attack tolerance of synchronization in Hindmarsh–Rose neural networks with community structure

    Energy Technology Data Exchange (ETDEWEB)

    Li, Chun-Hsien, E-mail: chli@nknucc.nknu.edu.tw [Department of Mathematics, National Kaohsiung Normal University, Yanchao District, Kaohsiung City 82444, Taiwan (China); Yang, Suh-Yuh, E-mail: syyang@math.ncu.edu.tw [Department of Mathematics, National Central University, Jhongli City, Taoyuan County 32001, Taiwan (China)

    2014-03-01

    Synchronization is one of the most important features observed in large-scale complex networks of interacting dynamical systems. As is well known, there is a close relation between the network topology and the network synchronizability. Using the coupled Hindmarsh–Rose neurons with community structure as a model network, in this paper we explore how failures of the nodes due to random errors or intentional attacks affect the synchronizability of community networks. The intentional attacks are realized by removing a fraction of the nodes with high values in some centrality measure such as the centralities of degree, eigenvector, betweenness and closeness. According to the master stability function method, we employ the algebraic connectivity of the considered community network as an indicator to examine the network synchronizability. Numerical evidences show that the node failure strategy based on the betweenness centrality has the most influence on the synchronizability of community networks. With this node failure strategy for a given network with a fixed number of communities, we find that the larger the degree of communities, the worse the network synchronizability; however, for a given network with a fixed degree of communities, we observe that the more the number of communities, the better the network synchronizability.

  8. Error and attack tolerance of synchronization in Hindmarsh-Rose neural networks with community structure

    Science.gov (United States)

    Li, Chun-Hsien; Yang, Suh-Yuh

    2014-03-01

    Synchronization is one of the most important features observed in large-scale complex networks of interacting dynamical systems. As is well known, there is a close relation between the network topology and the network synchronizability. Using the coupled Hindmarsh-Rose neurons with community structure as a model network, in this paper we explore how failures of the nodes due to random errors or intentional attacks affect the synchronizability of community networks. The intentional attacks are realized by removing a fraction of the nodes with high values in some centrality measure such as the centralities of degree, eigenvector, betweenness and closeness. According to the master stability function method, we employ the algebraic connectivity of the considered community network as an indicator to examine the network synchronizability. Numerical evidences show that the node failure strategy based on the betweenness centrality has the most influence on the synchronizability of community networks. With this node failure strategy for a given network with a fixed number of communities, we find that the larger the degree of communities, the worse the network synchronizability; however, for a given network with a fixed degree of communities, we observe that the more the number of communities, the better the network synchronizability.

  9. Effect of repeated contact on adhesion measurements involving polydimethylsiloxane structural material

    Energy Technology Data Exchange (ETDEWEB)

    Kroner, E; Arzt, E [INM-Leibniz Institute for New Materials, Campus D2 2, 66125 Saarbruecken (Germany); Maboudian, R, E-mail: elmar.kroner@inm-gmbh.de [Department of Chem. Eng., 201 Gilman Hall, University of California, Berkeley, CA 94720-1462 (United States)

    2009-09-15

    During the last few years several research groups have focused on the fabrication of artificial gecko inspired adhesives. For mimicking these structures, different polymers are used as structure material, such as polydimethylsiloxanes (PDMS), polyurethanes (PU), and polypropylene (PP). While these polymers can be structured easily and used for artificial adhesion systems, the effects of repeated adhesion testing have never been investigated closely. In this paper we report on the effect of repeated adhesion measurements on the commercially available poly(dimethylsiloxane) polymer kit Sylgard 184 (Dow Corning). We show that the adhesion force decreases as a function of contact cycles. The rate of change and the final value of adhesion are found to depend on the details of the PDMS synthesis and structuring.

  10. Conserved structural domains in FoxD4L1, a neural forkhead box transcription factor, are required to repress or activate target genes.

    Directory of Open Access Journals (Sweden)

    Steven L Klein

    Full Text Available FoxD4L1 is a forkhead transcription factor that expands the neural ectoderm by down-regulating genes that promote the onset of neural differentiation and up-regulating genes that maintain proliferative neural precursors in an immature state. We previously demonstrated that binding of Grg4 to an Eh-1 motif enhances the ability of FoxD4L1 to down-regulate target neural genes but does not account for all of its repressive activity. Herein we analyzed the protein sequence for additional interaction motifs and secondary structure. Eight conserved motifs were identified in the C-terminal region of fish and frog proteins. Extending the analysis to mammals identified a high scoring motif downstream of the Eh-1 domain that contains a tryptophan residue implicated in protein-protein interactions. In addition, secondary structure prediction programs predicted an α-helical structure overlapping with amphibian-specific Motif 6 in Xenopus, and similarly located α-helical structures in other vertebrate FoxD proteins. We tested functionality of this site by inducing a glutamine-to-proline substitution expected to break the predicted α-helical structure; this significantly reduced FoxD4L1's ability to repress zic3 and irx1. Because this mutation does not interfere with Grg4 binding, these results demonstrate that at least two regions, the Eh-1 motif and a more C-terminal predicted α-helical/Motif 6 site, additively contribute to repression. In the N-terminal region we previously identified a 14 amino acid motif that is required for the up-regulation of target genes. Secondary structure prediction programs predicted a short β-strand separating two acidic domains. Mutant constructs show that the β-strand itself is not required for transcriptional activation. Instead, activation depends upon a glycine residue that is predicted to provide sufficient flexibility to bring the two acidic domains into close proximity. These results identify conserved predicted

  11. Neural correlates of viewing paintings

    DEFF Research Database (Denmark)

    Vartanian, Oshin; Skov, Martin

    2014-01-01

    Many studies involving functional magnetic resonance imaging (fMRI) have exposed participants to paintings under varying task demands. To isolate neural systems that are activated reliably across fMRI studies in response to viewing paintings regardless of variation in task demands, a quantitative...... meta-analysis of fifteen experiments using the activation likelihood estimation (ALE) method was conducted. As predicted, viewing paintings was correlated with activation in a distributed system including the occipital lobes, temporal lobe structures in the ventral stream involved in object (fusiform...... gyrus) and scene (parahippocampal gyrus) perception, and the anterior insula-a key structure in experience of emotion. In addition, we also observed activation in the posterior cingulate cortex bilaterally-part of the brain's default network. These results suggest that viewing paintings engages not only...

  12. Pea border cell maturation and release involve complex cell wall structural dynamics

    DEFF Research Database (Denmark)

    Mravec, Jozef; Guo, Xiaoyuan; Hansen, Aleksander Riise

    2017-01-01

    of hydrolytic activities, transmission electron microscopy (TEM) and immunolocalization of cell wall components. Using this integrated glycobiology approach, we identified multiple novel modes of cell wall structural and compositional rearrangement during root cap growth and the release of border cells. Our...

  13. Structure of a Bacterial ABC Transporter Involved in the Import of an Acidic Polysaccharide Alginate.

    Science.gov (United States)

    Maruyama, Yukie; Itoh, Takafumi; Kaneko, Ai; Nishitani, Yu; Mikami, Bunzo; Hashimoto, Wataru; Murata, Kousaku

    2015-09-01

    The acidic polysaccharide alginate represents a promising marine biomass for the microbial production of biofuels, although the molecular and structural characteristics of alginate transporters remain to be clarified. In Sphingomonas sp. A1, the ATP-binding cassette transporter AlgM1M2SS is responsible for the import of alginate across the cytoplasmic membrane. Here, we present the substrate-transport characteristics and quaternary structure of AlgM1M2SS. The addition of poly- or oligoalginate enhanced the ATPase activity of reconstituted AlgM1M2SS coupled with one of the periplasmic solute-binding proteins, AlgQ1 or AlgQ2. External fluorescence-labeled oligoalginates were specifically imported into AlgM1M2SS-containing proteoliposomes in the presence of AlgQ2, ATP, and Mg(2+). The crystal structure of AlgQ2-bound AlgM1M2SS adopts an inward-facing conformation. The interaction between AlgQ2 and AlgM1M2SS induces the formation of an alginate-binding tunnel-like structure accessible to the solvent. The translocation route inside the transmembrane domains contains charged residues suitable for the import of acidic saccharides. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Paths of water entry and structures involved in the breaking of seed dormancy of Lupinus.

    Science.gov (United States)

    Robles-Díaz, Erika; Flores, Joel; Yáñez-Espinosa, Laura

    2016-03-15

    Physical dormancy is the water impermeability of the seed coat caused by one or more palisade cell layer(s) called macrosclereids. The specialised structure for water entry sites is the water gap, which serves as a detector of environmental cues for germination. In Fabaceae, the water gap is the lens, although another seed structure for water entry could exist. In this study, we identified the initial site of water entry, observed the hydration of a cushion-like structure near the radicle, described the anatomy of the water gap, and analysed the association of anatomical seed traits with the initial site of water entry and the imbibition velocity of six species of Lupinus from the state of Jalisco, Mexico. Dye tracking with a toluidine blue solution was used to identify the initial site of water entry. The anatomical description was performed using conventional microtechnique and a light microscope. The entry of the toluidine solution into seeds of L. montanus was observed after 6h, followed by L. exaltatus and L. mexicanus after 18h and L. elegans, L. reflexus and L. rotundiflorus after 48h. The site of water entry was the lens in L. elegans, L. exaltatus, L. reflexus and L. rotundiflorus and the micropyle in L. mexicanus and L. montanus. The cushion-like structure was responsible for water accumulation in embryo imbibition. Significant differences among anatomical seed traits such as thickness in the hilar region, the counter-palisade layer, cushion-like structure, epidermis, hypodermis, and innermost parenchyma layer were found among the species. Copyright © 2016 Elsevier GmbH. All rights reserved.

  15. The Crystal Structure of CREG, a secreted Glycoprotein Involved in Cellular Growth and Differentiation

    Energy Technology Data Exchange (ETDEWEB)

    Sacher,M.; Di Bacco, A.; Lunin, V.; Ye, Z.; Wagner, J.; Gill, G.; Cygler, M.

    2005-01-01

    The cellular repressor of E1A-stimulated genes (CREG) is a secreted glycoprotein that inhibits proliferation and enhances differentiation of human embryonal carcinoma cells. CREG binds to the cation-independent mannose 6-phosphate (M6P)/insulin-like growth factor II (IGF2) receptor (IGF2R) (M6P/IGF2R), and this receptor has been shown to be required for CREG-induced growth suppression. To better understand CREG function in cellular growth and differentiation, we solved the 3D crystal structure of this protein to 1.9-Angstrom resolution. CREG forms a tight homodimeric complex, and CREG monomers display a {beta}-barrel fold. The three potential glycosylation sites on CREG map to a confined patch opposite the dimer interface. Thus, dimerization of glycosylated CREG likely presents a bivalent ligand for the M6P/IGF2R. Closely related structural homologs of CREG are FMN-binding split-barrel fold proteins that bind flavin mononucleotide. Our structure shows that the putative flavin mononucleotide-binding pocket in CREG is sterically blocked by a loop and several key bulky residues. A mutant of CREG lacking a part of this loop maintained overall structure and dimerization, as well as M6P/IGF2R binding, but lost the growth suppression activity of WT CREG. Thus, analysis of a structure-based mutant of CREG revealed that binding to M6P/IGF2R, while necessary, is not sufficient for CREG-induced growth suppression. These findings indicate that CREG utilizes a known fold.

  16. Symmetrical retrograde actin flow in the actin fusion structure is involved in osteoclast fusion

    Directory of Open Access Journals (Sweden)

    Jiro Takito

    2017-07-01

    Full Text Available The aim of this study was to elucidate the role of the zipper-like structure (ZLS, a podosome-related structure that transiently appears at the cell contact zone, in osteoclast fusion. Live-cell imaging of osteoclasts derived from RAW264.7 cells transfected with EGFP-actin revealed consistent symmetrical retrograde actin flow in the ZLS, but not in the podosome cluster, the podosome ring or the podosome belt. Confocal imaging showed that the distributions of F-actin, vinculin, paxillin and zyxin in the ZLS were different from those in the podosome belt. Thick actin filament bundles running outside the ZLS appeared to recruit non-muscle myosin IIA. The F-actin-rich domain of the ZLS contained actin-related protein 2/3 complex (Arp2/3. Inhibition of Arp2/3 activity disorganized the ZLS, disrupted actin flow, deteriorated cell-cell adhesion and inhibited osteoclast hypermultinucleation. In contrast, ML-7, an inhibitor of myosin light chain kinase, had little effect on the structure of ZLS and promoted osteoclast hypermultinucleation. These results reveal a link between actin flow in the ZLS and osteoclast fusion. Osteoclast fusion was promoted by branched actin elongation and negatively regulated by actomyosin contraction.

  17. Crystal Structure of a Phenol-coupling P450 Monooxygenase Involved in Teicoplanin Biosynthesis

    Science.gov (United States)

    Li, Zhi; Rupasinghe, Sanjeewa G.; Schuler, Mary A.; Nair, Satish K.

    2011-01-01

    The lipoglycopeptide antibiotic teicoplanin has proven efficacy against gram-positive pathogens. Teicoplanin is distinguished from the vancomycin-type glycopeptide antibiotics, by the presence of an additional cross-link between the aromatic amino acids 1 and 3 that is catalyzed by the cytochrome P450 monooxygenase Orf6* (CYP165D3). As a goal towards understanding the mechanism of this phenol-coupling reaction, we have characterized recombinant Orf6* and determined its crystal structure to 2.2 Å resolution. Although the structure of Orf6* reveals the core fold common to other P450 monooxygenases, there are subtle differences in the disposition of secondary structure elements near the active site cavity necessary to accommodate its complex heptapeptide substrate. Specifically, the orientation of the F and G helices in Orf6* results in a more closed active site than found in the vancomycin oxidative enzymes OxyB and OxyC. In addition, Met226 in the I helix replaces the more typical Gly/Ala residue that is positioned above the heme porphyrin ring, where it forms a hydrogen bond with a heme iron-bound water molecule. Sequence comparisons with other phenol-coupling P450 monooxygenases suggest that Met226 plays a role in determining the substrate regiospecificity of Orf6*. These features provide further insights into the mechanism of the cross-linking mechanisms that occur during glycopeptide antibiotics biosynthesis. PMID:21445994

  18. Crystal structure of a phenol-coupling P450 monooxygenase involved in teicoplanin biosynthesis

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zhi; Rupasinghe, Sanjeewa G.; Schuler, Mary A.; Nair, Satish K. (UIUC)

    2012-02-08

    The lipoglycopeptide antibiotic teicoplanin has proven efficacy against gram-positive pathogens. Teicoplanin is distinguished from the vancomycin-type glycopeptide antibiotics, by the presence of an additional cross-link between the aromatic amino acids 1 and 3 that is catalyzed by the cytochrome P450 monooxygenase Orf6* (CYP165D3). As a goal towards understanding the mechanism of this phenol-coupling reaction, we have characterized recombinant Orf6* and determined its crystal structure to 2.2-{angstrom} resolution. Although the structure of Orf6* reveals the core fold common to other P450 monooxygenases, there are subtle differences in the disposition of secondary structure elements near the active site cavity necessary to accommodate its complex heptapeptide substrate. Specifically, the orientation of the F and G helices in Orf6* results in a more closed active site than found in the vancomycin oxidative enzymes OxyB and OxyC. In addition, Met226 in the I helix replaces the more typical Gly/Ala residue that is positioned above the heme porphyrin ring, where it forms a hydrogen bond with a heme iron-bound water molecule. Sequence comparisons with other phenol-coupling P450 monooxygenases suggest that Met226 plays a role in determining the substrate regiospecificity of Orf6*. These features provide further insights into the mechanism of the cross-linking mechanisms that occur during glycopeptide antibiotics biosynthesis.

  19. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  20. Visual motion imagery neurofeedback based on the hMT+/V5 complex: evidence for a feedback-specific neural circuit involving neocortical and cerebellar regions

    Science.gov (United States)

    Banca, Paula; Sousa, Teresa; Catarina Duarte, Isabel; Castelo-Branco, Miguel

    2015-12-01

    Objective. Current approaches in neurofeedback/brain-computer interface research often focus on identifying, on a subject-by-subject basis, the neural regions that are best suited for self-driven modulation. It is known that the hMT+/V5 complex, an early visual cortical region, is recruited during explicit and implicit motion imagery, in addition to real motion perception. This study tests the feasibility of training healthy volunteers to regulate the level of activation in their hMT+/V5 complex using real-time fMRI neurofeedback and visual motion imagery strategies. Approach. We functionally localized the hMT+/V5 complex to further use as a target region for neurofeedback. An uniform strategy based on motion imagery was used to guide subjects to neuromodulate hMT+/V5. Main results. We found that 15/20 participants achieved successful neurofeedback. This modulation led to the recruitment of a specific network as further assessed by psychophysiological interaction analysis. This specific circuit, including hMT+/V5, putative V6 and medial cerebellum was activated for successful neurofeedback runs. The putamen and anterior insula were recruited for both successful and non-successful runs. Significance. Our findings indicate that hMT+/V5 is a region that can be modulated by focused imagery and that a specific cortico-cerebellar circuit is recruited during visual motion imagery leading to successful neurofeedback. These findings contribute to the debate on the relative potential of extrinsic (sensory) versus intrinsic (default-mode) brain regions in the clinical application of neurofeedback paradigms. This novel circuit might be a good target for future neurofeedback approaches that aim, for example, the training of focused attention in disorders such as ADHD.

  1. Magnetisation reversal in cylindrical nickel nanobars involving magnetic vortex structure: A micromagnetic study

    Energy Technology Data Exchange (ETDEWEB)

    Barpanda, Prabeer, E-mail: prabeer.barpanda@u-picardie.f [Laboratoire de Reactivite et Chimie des Solides, Universite de Picardie Jules Verne, 33 rue Saint Leu, Amiens Cedex 80039 (France); Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, B3H 3J5 (Canada)

    2011-03-15

    A three-dimensional, Fast-Fourier-Transformed (3D-FFT) micromagnetic simulation was employed to study the magnetization reversal mechanisms in cylindrical nickel nanobars possessing magnetic vortices. Individual Ni nanobars of height 150-250 nm with aspect ratio varying from 2.1 to 2.5 were considered, all of them supporting magnetic vortices domains. Magnetization reversal in these nanobars involves the vortex-creation-annihilation (VCA) mechanism with an inversion symmetry feature observed mid-way during reversal process. The effect of incidence angle of externally applied field on overall magnetization reversal process is examined in detail. The corresponding variations in coercivity, squareness, exchange energy and vortex parameters are described by the micromagnetic study that can shed insights for building practical Ni nanobars magnetic nanostructures/devices.

  2. Involvement of S6K1 in mitochondria function and structure in HeLa cells.

    Science.gov (United States)

    Park, Jisoo; Tran, Quangdon; Mun, Kisun; Masuda, Kouhei; Kwon, So Hee; Kim, Seon-Hwan; Kim, Dong-Hoon; Thomas, George; Park, Jongsun

    2016-12-01

    The major biological function of mitochondria is to generate cellular energy through oxidative phosphorylation. Apart from cellular respiration, mitochondria also play a key role in signaling processes, including aging and cancer metabolism. It has been shown that S6K1-knockout mice are resistant to obesity due to enhanced beta-oxidation, with an increased number of large mitochondria. Therefore, in this report, the possible involvement of S6K1 in regulating mitochondria dynamics and function has been investigated in stable lenti-shS6K1-HeLa cells. Interestingly, S6K1-stably depleted HeLa cells showed phenotypical changes in mitochondria morphology. This observation was further confirmed by detailed image analysis of mitochondria shape. Corresponding molecular changes were also observed in these cells, such as the induction of mitochondrial fission proteins (Drp1 and Fis1). Oxygen consumption is elevated in S6K1-depeleted HeLa cells and FL5.12 cells. In addition, S6K1 depletion leads to enhancement of ATP production in cytoplasm and mitochondria. However, the relative ratio of mitochondrial ATP to cytoplasmic ATP is actually decreased in lenti-shS6K1-HeLa cells compared to control cells. Lastly, induction of mitophagy was found in lenti-shS6K1-HeLa cells with corresponding changes of mitochondria shape on electron microscope analysis. Taken together, our results indicate that S6K1 is involved in the regulation of mitochondria morphology and function in HeLa cells. This study will provide novel insights into S6K1 function in mitochondria-mediated cellular signaling. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. The structural involvement of the cingulate cortex in premanifest and early Huntington's disease.

    Science.gov (United States)

    Hobbs, Nicola Z; Pedrick, Amy V; Say, Miranda J; Frost, Chris; Dar Santos, Rachelle; Coleman, Allison; Sturrock, Aaron; Craufurd, David; Stout, Julie C; Leavitt, Blair R; Barnes, Josephine; Tabrizi, Sarah J; Scahill, Rachael I

    2011-08-01

    The impact of Huntington's disease neuropathology on the structure of the cingulate is uncertain, with evidence of both cortical enlargement and atrophy in this structure in early clinical disease. We sought to determine differences in cingulate volume between premanifest Huntington's disease and early Huntington's disease groups compared with controls using detailed manual measurements. Thirty controls, 30 subjects with premanifest Huntington's disease, and 30 subjects with early Huntington's disease were selected from the Vancouver site of the TRACK-HD study. Subjects underwent 3 Tesla magnetic resonance imaging and motor, cognitive, and neuropsychiatric assessment. The cingulate was manually delineated and subdivided into rostral, caudal, and posterior segments. Group differences in volume and associations with performance on 4 tasks thought to utilize cingulate function were examined, with adjustment for appropriate covariates. Cingulate volumes were, on average, 1.7 mL smaller in early Huntington's disease (P=.001) and 0.9 mL smaller in premanifest Huntington's disease (P=.1) compared with controls. Smaller volumes in subsections of the cingulate were associated with impaired recognition of negative emotions (P=.04), heightened depression (P=.009), and worse visual working memory performance (P=.01). There was no evidence of associations between volume and ability on a performance-monitoring task. This study disputes previous findings of enlargement of the cingulate cortex in Huntington's disease and instead suggests that the cingulate undergoes structural degeneration during early Huntington's disease with directionally consistent, nonsignificant differences seen in premanifest Huntington's disease. Cingulate atrophy may contribute to deficits in mood, emotional processing, and visual working memory in Huntington's disease. Copyright © 2011 Movement Disorder Society.

  4. Competitive adsorption involving phosphate and benzenecarboxylic acids on goethite--effects of molecular structures.

    Science.gov (United States)

    Lindegren, Malin; Persson, Per

    2010-03-01

    The competitive adsorption between phosphate and either one of seven benzenecarboxylates (benzoate, phthalate, trimellitate, trimesoate, hemimellitate, pyromellitate, and mellitate) on the surfaces of fine-particulate goethite (alpha-FeOOH) was investigated as a function of pH. The series of ligands contained molecules with an increasing number of functional groups as well as three structural isomers of the tricarboxylates. Thus, the effects of both the number of carboxylate groups and the relative positions of these groups on the competitive efficiency toward phosphate were probed in this study. Quantitative adsorption experiments in batch mode and infrared spectroscopy were collectively used to evaluate the competitive adsorption reactions. Under the conditions probed, mono- and dicarboxylates had no detectable effect on phosphate adsorption whereas the ligands containing three or more carboxylate groups were able to partially outcompete phosphate. However, the pH dependency and the extent of these competitive effects were strongly dependent on the structure and composition of the benzenecarboxylate. The collective results showed that it was the competition for hydrogen-bonding surface sites rather than inner sphere surface sites that primarily determined the outcome of the competitive adsorption experiments, and it was the ability of the organic ligand to act as hydrogen-bonding acceptor and/or donor in various parts of the pH range that also determined the competitive pH dependency. The importance of H-bonding for the competitive adsorption between phosphate and benzenecarboxylic acids suggested that H-bonding interactions contributed substantially to the stabilities of both the adsorbed benzenecarboxylates and the phosphate ions and that these interactions were structurally specific; i.e., they were sensitive to the locations and the directional properties of the H-acceptor and H-donor surface sites. 2009 Elsevier Inc. All rights reserved.

  5. Structure and Characterization of Proteins and Enzymes Involved in Nucleotide Metabolism and Iron-Sulfur Proteins

    DEFF Research Database (Denmark)

    Løvgreen, Monika Nøhr; Ooi, Bee Lean

    , a program named MyCrystals has been developed to keep track of crystallization trials and results. The program combines pictures with crystallization conditions and is able to sort the pictures based on selected conditions. MyCrystals was used extensively throughout this work and allows for an overview...... extended β-sheet dimers. These dimers were not observed in solution and were likely a result of the high protein concentration in the crystals. WT, A115V and A115G Mt DCD-DUT were successfully purified, and the crystal structure of the A115V variant with dTTP bound was solved. The variants were created...

  6. Structural factors associated with an increased risk of HIV and sexually transmitted infection transmission among street-involved youth

    Directory of Open Access Journals (Sweden)

    Shoveller Jean A

    2009-01-01

    Full Text Available Abstract Background The prevalence of HIV and sexually transmitted infections (STIs among street-involved youth greatly exceed that of the general adolescent population; however, little is known regarding the structural factors that influence disease transmission risk among this population. Methods Between September 2005 and October 2006, 529 street-involved youth were enroled in a prospective cohort known as the At Risk Youth Study (ARYS. We examined structural factors associated with number of sex partners using quasi-Poisson regression and consistent condom use using logistic regression. Results At baseline, 415 (78.4% were sexually active, of whom 253 (61.0% reported multiple sex partners and 288 (69.4% reported inconsistent condom use in the past six months. In multivariate analysis, self-reported barriers to health services were inversely associated with consistent condom use (adjusted odds ratio [aOR] = 0.52, 95%CI: 0.25 – 1.07. Structural factors that were associated with greater numbers of sex partners included homelessness (adjusted incidence rate ratio [aIRR] = 1.54, 95%CI: 1.11 – 2.14 and having an area restriction that affects access to services (aIRR = 2.32, 95%CI: 1.28 – 4.18. Being searched or detained by the police was significant for males (aIRR = 1.36, 95%CI: 1.02 – 1.81. Conclusion Although limited by its cross-sectional design, our study found several structural factors amenable to policy-level interventions independently associated with sexual risk behaviours. These findings imply that the criminalization and displacement of street-involved youth may increase the likelihood that youth will engage in sexual risk behaviours and exacerbate the negative impact of resultant health outcomes. Moreover, our findings indicate that environmental-structural interventions may help to reduce the burden of these diseases among street youth in urban settings.

  7. The Incremental Induction of Neuroprotective Properties by Multiple Therapeutic Strategies for Primary and Secondary Neural Injury

    Directory of Open Access Journals (Sweden)

    Seunghoon Lee

    2015-08-01

    Full Text Available Neural diseases including injury by endogenous factors, traumatic brain injury, and degenerative neural injury are eventually due to reactive oxygen species (ROS. Thus ROS generation in neural tissues is a hallmark feature of numerous forms of neural diseases. Neural degeneration and the neural damage process is complex, involving a vast array of tissue structure, transcriptional/translational, electrochemical, metabolic, and functional events within the intact neighbors surrounding injured neural tissues. During aging, multiple changes involving physical, chemical, and biochemical processes occur from the molecular to the morphological levels in neural tissues. Among many recommended therapeutic candidates, melatonin also plays a role in protecting the nervous system from anti-inflammation and efficiently safeguards neuronal cells via antioxidants and other endogenous/exogenous beneficial factors. Therefore, given the wide range of mechanisms responsible for neuronal damage, multi-action drugs or therapies for the treatment of neural injury that make use of two or more agents and target several pathways may have greater efficacy in promoting functional recovery than a single therapy alone.

  8. Genetic algorithm based on optimization of neural network structure for fault diagnosis of the clutch retainer mechanism of MF 285 tractor

    Directory of Open Access Journals (Sweden)

    S. F Mousavi

    2016-09-01

    Full Text Available Introduction The diagnosis of agricultural machinery faults must be performed at an opportune time, in order to fulfill the agricultural operations in a timely manner and to optimize the accuracy and the integrity of a system, proper monitoring and fault diagnosis of the rotating parts is required. With development of fault diagnosis methods of rotating equipment, especially bearing failure, the security, performance and availability of machines has been increasing. In general, fault detection is conducted through a specific procedure which starts with data acquisition and continues with features extraction, and subsequently failure of the machine would be detected. Several practical methods have been introduced for fault detection in rotating parts of machineries. The review of the literature shows that both Artificial Neural Networks (ANN and Support Vector Machines (SVM have been used for this purpose. However, the results show that SVM is more effective than Artificial Neural Networks in fault detection of such machineries. In some smart detection systems, incorporating an optimized method such as Genetic Algorithm in the Neural Network model, could improve the fault detection procedure. Consequently, the fault detection performance of neural networks may also be improved by combining with the Genetic Algorithm and hence will be comparable with the performance of the Support Vector Machine. In this study, the so called Genetic Algorithm (GA method was used to optimize the structure of the Artificial Neural Networks (ANN for fault detection of the clutch retainer mechanism of Massey Ferguson 285 tractor. Materials and Methods The test rig consists of some electro mechanical parts including the clutch retainer mechanism of Massey Ferguson 285 tractor, a supporting shaft, a single-phase electric motor, a loading mechanism to model the load of the tractor clutch and the corresponding power train gears. The data acquisition section consists of a

  9. Crystal structure of a human membrane protein involved in cysteinyl leukotriene biosynthesis.

    Science.gov (United States)

    Ago, Hideo; Kanaoka, Yoshihide; Irikura, Daisuke; Lam, Bing K; Shimamura, Tatsuro; Austen, K Frank; Miyano, Masashi

    2007-08-02

    The cysteinyl leukotrienes, namely leukotriene (LT)C4 and its metabolites LTD4 and LTE4, the components of slow-reacting substance of anaphylaxis, are lipid mediators of smooth muscle constriction and inflammation, particularly implicated in bronchial asthma. LTC4 synthase (LTC4S), the pivotal enzyme for the biosynthesis of LTC4 (ref. 10), is an 18-kDa integral nuclear membrane protein that belongs to a superfamily of membrane-associated proteins in eicosanoid and glutathione metabolism that includes 5-lipoxygenase-activating protein, microsomal glutathione S-transferases (MGSTs), and microsomal prostaglandin E synthase 1 (ref. 13). LTC4S conjugates glutathione to LTA4, the endogenous substrate derived from arachidonic acid through the 5-lipoxygenase pathway. In contrast with MGST2 and MGST3 (refs 15, 16), LTC4S does not conjugate glutathione to xenobiotics. Here we show the atomic structure of human LTC4S in a complex with glutathione at 3.3 A resolution by X-ray crystallography and provide insights into the high substrate specificity for glutathione and LTA4 that distinguishes LTC4S from other MGSTs. The LTC4S monomer has four transmembrane alpha-helices and forms a threefold symmetric trimer as a unit with functional domains across each interface. Glutathione resides in a U-shaped conformation within an interface between adjacent monomers, and this binding is stabilized by a loop structure at the top of the interface. LTA4 would fit into the interface so that Arg 104 of one monomer activates glutathione to provide the thiolate anion that attacks C6 of LTA4 to form a thioether bond, and Arg 31 in the neighbouring monomer donates a proton to form a hydroxyl group at C5, resulting in 5(S)-hydroxy-6(R)-S-glutathionyl-7,9-trans-11,14-cis-eicosatetraenoic acid (LTC4). These findings provide a structural basis for the development of LTC4S inhibitors for a proinflammatory pathway mediated by three cysteinyl leukotriene ligands whose stability and potency are different

  10. Artificial neural networks modeling gene-environment interaction

    Directory of Open Access Journals (Sweden)

    Günther Frauke

    2012-05-01

    Full Text Available Abstract Background Gene-environment interactions play an important role in the etiological pathway of complex diseases. An appropriate statistical method for handling a wide variety of complex situations involving interactions between variables is still lacking, especially when continuous variables are involved. The aim of this paper is to explore the ability of neural networks to model different structures of gene-environment interactions. A simulation study is set up to compare neural networks with standard logistic regression models. Eight different structures of gene-environment interactions are investigated. These structures are characterized by penetrance functions that are based on sigmoid functions or on combinations of linear and non-linear effects of a continuous environmental factor and a genetic factor with main effect or with a masking effect only. Results In our simulation study, neural networks are more successful in modeling gene-environment interactions than logistic regression models. This outperfomance is especially pronounced when modeling sigmoid penetrance functions, when distinguishing between linear and nonlinear components, and when modeling masking effects of the genetic factor. Conclusion Our study shows that neural networks are a promising approach for analyzing gene-environment interactions. Especially, if no prior knowledge of the correct nature of the relationship between co-variables and response variable is present, neural networks provide a valuable alternative to regression methods that are limited to the analysis of linearly separable data.

  11. Functional Magnetic Resonance Imaging with Concurrent Urodynamic Testing Identifies Brain Structures Involved in Micturition Cycle in Patients with Multiple Sclerosis.

    Science.gov (United States)

    Khavari, Rose; Karmonik, Christof; Shy, Michael; Fletcher, Sophie; Boone, Timothy

    2017-02-01

    Neurogenic lower urinary tract dysfunction, which is common in patients with multiple sclerosis, has a significant impact on quality of life. In this study we sought to determine brain activity processes during the micturition cycle in female patients with multiple sclerosis and neurogenic lower urinary tract dysfunction. We report brain activity on functional magnetic resonance imaging and simultaneous urodynamic testing in 23 ambulatory female patients with multiple sclerosis. Individual functional magnetic resonance imaging activation maps at strong desire to void and at initiation of voiding were calculated and averaged at Montreal Neuroimaging Institute. Areas of significant activation were identified in these average maps. Subgroup analysis was performed in patients with elicitable neurogenic detrusor overactivity or detrusor-sphincter dyssynergia. Group analysis of all patients at strong desire to void yielded areas of activation in regions associated with executive function (frontal gyrus), emotional regulation (cingulate gyrus) and motor control (putamen, cerebellum and precuneus). Comparison of the average change in activation between previously reported healthy controls and patients with multiple sclerosis showed predominantly stronger, more focal activation in the former and lower, more diffused activation in the latter. Patients with multiple sclerosis who had demonstrable neurogenic detrusor overactivity and detrusor-sphincter dyssynergia showed a trend toward distinct brain activation at full urge and at initiation of voiding respectively. We successfully studied brain activation during the entire micturition cycle in female patients with neurogenic lower urinary tract dysfunction and multiple sclerosis using a concurrent functional magnetic resonance imaging/urodynamic testing platform. Understanding the central neural processes involved in specific parts of micturition in patients with neurogenic lower urinary tract dysfunction may identify areas

  12. Are liquid crystalline properties of nucleosomes involved in chromosome structure and dynamics?

    Science.gov (United States)

    Livolant, Françoise; Mangenot, Stéphanie; Leforestier, Amélie; Bertin, Aurélie; Frutos, Marta de; Raspaud, Eric; Durand, Dominique

    2006-10-15

    Nucleosome core particles correspond to the structural units of eukaryotic chromatin. They are charged colloids, 101 Angstrom in diameter and 55 Angstrom in length, formed by the coiling of a 146/147 bp DNA fragment (50 nm) around the histone protein octamer. Solutions of these particles can be concentrated, under osmotic pressure, up to the concentrations found in the nuclei of living cells. In the presence of monovalent cations (Na(+)), nucleosomes self-assemble into crystalline or liquid crystalline phases. A lamello-columnar phase is observed at 'low salt' concentrations, while a two-dimensional hexagonal phase and a three-dimensional quasi-hexagonal phase form at 'high salt' concentrations. We followed the formation of these phases from the dilute isotropic solutions to the ordered phases by combining cryoelectron microscopy and X-ray diffraction analyses. The phase diagram is presented as a function of the monovalent salt concentration and applied osmotic pressure. An alternative method to condense nucleosomes is to induce their aggregation upon addition of divalent or multivalent cations (Mg(2+), spermidine(3+) and spermine(4+)). Ordered phases are also found in the aggregates. We also discuss whether these condensed phases of nucleosomes may be relevant from a biological point of view.

  13. Neural plasticity and its initiating conditions in tinnitus.

    Science.gov (United States)

    Roberts, L E

    2017-12-12

    Deafferentation caused by cochlear pathology (which can be hidden from the audiogram) activates forms of neural plasticity in auditory pathways, generating tinnitus and its associated conditions including hyperacusis. This article discusses tinnitus mechanisms and suggests how these mechanisms may relate to those involved in normal auditory information processing. Research findings from animal models of tinnitus and from electromagnetic imaging of tinnitus patients are reviewed which pertain to the role of deafferentation and neural plasticity in tinnitus and hyperacusis. Auditory neurons compensate for deafferentation by increasing their input/output functions (gain) at multiple levels of the auditory system. Forms of homeostatic plasticity are believed to be responsible for this neural change, which increases the spontaneous and driven activity of neurons in central auditory structures in animals expressing behavioral evidence of tinnitus. Another tinnitus correlate, increased neural synchrony among the affected neurons, is forged by spike-timing-dependent neural plasticity in auditory pathways. Slow oscillations generated by bursting thalamic neurons verified in tinnitus animals appear to modulate neural plasticity in the cortex, integrating tinnitus neural activity with information in brain regions supporting memory, emotion, and consciousness which exhibit increased metabolic activity in tinnitus patients. The latter process may be induced by transient auditory events in normal processing but it persists in tinnitus, driven by phantom signals from the auditory pathway. Several tinnitus therapies attempt to suppress tinnitus through plasticity, but repeated sessions will likely be needed to prevent tinnitus activity from returning owing to deafferentation as its initiating condition.

  14. Modeling a Neural Network as a Teaching Tool for the Learning of the Structure-Function Relationship

    Science.gov (United States)

    Salinas, Dino G.; Acevedo, Cristian; Gomez, Christian R.

    2010-01-01

    The authors describe an activity they have created in which students can visualize a theoretical neural network whose states evolve according to a well-known simple law. This activity provided an uncomplicated approach to a paradigm commonly represented through complex mathematical formulation. From their observations, students learned many basic…

  15. DHX9 helicase is involved in preventing genomic instability induced by alternatively structured DNA in human cells

    Science.gov (United States)

    Jain, Aklank; Bacolla, Albino; del Mundo, Imee M.; Zhao, Junhua; Wang, Guliang; Vasquez, Karen M.

    2013-01-01

    Sequences that have the capacity to adopt alternative (i.e. non-B) DNA structures in the human genome have been implicated in stimulating genomic instability. Previously, we found that a naturally occurring intra-molecular triplex (H-DNA) caused genetic instability in mammals largely in the form of DNA double-strand breaks. Thus, it is of interest to determine the mechanism(s) involved in processing H-DNA. Recently, we demonstrated that human DHX9 helicase preferentially unwinds inter-molecular triplex DNA in vitro. Herein, we used a mutation-reporter system containing H-DNA to examine the relevance of DHX9 activity on naturally occurring H-DNA structures in human cells. We found that H-DNA significantly increased mutagenesis in small-interfering siRNA-treated, DHX9-depleted cells, affecting mostly deletions. Moreover, DHX9 associated with H-DNA in the context of supercoiled plasmids. To further investigate the role of DHX9 in the recognition/processing of H-DNA, we performed binding assays in vitro and chromatin immunoprecipitation assays in U2OS cells. DHX9 recognized H-DNA, as evidenced by its binding to the H-DNA structure and enrichment at the H-DNA region compared with a control region in human cells. These composite data implicate DHX9 in processing H-DNA structures in vivo and support its role in the overall maintenance of genomic stability at sites of alternatively structured DNA. PMID:24049074

  16. Lectin staining shows no evidence of involvement of glycocalyx/mucous layer carbohydrate structures in development of celiac disease

    DEFF Research Database (Denmark)

    Toft-Hansen, Henrik; Nielsen, Christian; Biagini, Matteo

    2013-01-01

    The presence of unique carbohydrate structures in the glycocalyx/mucous layer of the intestine may be involved in a susceptibility to celiac disease (CD) by serving as attachment sites for bacteria. This host-microbiota interaction may influence the development of CD and possibly other diseases...... with autoimmune components. We examined duodenal biopsies from a total of 30 children, of which 10 had both celiac disease (CD) and type 1 diabetes (T1D); 10 had CD alone; and 10 were suspected of having gastrointestinal disease, but had normal duodenal histology (non-CD controls). Patients with both CD and T1D...... showed no significant differences. Based on our material, we found no indication that the presence of Gal-β(1,3)-GalNAc or Fucα1-2Gal-R is involved in the susceptibility to CD, or that the disease process affects the expression of these carbohydrates....

  17. Identification of β-Dystrobrevin as a Direct Target of miR-143: Involvement in Early Stages of Neural Differentiation.

    Science.gov (United States)

    Quaranta, Maria Teresa; Spinello, Isabella; Paolillo, Rosa; Macchia, Gianfranco; Boe, Alessandra; Ceccarini, Marina; Labbaye, Catherine; Macioce, Pompeo

    2016-01-01

    Duchenne Muscular Dystrophy, a genetic disorder that results in a gradual breakdown of muscle, is associated to mild to severe cognitive impairment in about one-third of dystrophic patients. The brain dysfunction is independent of the muscular pathology, occurs early, and is most likely due to defects in the assembly of the Dystrophin-associated Protein Complex (DPC) during embryogenesis. We have recently described the interaction of the DPC component β-dystrobrevin with members of complexes that regulate chromatin dynamics, and suggested that β-dystrobrevin may play a role in the initiation of neuronal differentiation. Since oxygen concentrations and miRNAs appear as well to be involved in the cellular processes related to neuronal development, we have studied how these factors act on β-dystrobrevin and investigated the possibility of their functional interplay using the NTera-2 cell line, a well-established model for studying neurogenesis. We followed the pattern of expression and regulation of β-dystrobrevin during the early stages of neuronal differentiation induced by exposure to retinoic acid (RA) under hypoxia as compared with normoxia, and found that β-dystrobrevin expression is regulated during RA-induced differentiation of NTera-2 cells. We also found that β-dystrobrevin pattern is delayed under hypoxic conditions, together with a delay in the differentiation and an increase in the proliferation rate of cells. We identified miRNA-143 as a direct regulator of β-dystrobrevin expression, demonstrated that β-dystrobrevin is expressed in the nucleus and showed that, in line with our previous in vitro results, β-dystrobrevin is a repressor of synapsin I in live cells. Altogether the newly identified regulatory pathway miR-143/β-dystrobrevin/synapsin I provides novel insights into the functions of β-dystrobrevin and opens up new perspectives for elucidating the molecular mechanisms underlying the neuronal involvement in muscular dystrophy.

  18. Different structures involved during ictal and interictal epileptic activity in malformations of cortical development: an EEG-fMRI study.

    Science.gov (United States)

    Tyvaert, L; Hawco, C; Kobayashi, E; LeVan, P; Dubeau, F; Gotman, J

    2008-08-01

    Malformations of cortical development (MCDs) are commonly complicated by intractable focal epilepsy. Epileptogenesis in these disorders is not well understood and may depend on the type of MCD. The cellular mechanisms involved in interictal and ictal events are notably different, and could be influenced independently by the type of pathology. We evaluated the relationship between interictal and ictal zones in eight patients with different types of MCD in order to better understand the generation of these activities: four had nodular heterotopia, two focal cortical dysplasia and two subcortical band heterotopia (double-cortex). We used the non-invasive EEG-fMRI technique to record simultaneously all cerebral structures with a high spatio-temporal resolution. We recorded interictal and ictal events during the same session. Ictal events were either electrical only or clinical with minimal motion. BOLD changes were found in the focal cortical dysplasia during interictal and ictal epileptiform events in the two patients with this disorder. Heterotopic and normal cortices were involved in BOLD changes during interictal and ictal events in the two patients with double cortex, but the maximum BOLD response was in the heterotopic band in both patients. Only two of the four patients with nodular heterotopia showed involvement of a nodule during interictal activity. During seizures, although BOLD changes affected the lesion in two patients, the maximum was always in the overlying cortex and never in the heterotopia. For two patients intracranial recordings were available and confirm our findings. The dysplastic cortex and the heterotopic cortex of band heterotopia were involved in interictal and seizure processes. Even if the nodular gray matter heterotopia may have the cellular substrate to produce interictal events, the often abnormal overlying cortex is more likely to be involved during the seizures. The non-invasive BOLD study of interictal and ictal events in MCD

  19. Structures of Rhodopsin Kinase in Different Ligand States Reveal Key Elements Involved in G Protein-coupled Receptor Kinase Activation

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Puja; Wang, Benlian; Maeda, Tadao; Palczewski, Krzysztof; Tesmer, John J.G. (Case Western); (Michigan)

    2008-10-08

    G protein-coupled receptor (GPCR) kinases (GRKs) phosphorylate activated heptahelical receptors, leading to their uncoupling from G proteins. Here we report six crystal structures of rhodopsin kinase (GRK1), revealing not only three distinct nucleotide-binding states of a GRK but also two key structural elements believed to be involved in the recognition of activated GPCRs. The first is the C-terminal extension of the kinase domain, which was observed in all nucleotide-bound GRK1 structures. The second is residues 5-30 of the N terminus, observed in one of the GRK1{center_dot}(Mg{sup 2+}){sub 2} {center_dot}ATP structures. The N terminus was also clearly phosphorylated, leading to the identification of two novel phosphorylation sites by mass spectral analysis. Co-localization of the N terminus and the C-terminal extension near the hinge of the kinase domain suggests that activated GPCRs stimulate kinase activity by binding to this region to facilitate full closure of the kinase domain.

  20. Optical imaging of neuronal activity and visualization of fine neural structures in non-desheathed nervous systems.

    Directory of Open Access Journals (Sweden)

    Christopher John Goldsmith

    Full Text Available Locating circuit neurons and recording from them with single-cell resolution is a prerequisite for studying neural circuits. Determining neuron location can be challenging even in small nervous systems because neurons are densely packed, found in different layers, and are often covered by ganglion and nerve sheaths that impede access for recording electrodes and neuronal markers. We revisited the voltage-sensitive dye RH795 for its ability to stain and record neurons through the ganglion sheath. Bath-application of RH795 stained neuronal membranes in cricket, earthworm and crab ganglia without removing the ganglion sheath, revealing neuron cell body locations in different ganglion layers. Using the pyloric and gastric mill central pattern generating neurons in the stomatogastric ganglion (STG of the crab, Cancer borealis, we found that RH795 permeated the ganglion without major residue in the sheath and brightly stained somatic, axonal and dendritic membranes. Visibility improved significantly in comparison to unstained ganglia, allowing the identification of somata location and number of most STG neurons. RH795 also stained axons and varicosities in non-desheathed nerves, and it revealed the location of sensory cell bodies in peripheral nerves. Importantly, the spike activity of the sensory neuron AGR, which influences the STG motor patterns, remained unaffected by RH795, while desheathing caused significant changes in AGR activity. With respect to recording neural activity, RH795 allowed us to optically record membrane potential changes of sub-sheath neuronal membranes without impairing sensory activity. The signal-to-noise ratio was comparable with that previously observed in desheathed preparations and sufficiently high to identify neurons in single-sweep recordings and synaptic events after spike-triggered averaging. In conclusion, RH795 enabled staining and optical recording of neurons through the ganglion sheath and is therefore both a

  1. Structural and functional mapping of Rtg2p determinants involved in retrograde signaling and aging of Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Rafaela Maria Rios-Anjos

    Full Text Available In Saccharomyces cerevisiae mitochondrial dysfunction induces retrograde signaling, a pathway of communication from mitochondria to the nucleus that promotes a metabolic remodeling to ensure sufficient biosynthetic precursors for replication. Rtg2p is a positive modulator of this pathway that is also required for cellular longevity. This protein belongs to the ASKHA superfamily, and contains a putative N-terminal ATP-binding domain, but there is no detailed structural and functional map of the residues in this domain that accounts for their contribution to retrograde signaling and aging. Here we use Decomposition of Residue Correlation Networks and site-directed mutagenesis to identify Rtg2p structural determinants of retrograde signaling and longevity. We found that most of the residues involved in retrograde signaling surround the ATP-binding loops, and that Rtg2p N-terminus is divided in three regions whose mutants have different aging phenotypes. We also identified E137, D158 and S163 as possible residues involved in stabilization of ATP at the active site. The mutants shown here may be used to map other Rtg2p activities that crosstalk to other pathways of the cell related to genomic stability and aging.

  2. Structure/function analysis of Na(+)-K(+)-ATPase central isoform-specific region: involvement in PKC regulation.

    Science.gov (United States)

    Pierre, Sandrine V; Duran, Marie-Josée; Carr, Deborah L; Pressley, Thomas A

    2002-11-01

    Specific functions served by the various Na(+)-K(+)-ATPase alpha-isoforms are likely to originate in regions of structural divergence within their primary structures. The isoforms are nearly identical, with the exception of the NH(2) terminus and a 10-residue region near the center of each molecule (isoform-specific region; ISR). Although the NH(2) terminus has been clearly identified as a source of isoform functional diversity, other regions seem to be involved. We investigated whether the central ISR could also contribute to isoform variability. We constructed chimeric molecules in which the central ISRs of rat alpha(1)- and alpha(2)-isoforms were exchanged. After stable transfection into opossum kidney cells, the chimeras were characterized for two properties known to differ dramatically among the isoforms: their K(+) deocclusion pattern and their response to PKC activation. Comparisons with rat full-length alpha(1)- and alpha(2)-isoforms expressed under the same conditions suggest an involvement of the central ISR in the response to PKC but not in K(+) deocclusion.

  3. Structural alterations in rat liver proteins due to streptozotocin-induced diabetes and the recovery effect of selenium: Fourier transform infrared microspectroscopy and neural network study

    Science.gov (United States)

    Bozkurt, Ozlem; Haman Bayari, Sevgi; Severcan, Mete; Krafft, Christoph; Popp, Jürgen; Severcan, Feride

    2012-07-01

    The relation between protein structural alterations and tissue dysfunction is a major concern as protein fibrillation and/or aggregation due to structural alterations has been reported in many disease states. In the current study, Fourier transform infrared microspectroscopic imaging has been used to investigate diabetes-induced changes on protein secondary structure and macromolecular content in streptozotocin-induced diabetic rat liver. Protein secondary structural alterations were predicted using neural network approach utilizing the amide I region. Moreover, the role of selenium in the recovery of diabetes-induced alterations on macromolecular content and protein secondary structure was also studied. The results revealed that diabetes induced a decrease in lipid to protein and glycogen to protein ratios in diabetic livers. Significant alterations in protein secondary structure were observed with a decrease in α-helical and an increase in β-sheet content. Both doses of selenium restored diabetes-induced changes in lipid to protein and glycogen to protein ratios. However, low-dose selenium supplementation was not sufficient to recover the effects of diabetes on protein secondary structure, while a higher dose of selenium fully restored diabetes-induced alterations in protein structure.

  4. Compensatory recruitment of neural resources in chronic alcoholism.

    Science.gov (United States)

    Chanraud, Sandra; Sullivan, Edith V

    2014-01-01

    Functional recovery occurs with sustained sobriety, but the neural mechanisms enabling recovery are only now emerging. Theories about promising mechanisms involve concepts of neuroadaptation, where excessive alcohol consumption results in untoward structural and functional brain changes which are subsequently candidates for reversal with sobriety. Views on functional adaptation in chronic alcoholism have expanded with results from neuroimaging studies. Here, we first describe and define the concept of neuroadaptation according to emerging theories based on the growing literature in aging-related cognitive functioning. Then we describe findings as they apply to chronic alcoholism and factors that could influence compensation, such as functional brain reserve and the integrity of brain structure. Finally, we review brain plasticity based on physiologic mechanisms that could underlie mechanisms of neural compensation. Where possible, we provide operational criteria to define functional and neural compensation. © 2014 Elsevier B.V. All rights reserved.

  5. Structural and functional study of YER067W, a new protein involved in yeast metabolism control and drug resistance.

    Directory of Open Access Journals (Sweden)

    Tatiana Domitrovic

    2010-06-01

    Full Text Available The genome of Saccharomyces cerevisiae is arguably the best studied eukaryotic genome, and yet, it contains approximately 1000 genes that are still relatively uncharacterized. As the majority of these ORFs have no homologs with characterized sequence or protein structure, traditional sequence-based approaches cannot be applied to deduce their biological function. Here, we characterize YER067W, a conserved gene of unknown function that is strongly induced in response to many stress conditions and repressed in drug resistant yeast strains. Gene expression patterns of YER067W and its paralog YIL057C suggest an involvement in energy metabolism. We show that yeast lacking YER067W display altered levels of reserve carbohydrates and a growth deficiency in media that requires aerobic metabolism. Impaired mitochondrial function and overall reduction of ergosterol content in the YER067W deleted strain explained the observed 2- and 4-fold increase in resistance to the drugs fluconazole and amphotericin B, respectively. Cell fractionation and immunofluorescence microscopy revealed that Yer067w is associated with cellular membranes despite the absence of a transmembrane domain in the protein. Finally, the 1.7 A resolution crystal structure of Yer067w shows an alpha-beta fold with low similarity to known structures and a putative functional site.YER067W's involvement with aerobic energetic metabolism suggests the assignment of the gene name RGI1, standing for respiratory growth induced 1. Altogether, the results shed light on a previously uncharacterized protein family and provide basis for further studies of its apparent role in energy metabolism control and drug resistance.

  6. Functional and Structural Analysis of a β-Glucosidase Involved in β-1,2-Glucan Metabolism in Listeria innocua.

    Directory of Open Access Journals (Sweden)

    Masahiro Nakajima

    Full Text Available Despite the presence of β-1,2-glucan in nature, few β-1,2-glucan degrading enzymes have been reported to date. Recently, the Lin1839 protein from Listeria innocua was identified as a 1,2-β-oligoglucan phosphorylase. Since the adjacent lin1840 gene in the gene cluster encodes a putative glycoside hydrolase family 3 β-glucosidase, we hypothesized that Lin1840 is also involved in β-1,2-glucan dissimilation. Here we report the functional and structural analysis of Lin1840. A recombinant Lin1840 protein (Lin1840r showed the highest hydrolytic activity toward sophorose (Glc-β-1,2-Glc among β-1,2-glucooligosaccharides, suggesting that Lin1840 is a β-glucosidase involved in sophorose degradation. The enzyme also rapidly hydrolyzed laminaribiose (β-1,3, but not cellobiose (β-1,4 or gentiobiose (β-1,6 among β-linked gluco-disaccharides. We determined the crystal structures of Lin1840r in complexes with sophorose and laminaribiose as productive binding forms. In these structures, Arg572 forms many hydrogen bonds with sophorose and laminaribiose at subsite +1, which seems to be a key factor for substrate selectivity. The opposite side of subsite +1 from Arg572 is connected to a large empty space appearing to be subsite +2 for the binding of sophorotriose (Glc-β-1,2-Glc-β-1,2-Glc in spite of the higher Km value for sophorotriose than that for sophorose. The conformations of sophorose and laminaribiose are almost the same on the Arg572 side but differ on the subsite +2 side that provides no interaction with a substrate. Therefore, Lin1840r is unable to distinguish between sophorose and laminaribiose as substrates. These results provide the first mechanistic insights into β-1,2-glucooligosaccharide recognition by β-glucosidase.

  7. Structural insights into the human RyR2 N-terminal region involved in cardiac arrhythmias

    Energy Technology Data Exchange (ETDEWEB)

    Borko, Ľubomír; Bauerová-Hlinková, Vladena, E-mail: vladena.bauerova@savba.sk; Hostinová, Eva; Gašperík, Juraj [Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava (Slovakia); Beck, Konrad [Cardiff University School of Dentistry, Heath Park, Cardiff CF14 4XY Wales (United Kingdom); Lai, F. Anthony [Cardiff University School of Medicine, Cardiff CF14 4XN Wales (United Kingdom); Zahradníková, Alexandra, E-mail: vladena.bauerova@savba.sk [Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava (Slovakia); Institute of Molecular Physiology and Genetics, Slovak Academy of Sciences, Vlárska 5, 833 34 Bratislava (Slovakia); Ševčík, Jozef, E-mail: vladena.bauerova@savba.sk [Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava (Slovakia)

    2014-11-01

    X-ray and solution structures of the human RyR2 N-terminal region were obtained under near-physiological conditions. The structure exhibits a unique network of interactions between its three domains, revealing an important stabilizing role of the central helix. Human ryanodine receptor 2 (hRyR2) mediates calcium release from the sarcoplasmic reticulum, enabling cardiomyocyte contraction. The N-terminal region of hRyR2 (amino acids 1–606) is the target of >30 arrhythmogenic mutations and contains a binding site for phosphoprotein phosphatase 1. Here, the solution and crystal structures determined under near-physiological conditions, as well as a homology model of the hRyR2 N-terminal region, are presented. The N-terminus is held together by a unique network of interactions among its three domains, A, B and C, in which the central helix (amino acids 410–437) plays a prominent stabilizing role. Importantly, the anion-binding site reported for the mouse RyR2 N-terminal region is notably absent from the human RyR2. The structure concurs with the differential stability of arrhythmogenic mutations in the central helix (R420W, I419F and I419F/R420W) which are owing to disparities in the propensity of mutated residues to form energetically favourable or unfavourable contacts. In solution, the N-terminus adopts a globular shape with a prominent tail that is likely to involve residues 545–606, which are unresolved in the crystal structure. Docking the N-terminal domains into cryo-electron microscopy maps of the closed and open RyR1 conformations reveals C{sup α} atom movements of up to 8 Å upon channel gating, and predicts the location of the leucine–isoleucine zipper segment and the interaction site for spinophilin and phosphoprotein phosphatase 1 on the RyR surface.

  8. Structure reveals regulatory mechanisms of a MaoC-like hydratase from Phytophthora capsici involved in biosynthesis of polyhydroxyalkanoates (PHAs.

    Directory of Open Access Journals (Sweden)

    Huizheng Wang

    Full Text Available BACKGROUND: Polyhydroxyalkanoates (PHAs have attracted increasing attention as "green plastic" due to their biodegradable, biocompatible, thermoplastic, and mechanical properties, and considerable research has been undertaken to develop low cost/high efficiency processes for the production of PHAs. MaoC-like hydratase (MaoC, which belongs to (R-hydratase involved in linking the β-oxidation and the PHA biosynthetic pathways, has been identified recently. Understanding the regulatory mechanisms of (R-hydratase catalysis is critical for efficient production of PHAs that promise synthesis an environment-friendly plastic. METHODOLOGY/PRINCIPAL FINDINGS: We have determined the crystal structure of a new MaoC recognized from Phytophthora capsici. The crystal structure of the enzyme was solved at 2.00 Å resolution. The structure shows that MaoC has a canonical (R-hydratase fold with an N-domain and a C-domain. Supporting its dimerization observed in structure, MaoC forms a stable homodimer in solution. Mutations that disrupt the dimeric MaoC result in a complete loss of activity toward crotonyl-CoA, indicating that dimerization is required for the enzymatic activity of MaoC. Importantly, structure comparison reveals that a loop unique to MaoC interacts with an α-helix that harbors the catalytic residues of MaoC. Deletion of the loop enhances the enzymatic activity of MaoC, suggesting its inhibitory role in regulating the activity of MaoC. CONCLUSIONS/SIGNIFICANCE: The data in our study reveal the regulatory mechanism of an (R-hydratase, providing information on enzyme engineering to produce low cost PHAs.

  9. Structural and functional analysis of validoxylamine A 7'-phosphate synthase ValL involved in validamycin A biosynthesis.

    Directory of Open Access Journals (Sweden)

    Lina Zheng

    Full Text Available Validamycin A (Val-A is an effective antifungal agent widely used in Asian countries as crop protectant. Validoxylamine A, the core structure and intermediate of Val-A, consists of two C(7-cyclitol units connected by a rare C-N bond. In the Val-A biosynthetic gene cluster in Streptomyces hygroscopicus 5008, the ORF valL was initially annotated as a validoxylamine A 7'-phosphate(V7P synthase, whose encoded 497-aa protein shows high similarity with trehalose 6-phosphate(T6P synthase. Gene inactivation of valL abolished both validoxylamine A and validamycin A productivity, and complementation with a cloned valL recovered 10% production of the wild-type in the mutant, indicating the involvement of ValL in validoxylamine A biosynthesis. Also we determined the structures of ValL and ValL/trehalose complex. The structural data indicates that ValL adopts the typical fold of GT-B protein family, featuring two Rossmann-fold domains and an active site at domain junction. The residues in the active site are arranged in a manner homologous to that of Escherichia coli (E.coli T6P synthase OtsA. However, a significant discrepancy is found in the active-site loop region. Also noticeable structural variance is found around the active site entrance in the apo ValL structure while the region takes an ordered configuration upon binding of product analog trehalose. Furthermore, the modeling of V7P in the active site of ValL suggests that ValL might have a similar SNi-like mechanism as OtsA.

  10. Neural Blockade for Persistent Pain After Breast Cancer Surgery

    DEFF Research Database (Denmark)

    Wijayasinghe, Nelun; Andersen, Kenneth Geving; Kehlet, Henrik

    2014-01-01

    involved in neuropathic pain syndromes or to be used as a treatment in its own right. The purpose of this review was to examine the evidence for neural blockade as a potential diagnostic tool or treatment for persistent pain after breast cancer surgery. In this systematic review, we found only 7 studies (n...... = 135) assessing blocks directed at 3 neural structures-stellate ganglion, paravertebral plexus, and intercostal nerves-but none focusing on the intercostobrachial nerve. The quality of the studies was low and efficacy inconclusive, suggesting a need for well-designed, high-quality studies...

  11. Structure of Ca2+-binding protein-6 from Entamoeba histolytica and its involvement in trophozoite proliferation regulation.

    Science.gov (United States)

    Verma, Deepshikha; Murmu, Aruna; Gourinath, Samudrala; Bhattacharya, Alok; Chary, Kandala V R

    2017-05-01

    Cell cycle of Entamoeba histolytica, the etiological agent of amoebiasis, follows a novel pathway, which includes nuclear division without the nuclear membrane disassembly. We report a nuclear localized Ca2+-binding protein from E. histolytica (abbreviated hereafter as EhCaBP6), which is associated with microtubules. We determined the 3D solution NMR structure of EhCaBP6, and identified one unusual, one canonical and two non-canonical cryptic EF-hand motifs. The cryptic EF-II and EF-IV pair with the Ca2+-binding EF-I and EF-III, respectively, to form a two-domain structure similar to Calmodulin and Centrin proteins. Downregulation of EhCaBP6 affects cell proliferation by causing delays in transition from G1 to S phase, and inhibition of DNA synthesis and cytokinesis. We also demonstrate that EhCaBP6 modulates microtubule dynamics by increasing the rate of tubulin polymerization. Our results, including structural inferences, suggest that EhCaBP6 is an unusual CaBP involved in regulating cell proliferation in E. histolytica similar to nuclear Calmodulin.

  12. Neural stem cells and neuro/gliogenesis in the central nervous system: understanding the structural and functional plasticity of the developing, mature, and diseased brain.

    Science.gov (United States)

    Yamaguchi, Masahiro; Seki, Tatsunori; Imayoshi, Itaru; Tamamaki, Nobuaki; Hayashi, Yoshitaka; Tatebayashi, Yoshitaka; Hitoshi, Seiji

    2016-05-01

    Neurons and glia in the central nervous system (CNS) originate from neural stem cells (NSCs). Knowledge of the mechanisms of neuro/gliogenesis from NSCs is fundamental to our understanding of how complex brain architecture and function develop. NSCs are present not only in the developing brain but also in the mature brain in adults. Adult neurogenesis likely provides remarkable plasticity to the mature brain. In addition, recent progress in basic research in mental disorders suggests an etiological link with impaired neuro/gliogenesis in particular brain regions. Here, we review the recent progress and discuss future directions in stem cell and neuro/gliogenesis biology by introducing several topics presented at a joint meeting of the Japanese Association of Anatomists and the Physiological Society of Japan in 2015. Collectively, these topics indicated that neuro/gliogenesis from NSCs is a common event occurring in many brain regions at various ages in animals. Given that significant structural and functional changes in cells and neural networks are accompanied by neuro/gliogenesis from NSCs and the integration of newly generated cells into the network, stem cell and neuro/gliogenesis biology provides a good platform from which to develop an integrated understanding of the structural and functional plasticity that underlies the development of the CNS, its remodeling in adulthood, and the recovery from diseases that affect it.

  13. HDAC up-regulation in early colon field carcinogenesis is involved in cell tumorigenicity through regulation of chromatin structure.

    Science.gov (United States)

    Stypula-Cyrus, Yolanda; Damania, Dhwanil; Kunte, Dhananjay P; Cruz, Mart Dela; Subramanian, Hariharan; Roy, Hemant K; Backman, Vadim

    2013-01-01

    Normal cell function is dependent on the proper maintenance of chromatin structure. Regulation of chromatin structure is controlled by histone modifications that directly influence chromatin architecture and genome function. Specifically, the histone deacetylase (HDAC) family of proteins modulate chromatin compaction and are commonly dysregulated in many tumors, including colorectal cancer (CRC). However, the role of HDAC proteins in early colorectal carcinogenesis has not been previously reported. We found HDAC1, HDAC2, HDAC3, HDAC5, and HDAC7 all to be up-regulated in the field of human CRC. Furthermore, we observed that HDAC2 up-regulation is one of the earliest events in CRC carcinogenesis and observed this in human field carcinogenesis, the azoxymethane-treated rat model, and in more aggressive colon cancer cell lines. The universality of HDAC2 up-regulation suggests that HDAC2 up-regulation is a novel and important early event in CRC, which may serve as a biomarker. HDAC inhibitors (HDACIs) interfere with tumorigenic HDAC activity; however, the precise mechanisms involved in this process remain to be elucidated. We confirmed that HDAC inhibition by valproic acid (VPA) targeted the more aggressive cell line. Using nuclease digestion assays and transmission electron microscopy imaging, we observed that VPA treatment induced greater changes in chromatin structure in the more aggressive cell line. Furthermore, we used the novel imaging technique partial wave spectroscopy (PWS) to quantify nanoscale alterations in chromatin. We noted that the PWS results are consistent with the biological assays, indicating a greater effect of VPA treatment in the more aggressive cell type. Together, these results demonstrate the importance of HDAC activity in early carcinogenic events and the unique role of higher-order chromatin structure in determining cell tumorigenicity.

  14. HDAC up-regulation in early colon field carcinogenesis is involved in cell tumorigenicity through regulation of chromatin structure.

    Directory of Open Access Journals (Sweden)

    Yolanda Stypula-Cyrus

    Full Text Available Normal cell function is dependent on the proper maintenance of chromatin structure. Regulation of chromatin structure is controlled by histone modifications that directly influence chromatin architecture and genome function. Specifically, the histone deacetylase (HDAC family of proteins modulate chromatin compaction and are commonly dysregulated in many tumors, including colorectal cancer (CRC. However, the role of HDAC proteins in early colorectal carcinogenesis has not been previously reported. We found HDAC1, HDAC2, HDAC3, HDAC5, and HDAC7 all to be up-regulated in the field of human CRC. Furthermore, we observed that HDAC2 up-regulation is one of the earliest events in CRC carcinogenesis and observed this in human field carcinogenesis, the azoxymethane-treated rat model, and in more aggressive colon cancer cell lines. The universality of HDAC2 up-regulation suggests that HDAC2 up-regulation is a novel and important early event in CRC, which may serve as a biomarker. HDAC inhibitors (HDACIs interfere with tumorigenic HDAC activity; however, the precise mechanisms involved in this process remain to be elucidated. We confirmed that HDAC inhibition by valproic acid (VPA targeted the more aggressive cell line. Using nuclease digestion assays and transmission electron microscopy imaging, we observed that VPA treatment induced greater changes in chromatin structure in the more aggressive cell line. Furthermore, we used the novel imaging technique partial wave spectroscopy (PWS to quantify nanoscale alterations in chromatin. We noted that the PWS results are consistent with the biological assays, indicating a greater effect of VPA treatment in the more aggressive cell type. Together, these results demonstrate the importance of HDAC activity in early carcinogenic events and the unique role of higher-order chromatin structure in determining cell tumorigenicity.

  15. Prostaglandin E2 receptor expression in the rat trigeminal-vascular system and other brain structures involved in pain

    DEFF Research Database (Denmark)

    Myren, Maja; Olesen, Jes; Gupta, Saurabh

    2012-01-01

    receptors in both peripheral and central structures involved in pain transmission and perception in migraine: dura mater, cerebral arteries, trigeminal ganglion, trigeminal nucleus caudalis, periaqueductal grey, thalamus, hypothalamus, cortex, pituitary gland, hippocampus and cerebellum. In the trigeminal......Prostaglandin E(2) (PGE(2)) is considered to be a key mediator in migraine pathophysiology. PGE(2) acts via four receptors (EP(1)-EP(4)) but their distribution in the brain districts implicated in migraine has yet to be delineated. We quantified amount of mRNA and protein expression for the EP...... than in dorsal root ganglia (peripheral control), whereas the EP(2) mRNA and protein were highly abundant in the pituitary gland. EP(3) mRNA was mainly found in thalamus and hypothalamus. The most robust mRNA and protein expression for EP(4) receptor was seen in the dorsal root ganglion. In conclusion...

  16. Novel quantum inspired binary neural network algorithm

    Indian Academy of Sciences (India)

    In this paper, a quantum based binary neural network algorithm is proposed, named as novel quantum binary neural network algorithm (NQ-BNN). It forms a neural network structure by deciding weights and separability parameter in quantum based manner. Quantum computing concept represents solution probabilistically ...

  17. Lectin Staining Shows no Evidence of Involvement of Glycocalyx/Mucous Layer Carbohydrate Structures in Development of Celiac Disease

    Directory of Open Access Journals (Sweden)

    Henrik Toft-Hansen

    2013-11-01

    Full Text Available The presence of unique carbohydrate structures in the glycocalyx/mucous layer of the intestine may be involved in a susceptibility to celiac disease (CD by serving as attachment sites for bacteria. This host-microbiota interaction may influence the development of CD and possibly other diseases with autoimmune components. We examined duodenal biopsies from a total of 30 children, of which 10 had both celiac disease (CD and type 1 diabetes (T1D; 10 had CD alone; and 10 were suspected of having gastrointestinal disease, but had normal duodenal histology (non-CD controls. Patients with both CD and T1D were examined before and after remission following a gluten-free diet. We performed lectin histochemistry using peanut agglutinin (PNA and Ulex europaeus agglutinin (UEA staining for Gal-β(1,3-GalNAc and Fucα1-2Gal-R, respectively, of the glycocalyx/mucous layer. The staining was scored based on dissemination of stained structures on a scale from 0 to 3. Evaluation of the scores revealed no difference between biopsies obtained before and after remission in the group of children with both CD and T1D. A comparison of this pre-remission group with the children who had CD alone or the non-CD controls also showed no significant differences. Based on our material, we found no indication that the presence of Gal-β(1,3-GalNAc or Fucα1-2Gal-R is involved in the susceptibility to CD, or that the disease process affects the expression of these carbohydrates.

  18. Lectin Staining Shows no Evidence of Involvement of Glycocalyx/Mucous Layer Carbohydrate Structures in Development of Celiac Disease

    Science.gov (United States)

    Toft-Hansen, Henrik; Nielsen, Christian; Biagini, Matteo; Husby, Steffen; Lillevang, Søren T.

    2013-01-01

    The presence of unique carbohydrate structures in the glycocalyx/mucous layer of the intestine may be involved in a susceptibility to celiac disease (CD) by serving as attachment sites for bacteria. This host-microbiota interaction may influence the development of CD and possibly other diseases with autoimmune components. We examined duodenal biopsies from a total of 30 children, of which 10 had both celiac disease (CD) and type 1 diabetes (T1D); 10 had CD alone; and 10 were suspected of having gastrointestinal disease, but had normal duodenal histology (non-CD controls). Patients with both CD and T1D were examined before and after remission following a gluten-free diet. We performed lectin histochemistry using peanut agglutinin (PNA) and Ulex europaeus agglutinin (UEA) staining for Gal-β(1,3)-GalNAc and Fucα1-2Gal-R, respectively, of the glycocalyx/mucous layer. The staining was scored based on dissemination of stained structures on a scale from 0 to 3. Evaluation of the scores revealed no difference between biopsies obtained before and after remission in the group of children with both CD and T1D. A comparison of this pre-remission group with the children who had CD alone or the non-CD controls also showed no significant differences. Based on our material, we found no indication that the presence of Gal-β(1,3)-GalNAc or Fucα1-2Gal-R is involved in the susceptibility to CD, or that the disease process affects the expression of these carbohydrates. PMID:24253051

  19. Advocacy coalitions involved in California's menu labeling policy debate: Exploring coalition structure, policy beliefs, resources, and strategies.

    Science.gov (United States)

    Payán, Denise D; Lewis, LaVonna B; Cousineau, Michael R; Nichol, Michael B

    2017-03-01

    Advocacy coalitions often play an important role in the state health policymaking process, yet little is known about their structure, composition, and behavior. In 2008, California became the first state to enact a menu labeling law. Using the advocacy coalition framework, we examine different facets of the coalitions involved in California's menu labeling policy debate. We use a qualitative research approach to identify coalition members and explore their expressed beliefs and policy arguments, resources, and strategies by analyzing legislative documents (n = 87) and newspaper articles (n = 78) produced between 1999 and 2009. Between 2003 and 2008, six menu labeling bills were introduced in the state's legislature. We found the issue received increasing media attention during this period. We identified two advocacy coalitions involved in the debate-a public health (PH) coalition and an industry coalition. State organizations acted as coalition leaders and participated for a longer duration than elected officials. The structure and composition of each coalition varied. PH coalition leadership and membership notably increased compared to the industry coalition. The PH coalition, led by nonprofit PH and health organizations, promoted a clear and consistent message around informed decision making. The industry coalition, led by a state restaurant association, responded with cost and implementation arguments. Each coalition used various resources and strategies to advance desired outcomes. PH coalition leaders were particularly effective at using resources and employing advocacy strategies, which included engaging state legislators as coalition members, using public opinion polls and information, and leveraging media resources to garner support. Policy precedence and a local policy push emerged as important policymaking strategies. Areas for future research on the state health policymaking process are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Matrix architecture dictates three-dimensional migration modes of human macrophages: differential involvement of proteases and podosome-like structures.

    Science.gov (United States)

    Van Goethem, Emeline; Poincloux, Renaud; Gauffre, Fabienne; Maridonneau-Parini, Isabelle; Le Cabec, Véronique

    2010-01-15

    Tissue infiltration of macrophages, although critical for innate immunity, is also involved in pathologies, such as chronic inflammation and cancer. In vivo, macrophages migrate mostly in a constrained three-dimensional (3D) environment. However, in vitro studies, mainly focused on two dimensions, do not provide meaningful clues about the mechanisms involved in 3D macrophage migration. In contrast, tumor cell 3D migration is well documented. It comprises a protease-independent and Rho kinase (ROCK)-dependent amoeboid migration mode and a protease-dependent and ROCK-independent mesenchymal migration mode. In this study, we examined the influence of extracellular matrix (composition, architecture, and stiffness) on 3D migration of human macrophages derived from blood monocytes (MDMs). We show that: 1) MDMs use either the amoeboid migration mode in fibrillar collagen I or the mesenchymal migration mode in Matrigel and gelled collagen I, whereas HT1080 tumor cells only perform mesenchymal migration; 2) when MDMs use the mesenchymal migratory mode, they form 3D collagenolytic structures at the tips of cell protrusions that share several markers with podosomes as described in two dimensions; 3) in contrast to tumor cells, matrix metalloproteinase inhibitors do not impair protease-dependent macrophage 3D migration, suggesting the involvement of other proteolytic systems; and 4) MDMs infiltrating matrices of similar composition but with variable stiffness adapt their migration mode primarily to the matrix architecture. In conclusion, although it is admitted that leukocytes 3D migration is restricted to the amoeboid mode, we show that human macrophages also perform the mesenchymal mode but in a distinct manner than tumor cells, and they naturally adapt their migration mode to the environmental constraints.

  1. Structure of the Response Regulator NsrR from Streptococcus agalactiae, Which Is Involved in Lantibiotic Resistance.

    Directory of Open Access Journals (Sweden)

    Sakshi Khosa

    Full Text Available Lantibiotics are antimicrobial peptides produced by Gram-positive bacteria. Interestingly, several clinically relevant and human pathogenic strains are inherently resistant towards lantibiotics. The expression of the genes responsible for lantibiotic resistance is regulated by a specific two-component system consisting of a histidine kinase and a response regulator. Here, we focused on a response regulator involved in lantibiotic resistance, NsrR from Streptococcus agalactiae, and determined the crystal structures of its N-terminal receiver domain and C-terminal DNA-binding effector domain. The C-terminal domain exhibits a fold that classifies NsrR as a member of the OmpR/PhoB subfamily of regulators. Amino acids involved in phosphorylation, dimerization, and DNA-binding were identified and demonstrated to be conserved in lantibiotic resistance regulators. Finally, a model of the full-length NsrR in the active and inactive state provides insights into protein dimerization and DNA-binding.

  2. The Crystal Structure and Mechanism of an Unusual Oxidoreductase, GilR, Involved in Gilvocarcin V Biosynthesis

    Energy Technology Data Exchange (ETDEWEB)

    Noinaj, Nicholas; Bosserman, Mary A.; Schickli, M. Alexandra; Piszczek, Grzegorz; Kharel, Madan K.; Pahari, Pallab; Buchanan, Susan K.; Rohr, Jürgen (NIH); (Kentucky)

    2012-11-26

    GilR is a recently identified oxidoreductase that catalyzes the terminal step of gilvocarcin V biosynthesis and is a unique enzyme that establishes the lactone core of the polyketide-derived gilvocarcin chromophore. Gilvocarcin-type compounds form a small distinct family of anticancer agents that are involved in both photo-activated DNA-alkylation and histone H3 cross-linking. High resolution crystal structures of apoGilR and GilR in complex with its substrate pregilvocarcin V reveals that GilR belongs to the small group of a relatively new type of the vanillyl-alcohol oxidase flavoprotein family characterized by bicovalently tethered cofactors. GilR was found as a dimer, with the bicovalently attached FAD cofactor mediated through His-65 and Cys-125. Subsequent mutagenesis and functional assays indicate that Tyr-445 may be involved in reaction catalysis and in mediating the covalent attachment of FAD, whereas Tyr-448 serves as an essential residue initiating the catalysis by swinging away from the active site to accommodate binding of the 6R-configured substrate and consequently abstracting the proton of the hydroxyl residue of the substrate hemiacetal 6-OH group. These studies lay the groundwork for future enzyme engineering to broaden the substrate specificity of this bottleneck enzyme of the gilvocarcin biosynthetic pathway for the development of novel anti-cancer therapeutics.

  3. Adaptive neural control of MIMO nonlinear systems with a block-triangular pure-feedback control structure.

    Science.gov (United States)

    Chen, Zhenfeng; Ge, Shuzhi Sam; Zhang, Yun; Li, Yanan

    2014-11-01

    This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. All subsystems within these MIMO nonlinear systems are of completely nonaffine pure-feedback form and allowed to have different orders. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. Such a design procedure can remove the couplings among subsystems and hence avoids the possible circular control construction problem. As a consequence, all the signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Moreover, the outputs of the systems are ensured to converge to a small neighborhood of the desired trajectories. Simulation studies verify the theoretical findings revealed in this paper.

  4. Crystal structure of human importin-α1 (Rch1, revealing a potential autoinhibition mode involving homodimerization.

    Directory of Open Access Journals (Sweden)

    Hideyuki Miyatake

    Full Text Available In this study, we determined the crystal structure of N-terminal importin-β-binding domain (IBB-truncated human importin-α1 (ΔIBB-h-importin-α1 at 2.63 Å resolution. The crystal structure of ΔIBB-h-importin-α1 reveals a novel closed homodimer. The homodimer exists in an autoinhibited state in which both the major and minor nuclear localization signal (NLS binding sites are completely buried in the homodimerization interface, an arrangement that restricts NLS binding. Analytical ultracentrifugation studies revealed that ΔIBB-h-importin-α1 is in equilibrium between monomers and dimers and that NLS peptides shifted the equilibrium toward the monomer side. This finding suggests that the NLS binding sites are also involved in the dimer interface in solution. These results show that when the IBB domain dissociates from the internal NLS binding sites, e.g., by binding to importin-β, homodimerization possibly occurs as an autoinhibition state.

  5. Involvement and structure: a qualitative study of organizational change and sickness absence among women in the public sector in Sweden.

    Science.gov (United States)

    Baltzer, Maria; Westerlund, Hugo; Backhans, Mona; Melinder, Karin

    2011-05-16

    Organizational changes in modern corporate life have become increasingly common and there are indications that they often fail to achieve their ends. An earlier study of 24,036 employees showed that those who had repeatedly been exposed to large increases in staffing during 1991-1996 had an excess risk of both long-term sickness absence and hospital admission during 1997-1999, while moderate expansion appeared to be protective. The former was most salient among female public sector employees. We used qualitative interviews to explore work environment factors underlying the impact of organizational changes (moderate and large expansions in staffing) on sickness absence from an employee perspective. We interviewed 21 strategically selected women from the earlier study using semi-structured telephone interviews focusing on working conditions during the organizational changes. We identified 22 themes which could explain the association between organizational changes and sickness absence. We then used Qualitative Comparative Analysis (QCA) to reduce the number of themes and discover patterns of possible causation. The themes that most readily explained the outcomes were Well Planned Process of Change (a clear structure for involvement of the employees in the changes), Agent of Change (an active role in the implementation of the changes), Unregulated Work (a lack of clear limits and guidelines regarding work tasks from the management and among the employees), and Humiliating Position (feelings of low status or of not being wanted at the workplace), which had been salient throughout the analytic process, in combination with Multiple Contexts (working in several teams in parallel) and Already Ill (having already had a debilitating illness at the beginning of 1991), which may indicate degree of individual exposure and vulnerability. Well Planned Process of Change, Agent of Change and Multiple Contexts are themes that were associated with low sickness absence. Unregulated

  6. Involvement and structure: A qualitative study of organizational change and sickness absence among women in the public sector in Sweden

    Directory of Open Access Journals (Sweden)

    Backhans Mona

    2011-05-01

    Full Text Available Abstract Background Organizational changes in modern corporate life have become increasingly common and there are indications that they often fail to achieve their ends. An earlier study of 24,036 employees showed that those who had repeatedly been exposed to large increases in staffing during 1991-1996 had an excess risk of both long-term sickness absence and hospital admission during 1997-1999, while moderate expansion appeared to be protective. The former was most salient among female public sector employees. We used qualitative interviews to explore work environment factors underlying the impact of organizational changes (moderate and large expansions in staffing on sickness absence from an employee perspective. Method We interviewed 21 strategically selected women from the earlier study using semi-structured telephone interviews focusing on working conditions during the organizational changes. We identified 22 themes which could explain the association between organizational changes and sickness absence. We then used Qualitative Comparative Analysis (QCA to reduce the number of themes and discover patterns of possible causation. Results The themes that most readily explained the outcomes were Well Planned Process of Change (a clear structure for involvement of the employees in the changes, Agent of Change (an active role in the implementation of the changes, Unregulated Work (a lack of clear limits and guidelines regarding work tasks from the management and among the employees, and Humiliating Position (feelings of low status or of not being wanted at the workplace, which had been salient throughout the analytic process, in combination with Multiple Contexts (working in several teams in parallel and Already Ill (having already had a debilitating illness at the beginning of 1991, which may indicate degree of individual exposure and vulnerability. Well Planned Process of Change, Agent of Change and Multiple Contexts are themes that were

  7. The neural basis of monitoring goal progress

    Directory of Open Access Journals (Sweden)

    Yael eBenn

    2014-09-01

    Full Text Available The neural basis of progress monitoring has received relatively little attention compared to other sub-processes that are involved in goal directed behavior such as motor control and response inhibition. Studies of error-monitoring have identified the dorsal anterior cingulate cortex (dACC as a structure that is sensitive to conflict detection, and triggers corrective action. However, monitoring goal progress involves monitoring correct as well as erroneous events over a period of time. In the present research, 20 healthy participants underwent fMRI while playing a game that involved monitoring progress towards either a numerical or a visuo-spatial target. The findings confirmed the role of the dACC in detecting situations in which the current state may conflict with the desired state, but also revealed activations in the frontal and parietal regions, pointing to the involvement of processes such as attention and working memory in monitoring progress over time. In addition, activation of the cuneus was associated with monitoring progress towards a specific target presented in the visual modality. This is the first time that activation in this region has been linked to higher-order processing of goal-relevant information, rather than low-level anticipation of visual stimuli. Taken together, these findings identify the neural substrates involved in monitoring progress over time, and how these extend beyond activations observed in conflict and error monitoring.

  8. Crystal structure of the (R)-specific enoyl-CoA hydratase from Aeromonas caviae involved in polyhydroxyalkanoate biosynthesis.

    Science.gov (United States)

    Hisano, Tamao; Tsuge, Takeharu; Fukui, Toshiaki; Iwata, Tadahisa; Miki, Kunio; Doi, Yoshiharu

    2003-01-03

    The (R)-specific enoyl coenzyme A hydratase ((R)-hydratase) from Aeromonas caviae catalyzes the addition of a water molecule to trans-2-enoyl coenzyme A (CoA), with a chain-length of 4-6 carbons, to produce the corresponding (R)-3-hydroxyacyl-CoA. It forms a dimer of identical subunits with a molecular weight of about 14,000 and is involved in polyhydroxyalkanoate (PHA) biosynthesis. The crystal structure of the enzyme has been determined at 1.5-A resolution. The structure of the monomer consists of a five-stranded antiparallel beta-sheet and a central alpha-helix, folded into a so-called "hot dog" fold, with an overhanging segment. This overhang contains the conserved residues including the hydratase 2 motif residues. In dimeric form, two beta-sheets are associated to form an extended 10-stranded beta-sheet, and the overhangs obscure the putative active sites at the subunit interface. The active site is located deep within the substrate-binding tunnel, where Asp(31) and His(36) form a catalytic dyad. These residues are catalytically important as confirmed by site-directed mutagenesis and are possibly responsible for the activation of a water molecule and the protonation of a substrate molecule, respectively. Residues such as Leu(65) and Val(130) are situated at the bottom of the substrate-binding tunnel, defining the preference of the enzyme for the chain length of the substrate. These results provide target residues for protein engineering, which will enhance the significance of this enzyme in the production of novel PHA polymers. In addition, this study provides the first structural information of the (R)-hydratase family and may facilitate further functional studies for members of the family.

  9. Can micro-imaging based analysis methods quantify structural integrity of rat vertebrae with and without metastatic involvement?

    Science.gov (United States)

    Hojjat, Seyed-Parsa; Beek, Maarten; Akens, Margarete K; Whyne, Cari M

    2012-09-21

    This study compares the ability of μCT image-based registration, 2D structural rigidity analyses and multimodal continuum-level finite element (FE) modeling in evaluating the mechanical stability of healthy, osteolytic, and mixed osteolytic/osteoblastic metastatically involved rat vertebrae. μMR and μCT images (loaded and unloaded) were acquired of lumbar spinal motion segments from 15rnu/rnu rats (five per group). Strains were calculated based on image registration of the loaded and unloaded μCT images and via analysis of FE models created from the μCT and μMR data. Predicted yield load was also calculated through 2D structural rigidity analysis of the axial unloaded μCT slices. Measures from the three techniques were compared to experimental yield loads. The ability of these methods to predict experimental yield loads were evaluated and image registration and FE calculated strains were directly compared. Quantitatively for all samples, only limited weak correlations were found between the image-based measures and experimental yield load. In comparison to the experimental yield load, we observed a trend toward a weak negative correlation with median strain calculated using the image-based strain measurement algorithm (r=-0.405, p=0.067), weak significant correlations (pmodes of failure. Improvements in load characterization, material properties assignments and resolution are necessary to yield a more generalized ability for image-based registration, structural rigidity and FE methods to accurately represent stability in healthy and pathologic scenarios. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  11. Methodology of Neural Design: Applications in Microwave Engineering

    OpenAIRE

    Z. Raida; P. Pomenka

    2006-01-01

    In the paper, an original methodology for the automatic creation of neural models of microwave structures is proposed and verified. Following the methodology, neural models of the prescribed accuracy are built within the minimum CPU time. Validity of the proposed methodology is verified by developing neural models of selected microwave structures. Functionality of neural models is verified in a design - a neural model is joined with a genetic algorithm to find a global minimum of a formulat...

  12. Computationally efficient locally-recurrent neural networks for online signal processing

    CERN Document Server

    Hussain, A; Shim, I

    1999-01-01

    A general class of computationally efficient locally recurrent networks (CERN) is described for real-time adaptive signal processing. The structure of the CERN is based on linear-in-the- parameters single-hidden-layered feedforward neural networks such as the radial basis function (RBF) network, the Volterra neural network (VNN) and the functionally expanded neural network (FENN), adapted to employ local output feedback. The corresponding learning algorithms are derived and key structural and computational complexity comparisons are made between the CERN and conventional recurrent neural networks. Two case studies are performed involving the real- time adaptive nonlinear prediction of real-world chaotic, highly non- stationary laser time series and an actual speech signal, which show that a recurrent FENN based adaptive CERN predictor can significantly outperform the corresponding feedforward FENN and conventionally employed linear adaptive filtering models. (13 refs).

  13. What are artificial neural networks?

    DEFF Research Database (Denmark)

    Krogh, Anders

    2008-01-01

    Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...

  14. Application of the artificial neural network for reconstructing the internal-structure image of a random medium by spatial characteristics of backscattered optical radiation

    Science.gov (United States)

    Veksler, B. A.; Meglinskii, I. V.

    2008-06-01

    The feasibility of using an artificial neural network (ANN), which is the standard Matlab tool, for non-invasive (based on the data of backscattering) diagnostics of macro-inhomogeneities, localised at subsurface layers of the turbid strongly scattering medium was shown. The spatial and angle distribution of the backscattered optical radiation was calculated by using the Monte-Carlo method combining the modelling of effective optical paths and the use of statistical weights. It was shown that application of the backscattering method together with the ANN allows solving inverse problems for determining the average radius of the scattering particles and for reconstructing the images of structural elements within the medium with a high accuracy.

  15. Quantitative Structure-Activity Relationships of Noncompetitive Antagonists of the NMDA Receptor: A Study of a Series of MK801 Derivative Molecules Using Statistical Methods and Neural Network

    Directory of Open Access Journals (Sweden)

    T. Lakhlifi

    2003-04-01

    Full Text Available Abstract: From a series of 50 MK801 derivative molecules, a selected set of 44 compounds was submitted to a principal components analysis (PCA, a multiple regression analysis (MRA, and a neural network (NN. This study shows that the compounds' activity correlates reasonably well with the selected descriptors encoding the chemical structures. The correlation coefficients calculated by MRA and there after by NN, r = 0.986 and r = 0.974 respectively, are fairly good to evaluate a quantitative model, and to predict activity for MK801 derivatives. To test the performance of this model, the activities of the remained set of 6 compounds are deduced from the proposed quantitative model, by NN. This study proved that the predictive power of this model is relevant.

  16. Optimizing finite element predictions of local subchondral bone structural stiffness using neural network-derived density-modulus relationships for proximal tibial subchondral cortical and trabecular bone.

    Science.gov (United States)

    Nazemi, S Majid; Amini, Morteza; Kontulainen, Saija A; Milner, Jaques S; Holdsworth, David W; Masri, Bassam A; Wilson, David R; Johnston, James D

    2017-01-01

    Quantitative computed tomography based subject-specific finite element modeling has potential to clarify the role of subchondral bone alterations in knee osteoarthritis initiation, progression, and pain. However, it is unclear what density-modulus equation(s) should be applied with subchondral cortical and subchondral trabecular bone when constructing finite element models of the tibia. Using a novel approach applying neural networks, optimization, and back-calculation against in situ experimental testing results, the objective of this study was to identify subchondral-specific equations that optimized finite element predictions of local structural stiffness at the proximal tibial subchondral surface. Thirteen proximal tibial compartments were imaged via quantitative computed tomography. Imaged bone mineral density was converted to elastic moduli using multiple density-modulus equations (93 total variations) then mapped to corresponding finite element models. For each variation, root mean squared error was calculated between finite element prediction and in situ measured stiffness at 47 indentation sites. Resulting errors were used to train an artificial neural network, which provided an unlimited number of model variations, with corresponding error, for predicting stiffness at the subchondral bone surface. Nelder-Mead optimization was used to identify optimum density-modulus equations for predicting stiffness. Finite element modeling predicted 81% of experimental stiffness variance (with 10.5% error) using optimized equations for subchondral cortical and trabecular bone differentiated with a 0.5g/cm(3) density. In comparison with published density-modulus relationships, optimized equations offered improved predictions of local subchondral structural stiffness. Further research is needed with anisotropy inclusion, a smaller voxel size and de-blurring algorithms to improve predictions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Neural Computations in Binaural Hearing

    Science.gov (United States)

    Wagner, Hermann

    Binaural hearing helps humans and animals to localize and unmask sounds. Here, binaural computations in the barn owl's auditory system are discussed. Barn owls use the interaural time difference (ITD) for azimuthal sound localization, and they use the interaural level difference (ELD) for elevational sound localization. ITD and ILD and their precursors are processed in separate neural pathways, the time pathway and the intensity pathway, respectively. Representation of ITD involves four main computational steps, while the representation of ILD is accomplished in three steps. In the discussion neural processing in the owl's auditory system is compared with neural computations present in mammals.

  18. Modulation of Hippocampal Neural Plasticity by Glucose-Related Signaling

    OpenAIRE

    Marco Mainardi; Salvatore Fusco; Claudio Grassi

    2015-01-01

    Hormones and peptides involved in glucose homeostasis are emerging as important modulators of neural plasticity. In this regard, increasing evidence shows that molecules such as insulin, insulin-like growth factor-I, glucagon-like peptide-1, and ghrelin impact on the function of the hippocampus, which is a key area for learning and memory. Indeed, all these factors affect fundamental hippocampal properties including synaptic plasticity (i.e., synapse potentiation and depression), structural p...

  19. The Neural Correlates of Race

    Science.gov (United States)

    Ito, Tiffany A.; Bartholow, Bruce D.

    2009-01-01

    Behavioral analyses are a natural choice for understanding the wide-ranging behavioral consequences of racial stereotyping and prejudice. However, neuroimaging and electrophysiological research has recently considered the neural mechanisms that underlie racial categorization and the activation and application of racial stereotypes and prejudice, revealing exciting new insights. Work reviewed here points to the importance of neural structures previously associated with face processing, semantic knowledge activation, evaluation, and self-regulatory behavioral control, allowing for the specification of a neural model of race processing. We show how research on the neural correlates of race can serve to link otherwise disparate lines of evidence on the neural underpinnings of a broad array of social-cognitive phenomena, and consider implications for effecting change in race relations. PMID:19896410

  20. Neural-like growing networks

    Science.gov (United States)

    Yashchenko, Vitaliy A.

    2000-03-01

    On the basis of the analysis of scientific ideas reflecting the law in the structure and functioning the biological structures of a brain, and analysis and synthesis of knowledge, developed by various directions in Computer Science, also there were developed the bases of the theory of a new class neural-like growing networks, not having the analogue in world practice. In a base of neural-like growing networks the synthesis of knowledge developed by classical theories - semantic and neural of networks is. The first of them enable to form sense, as objects and connections between them in accordance with construction of the network. With thus each sense gets a separate a component of a network as top, connected to other tops. In common it quite corresponds to structure reflected in a brain, where each obvious concept is presented by certain structure and has designating symbol. Secondly, this network gets increased semantic clearness at the expense owing to formation not only connections between neural by elements, but also themselves of elements as such, i.e. here has a place not simply construction of a network by accommodation sense structures in environment neural of elements, and purely creation of most this environment, as of an equivalent of environment of memory. Thus neural-like growing networks are represented by the convenient apparatus for modeling of mechanisms of teleological thinking, as a fulfillment of certain psychophysiological of functions.

  1. Application of electrical capacitance tomography and artificial neural networks to rapid estimation of cylindrical shape parameters of industrial flow structure

    Directory of Open Access Journals (Sweden)

    Garbaa Hela

    2016-12-01

    Full Text Available A new approach to solve the inverse problem in electrical capacitance tomography is presented. The proposed method is based on an artificial neural network to estimate three different parameters of a circular object present inside a pipeline, i.e. radius and 2D position coordinates. This information allows the estimation of the distribution of material inside a pipe and determination of the characteristic parameters of a range of flows, which are characterised by a circular objects emerging within a cross section such as funnel flow in a silo gravitational discharging process. The main advantages of the proposed approach are explicitly: the desired characteristic flow parameters are estimated directly from the measured capacitances and rapidity, which in turn is crucial for online flow monitoring. In a classic approach in order to obtain these parameters in the first step the image is reconstructed and then the parameters are estimated with the use of image processing methods. The obtained results showed significant reduction of computations time in comparison to the iterative LBP or Levenberg-Marquard algorithms.

  2. Protection of Melanized Cryptococcus neoformans from Lethal Dose Gamma Irradiation Involves Changes in Melanin's Chemical Structure and Paramagnetism

    Science.gov (United States)

    Khajo, Abdelahad; Bryan, Ruth A.; Friedman, Matthew; Burger, Richard M.; Levitsky, Yan; Casadevall, Arturo; Magliozzo, Richard S.; Dadachova, Ekaterina

    2011-01-01

    Certain fungi thrive in highly radioactive environments including the defunct Chernobyl nuclear reactor. Cryptococcus neoformans (C. neoformans), which uses L-3,4-dihydroxyphenylalanine (L-DOPA) to produce melanin, was used here to investigate how gamma radiation under aqueous aerobic conditions affects the properties of melanin, with the aim of gaining insight into its radioprotective role. Exposure of melanized fungal cell in aqueous suspensions to doses of γ-radiation capable of killing 50 to 80% of the cells did not lead to a detectable loss of melanin integrity according to EPR spectra of melanin radicals. Moreover, upon UV-visible (Xe-lamp) illumination of melanized cells, the increase in radical population was unchanged after γ-irradiation. Gamma-irradiation of frozen cell suspensions and storage of samples for several days at 77 K however, produced melanin modification noted by a reduced radical population and reduced photoresponse. More direct evidence for structural modification of melanin came from the detection of soluble products with absorbance maxima near 260 nm in supernatants collected after γ-irradiation of cells and cell-free melanin. These products, which include thiobarbituric acid (TBA)-reactive aldehydes, were also generated by Fenton reagent treatment of cells and cell-free melanin. In an assay of melanin integrity based on the metal (Bi+3) binding capacity of cells, no detectable loss in binding was detected after γ-irradiation. Our results show that melanin in C. neoformans cells is susceptible to some damage by hydroxyl radical formed in lethal radioactive aqueous environments and serves a protective role in melanized fungi that involves sacrificial breakdown. PMID:21966422

  3. Protection of melanized Cryptococcus neoformans from lethal dose gamma irradiation involves changes in melanin's chemical structure and paramagnetism.

    Directory of Open Access Journals (Sweden)

    Abdelahad Khajo

    Full Text Available Certain fungi thrive in highly radioactive environments including the defunct Chernobyl nuclear reactor. Cryptococcus neoformans (C. neoformans, which uses L-3,4-dihydroxyphenylalanine (L-DOPA to produce melanin, was used here to investigate how gamma radiation under aqueous aerobic conditions affects the properties of melanin, with the aim of gaining insight into its radioprotective role. Exposure of melanized fungal cell in aqueous suspensions to doses of γ-radiation capable of killing 50 to 80% of the cells did not lead to a detectable loss of melanin integrity according to EPR spectra of melanin radicals. Moreover, upon UV-visible (Xe-lamp illumination of melanized cells, the increase in radical population was unchanged after γ-irradiation. Gamma-irradiation of frozen cell suspensions and storage of samples for several days at 77 K however, produced melanin modification noted by a reduced radical population and reduced photoresponse. More direct evidence for structural modification of melanin came from the detection of soluble products with absorbance maxima near 260 nm in supernatants collected after γ-irradiation of cells and cell-free melanin. These products, which include thiobarbituric acid (TBA-reactive aldehydes, were also generated by Fenton reagent treatment of cells and cell-free melanin. In an assay of melanin integrity based on the metal (Bi(+3 binding capacity of cells, no detectable loss in binding was detected after γ-irradiation. Our results show that melanin in C. neoformans cells is susceptible to some damage by hydroxyl radical formed in lethal radioactive aqueous environments and serves a protective role in melanized fungi that involves sacrificial breakdown.

  4. Projection learning algorithm for threshold - controlled neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Reznik, A.M.

    1995-03-01

    The projection learning algorithm proposed in [1, 2] and further developed in [3] substantially improves the efficiency of memorizing information and accelerates the learning process in neural networks. This algorithm is compatible with the completely connected neural network architecture (the Hopfield network [4]), but its application to other networks involves a number of difficulties. The main difficulties include constraints on interconnection structure and the need to eliminate the state uncertainty of latent neurons if such are present in the network. Despite the encouraging preliminary results of [3], further extension of the applications of the projection algorithm therefore remains problematic. In this paper, which is a continuation of the work begun in [3], we consider threshold-controlled neural networks. Networks of this type are quite common. They represent the receptor neuron layers in some neurocomputer designs. A similar structure is observed in the lower divisions of biological sensory systems [5]. In multilayer projection neural networks with lateral interconnections, the neuron layers or parts of these layers may also have the structure of a threshold-controlled completely connected network. Here the thresholds are the potentials delivered through the projection connections from other parts of the network. The extension of the projection algorithm to the class of threshold-controlled networks may accordingly prove to be useful both for extending its technical applications and for better understanding of the operation of the nervous system in living organisms.

  5. Neural network approach to parton distributions fitting

    CERN Document Server

    Piccione, Andrea; Forte, Stefano; Latorre, Jose I.; Rojo, Joan; Piccione, Andrea; Rojo, Joan

    2006-01-01

    We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on each Monte Carlo replica via a genetic algorithm. Results on the proton and deuteron structure functions, and on the nonsinglet parton distribution will be shown.

  6. Neural Networks for Non-linear Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1994-01-01

    This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process.......This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process....

  7. A Fuzzy Neural Tree for Possibilistic Reliability

    NARCIS (Netherlands)

    Ciftcioglu, O.

    2008-01-01

    An innovative neural fuzzy system is considered for possibilistic reliability using a neural tree structure with nodes of neuronal type. The total tree structure works effectively as a fuzzy logic system where the possibility theory plays important role with Gaussian possibility distribution at the

  8. Biologically Inspired Modular Neural Networks

    OpenAIRE

    Azam, Farooq

    2000-01-01

    This dissertation explores the modular learning in artificial neural networks that mainly driven by the inspiration from the neurobiological basis of the human learning. The presented modularization approaches to the neural network design and learning are inspired by the engineering, complexity, psychological and neurobiological aspects. The main theme of this dissertation is to explore the organization and functioning of the brain to discover new structural and learning ...

  9. Musical experts recruit action-related neural structures in harmonic anomaly detection: evidence for embodied cognition in expertise.

    Science.gov (United States)

    Sherwin, Jason; Sajda, Paul

    2013-11-01

    Humans are extremely good at detecting anomalies in sensory input. For example, while listening to a piece of Western-style music, an anomalous key change or an out-of-key pitch is readily apparent, even to the non-musician. In this paper we investigate differences between musical experts and non-experts during musical anomaly detection. Specifically, we analyzed the electroencephalograms (EEG) of five expert cello players and five non-musicians while they listened to excerpts of J.S. Bach's Prelude from Cello Suite No. 1. All subjects were familiar with the piece, though experts also had extensive experience playing the piece. Subjects were told that anomalous musical events (AMEs) could occur at random within the excerpts of the piece and were told to report the number of AMEs after each excerpt. Furthermore, subjects were instructed to remain still while listening to the excerpts and their lack of movement was verified via visual and EEG monitoring. Experts had significantly better behavioral performance (i.e. correctly reporting AME counts) than non-experts, though both groups had mean accuracies greater than 80%. These group differences were also reflected in the EEG correlates of key-change detection post-stimulus, with experts showing more significant, greater magnitude, longer periods of, and earlier peaks in condition-discriminating EEG activity than novices. Using the timing of the maximum discriminating neural correlates, we performed source reconstruction and compared significant differences between cellists and non-musicians. We found significant differences that included a slightly right lateralized motor and frontal source distribution. The right lateralized motor activation is consistent with the cortical representation of the left hand - i.e. the hand a cellist would use, while playing, to generate the anomalous key-changes. In general, these results suggest that sensory anomalies detected by experts may in fact be partially a result of an embodied

  10. Developing a Graphical User Interface to Automate the Estimation and Prediction of Risk Values for Flood Protective Structures using Artificial Neural Network

    Science.gov (United States)

    Hasan, M.; Helal, A.; Gabr, M.

    2014-12-01

    In this project, we focus on providing a computer-automated platform for a better assessment of the potential failures and retrofit measures of flood-protecting earth structures, e.g., dams and levees. Such structures play an important role during extreme flooding events as well as during normal operating conditions. Furthermore, they are part of other civil infrastructures such as water storage and hydropower generation. Hence, there is a clear need for accurate evaluation of stability and functionality levels during their service lifetime so that the rehabilitation and maintenance costs are effectively guided. Among condition assessment approaches based on the factor of safety, the limit states (LS) approach utilizes numerical modeling to quantify the probability of potential failures. The parameters for LS numerical modeling include i) geometry and side slopes of the embankment, ii) loading conditions in terms of rate of rising and duration of high water levels in the reservoir, and iii) cycles of rising and falling water levels simulating the effect of consecutive storms throughout the service life of the structure. Sample data regarding the correlations of these parameters are available through previous research studies. We have unified these criteria and extended the risk assessment in term of loss of life through the implementation of a graphical user interface to automate input parameters that divides data into training and testing sets, and then feeds them into Artificial Neural Network (ANN) tool through MATLAB programming. The ANN modeling allows us to predict risk values of flood protective structures based on user feedback quickly and easily. In future, we expect to fine-tune the software by adding extensive data on variations of parameters.

  11. Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

  12. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  13. Middle manager involvement in strategy development in not-for profit organizations: the director of nursing perspective--how organizational structure impacts on the role.

    Science.gov (United States)

    Carney, M

    2004-01-01

    An attempt was made to link organizational structure and strategic management and, in the process, to identify how organizational structure impacts on the strategic management role of Directors of Nursing working in acute care hospitals in the Republic of Ireland. Directors of Nursing are recognized as holding a pivotal role in health care delivery. The need for their involvement in strategic management is acknowledged, yet it is not clear if this role is influenced by organizational structure. It is recognized that strategic involvement increases the likelihood that middle managers' initiatives will be in line with top management's concept of corporate strategy. The principal thesis is that organizational members will exercise a higher level of strategic consensus if they have been initially involved in the development of strategy. The study was undertaken in not-for-profit health service organizations, through a series of 25 semi-structured interviews with Directors of Nursing. The review of the literature was undertaken simultaneously with grounded theory analysis of the interviews. This research suggests that structure does impact on the role, conferring both positive benefits and negative consequences. Structure is identified in this study, in terms of organizational hierarchy, and the locus of control pertaining in each organization. Two predominating structure models are discussed and analysed.

  14. Locomotor activation by theacrine, a purine alkaloid structurally similar to caffeine: involvement of adenosine and dopamine receptors.

    Science.gov (United States)

    Feduccia, Allison A; Wang, Yuanyuan; Simms, Jeffrey A; Yi, Henry Y; Li, Rui; Bjeldanes, Leonard; Ye, Chuangxing; Bartlett, Selena E

    2012-08-01

    Purine compounds, such as caffeine, have many health-promoting properties and have proven to be beneficial in treating a number of different conditions. Theacrine, a purine alkaloid structurally similar to caffeine and abundantly present in Camellia kucha, has recently become of interest as a potential therapeutic compound. In the present study, theacrine was tested using a rodent behavioral model to investigate the effects of the drug on locomotor activity. Long Evans rats were injected with theacrine (24 or 48 mg/kg, i.p.) and activity levels were measured. Results showed that the highest dose of theacrine (48 mg/kg, i.p.) significantly increased locomotor activity compared to control animals and activity remained elevated throughout the duration of the session. To test for the involvement of adenosine receptors underlying theacrine's motor-activating properties, rats were administered a cocktail of the adenosine A₁ agonist, N⁶-cyclopentyladenosine (CPA; 0.1 mg/kg, i.p.) and A(2A) receptor agonist 2-p-(2-carboxyethyl)phenethylamino-5'-N-ethylcarboxamidoadenosine (CGS-21680; 0.2 mg/kg, i.p.). Pre-treatment with theacrine significantly attenuated the motor depression induced by the adenosine receptor agonists, indicating that theacrine is likely acting as an adenosine receptor antagonist. Next, we examined the role of DA D₁ and D₂ receptor antagonism on theacrine-induced hyperlocomotion. Both antagonists, D₁R SCH23390 (0.1 or 0.05 mg/kg, i.p.) and D₂R eticlopride (0.1 mg/kg, i.p.), significantly reduced theacrine-stimulated activity indicating that this behavioral response, at least in part, is mediated by DA receptors. In order to investigate the brain region where theacrine may be acting, the drug (10 or 20 μg) was infused bilaterally into nucleus accumbens (NAc). Theacrine enhanced activity levels in a dose-dependent manner, implicating a role of the NAc in modulating theacrine's effects on locomotion. In addition, theacrine did not induce locomotor

  15. Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

    Science.gov (United States)

    Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

    2017-08-01

    Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar

  16. The influence of sensation-seeking and parental and peer influences in early adolescence on risk involvement through middle adolescence: A structural equation modeling analysis.

    Science.gov (United States)

    Wang, Bo; Deveaux, Lynette; Lunn, Sonja; Dinaj-Koci, Veronica; Li, Xiaoming; Stanton, Bonita

    2016-03-01

    This study examined the relationships between youth and parental sensation-seeking, peer influence, parental monitoring and youth risk involvement in adolescence using structural equation modeling. Beginning in grade-six, longitudinal data were collected from 543 students over three years. Youth sensation-seeking in grade six contributed to risk involvement in early adolescence (grades six and seven) indirectly through increased peer risk influence and decreased parental monitoring but did not have a direct contribution. It contributed directly and indirectly to risk involvement in middle adolescence (grades eight and nine). Parent sensation-seeking at baseline was positively associated with peer risk influence and negatively associated with parental monitoring; it had no direct effect on adolescent risk involvement. Parental monitoring buffers negative peer influence on adolescent risk involvement. Results highlight the need for intervention efforts to provide normative feedback about adolescent risky behaviors and to vary among families in which parents and/or youth have high sensation-seeking propensities.

  17. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  18. Principal Component Analysis Coupled with Artificial Neural Networks—A Combined Technique Classifying Small Molecular Structures Using a Concatenated Spectral Database

    Directory of Open Access Journals (Sweden)

    Mihail Lucian Birsa

    2011-10-01

    Full Text Available In this paper we present several expert systems that predict the class identity of the modeled compounds, based on a preprocessed spectral database. The expert systems were built using Artificial Neural Networks (ANN and are designed to predict if an unknown compound has the toxicological activity of amphetamines (stimulant and hallucinogen, or whether it is a nonamphetamine. In attempts to circumvent the laws controlling drugs of abuse, new chemical structures are very frequently introduced on the black market. They are obtained by slightly modifying the controlled molecular structures by adding or changing substituents at various positions on the banned molecules. As a result, no substance similar to those forming a prohibited class may be used nowadays, even if it has not been specifically listed. Therefore, reliable, fast and accessible systems capable of modeling and then identifying similarities at molecular level, are highly needed for epidemiological, clinical, and forensic purposes. In order to obtain the expert systems, we have preprocessed a concatenated spectral database, representing the GC-FTIR (gas chromatography-Fourier transform infrared spectrometry and GC-MS (gas chromatography-mass spectrometry spectra of 103 forensic compounds. The database was used as input for a Principal Component Analysis (PCA. The scores of the forensic compounds on the main principal components (PCs were then used as inputs for the ANN systems. We have built eight PC-ANN systems (principal component analysis coupled with artificial neural network with a different number of input variables: 15 PCs, 16 PCs, 17 PCs, 18 PCs, 19 PCs, 20 PCs, 21 PCs and 22 PCs. The best expert system was found to be the ANN network built with 18 PCs, which accounts for an explained variance of 77%. This expert system has the best sensitivity (a rate of classification C = 100% and a rate of true positives TP = 100%, as well as a good selectivity (a rate of true negatives TN

  19. The neural cell adhesion molecule

    DEFF Research Database (Denmark)

    Berezin, V; Bock, E; Poulsen, F M

    2000-01-01

    During the past year, the understanding of the structure and function of neural cell adhesion has advanced considerably. The three-dimensional structures of several of the individual modules of the neural cell adhesion molecule (NCAM) have been determined, as well as the structure of the complex...... between two identical fragments of the NCAM. Also during the past year, a link between homophilic cell adhesion and several signal transduction pathways has been proposed, connecting the event of cell surface adhesion to cellular responses such as neurite outgrowth. Finally, the stimulation of neurite...

  20. Structural and functional characterization of CSDA protein complexes involved in the modulation of fetal globin gene expression

    OpenAIRE

    Gaudino, Sara

    2009-01-01

    Impaired switching from fetal hemoglobin (HbF) to adult globin gene expression leads to hereditary persistence of fetal hemoglobin (HPFH) in adult life. This is of prime interest because elevated HbF levels ameliorate beta-thalassemia and sickle cell anemia. Fetal hemoglobin levels are regulated by complex mechanisms involving factors linked or not to the beta-globin gene locus. To search for factors putatively involved in gamma-globin gene expression, we examined the reticulocyte transcripto...

  1. High serotonin levels during brain development alter the structural input-output connectivity of neural networks in the rat somatosensory layer IV

    Directory of Open Access Journals (Sweden)

    Stéphanie eMiceli

    2013-06-01

    Full Text Available Homeostatic regulation of serotonin (5-HT concentration is critical for normal topographical organization and development of thalamocortical (TC afferent circuits. Down-regulation of the serotonin transporter (SERT and the consequent impaired reuptake of 5-HT at the synapse, results in a reduced terminal branching of developing TC afferents within the primary somatosensory cortex (S1. Despite the presence of multiple genetic models, the effect of high extracellular 5-HT levels on the structure and function of developing intracortical neural networks is far from being understood. Here, using juvenile SERT knockout (SERT-/- rats we investigated, in vitro, the effect of increased 5-HT levels on the structural organization of (i the thalamocortical projections of the ventroposteromedial thalamic nucleus towards S1, (ii the general barrel-field pattern and (iii the electrophysiological and morphological properties of the excitatory cell population in layer IV of S1 (spiny stellate and pyramidal cells. Our results confirmed previous findings that high levels of 5-HT during development lead to a reduction of the topographical precision of TCA projections towards the barrel cortex. Also, the barrel pattern was altered but not abolished in SERT-/- rats. In layer IV, both excitatory spiny stellate and pyramidal cells showed a significantly reduced intracolumnar organization of their axonal projections. In addition, the layer IV spiny stellate cells gave rise to a prominent projection towards the infragranular layer Vb. Our findings point to a structural and functional reorganization, of TCAs, as well as early stage intracortical microcircuitry, following the disruption of 5-HT reuptake during critical developmental periods. The increased projection pattern of the layer IV neurons suggests that the intracortical network changes are not limited to the main entry layer IV but may also affect the subsequent stages of the canonical circuits of the barrel

  2. Neural bases of accented speech perception

    OpenAIRE

    Patti eAdank; Nuttall, Helen E.; Briony eBanks; Dan eKennedy-Higgins

    2015-01-01

    The recognition of unfamiliar regional and foreign accents represents a challenging task for the speech perception system (Adank, Evans, Stuart-Smith, & Scott, 2009; Floccia, Goslin, Girard, & Konopczynski, 2006). Despite the frequency with which we encounter such accents, the neural mechanisms supporting successful perception of accented speech are poorly understood. Nonetheless, candidate neural substrates involved in processing speech in challenging listening conditions, including accented...

  3. The Effects of Perceptions of Organizational Structure on Job Involvement, Job Satisfaction, and Organizational Commitment Among Indian Police Officers.

    Science.gov (United States)

    Lambert, Eric G; Qureshi, Hanif; Klahm, Charles; Smith, Brad; Frank, James

    2017-12-01

    Successful police organizations rely on involved, satisfied, and committed workers. The concepts of job involvement (i.e., connection with the job), job satisfaction (i.e., affective feeling toward the job), and organizational commitment (i.e., bond with the employing organization) have been shown to significantly affect intentions and behaviors of employees. The current study used multivariate ordinary least squares (OLS) regression analysis on survey results from a sample of 827 Indian police officers to explore how perceptions of work environment factors affect officers' job involvement, job satisfaction, and organizational commitment. Organizational support, formalization (i.e., level of codified written rules and guidelines), promotional opportunities, institutional communication (i.e., salient work information is transmitted), and input into decision-making (i.e., having a voice in the process) significantly influenced the job involvement, job satisfaction, and organizational commitment of Indian police officers. Specifically, in the multivariate analysis, perceptions of formalization and instrumental communication had a positive relationship with job involvement; perceptions of organizational support, promotional opportunities, instrumental communication, and input into decision-making had positive associations with job satisfaction; and perceptions of organizational support, formalization, promotional opportunities, instrumental communication, and input into decision-making had positive relationships with organizational commitment.

  4. Structure and Mechanism of Staphylococcus aureus TarS, the Wall Teichoic Acid β-glycosyltransferase Involved in Methicillin Resistance.

    Directory of Open Access Journals (Sweden)

    Solmaz Sobhanifar

    2016-12-01

    Full Text Available In recent years, there has been a growing interest in teichoic acids as targets for antibiotic drug design against major clinical pathogens such as Staphylococcus aureus, reflecting the disquieting increase in antibiotic resistance and the historical success of bacterial cell wall components as drug targets. It is now becoming clear that β-O-GlcNAcylation of S. aureus wall teichoic acids plays a major role in both pathogenicity and antibiotic resistance. Here we present the first structure of S. aureus TarS, the enzyme responsible for polyribitol phosphate β-O-GlcNAcylation. Using a divide and conquer strategy, we obtained crystal structures of various TarS constructs, mapping high resolution overlapping N-terminal and C-terminal structures onto a lower resolution full-length structure that resulted in a high resolution view of the entire enzyme. Using the N-terminal structure that encapsulates the catalytic domain, we furthermore captured several snapshots of TarS, including the native structure, the UDP-GlcNAc donor complex, and the UDP product complex. These structures along with structure-guided mutants allowed us to elucidate various catalytic features and identify key active site residues and catalytic loop rearrangements that provide a valuable platform for anti-MRSA drug design. We furthermore observed for the first time the presence of a trimerization domain composed of stacked carbohydrate binding modules, commonly observed in starch active enzymes, but adapted here for a poly sugar-phosphate glycosyltransferase.

  5. Fathers' Involvement with Their Preschool-Age Children: How Fathers Spend Time with Their Children in Different Family Structures

    Science.gov (United States)

    Halme, Nina; Astedt-Kurki, Paivi; Tarkka, Marja-Terttu

    2009-01-01

    The purpose of this study was to describe how fathers (n = 263) spent time with their preschool-age children and to compare it in different family structures. Data were gathered by structured questionnaires. The instrument included five categories of variables for the time spent: the quantity of time, physical activities, fathers' attitude towards…

  6. Estimation of Effectivty Connectivity via Data-Driven Neural Modeling

    Directory of Open Access Journals (Sweden)

    Dean Robert Freestone

    2014-11-01

    Full Text Available This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used the track the mechanisms involved in seizure initiation and termination.

  7. A Computational Approach From Gene to Structure Analysis of the Human ABCA4 Transporter Involved in Genetic Retinal Diseases.

    Science.gov (United States)

    Trezza, Alfonso; Bernini, Andrea; Langella, Andrea; Ascher, David B; Pires, Douglas E V; Sodi, Andrea; Passerini, Ilaria; Pelo, Elisabetta; Rizzo, Stanislao; Niccolai, Neri; Spiga, Ottavia

    2017-10-01

    The aim of this article is to report the investigation of the structural features of ABCA4, a protein associated with a genetic retinal disease. A new database collecting knowledge of ABCA4 structure may facilitate predictions about the possible functional consequences of gene mutations observed in clinical practice. In order to correlate structural and functional effects of the observed mutations, the structure of mouse P-glycoprotein was used as a template for homology modeling. The obtained structural information and genetic data are the basis of our relational database (ABCA4Database). Sequence variability among all ABCA4-deposited entries was calculated and reported as Shannon entropy score at the residue level. The three-dimensional model of ABCA4 structure was used to locate the spatial distribution of the observed variable regions. Our predictions from structural in silico tools were able to accurately link the functional effects of mutations to phenotype. The development of the ABCA4Database gathers all the available genetic and structural information, yielding a global view of the molecular basis of some retinal diseases. ABCA4 modeled structure provides a molecular basis on which to analyze protein sequence mutations related to genetic retinal disease in order to predict the risk of retinal disease across all possible ABCA4 mutations. Additionally, our ABCA4 predicted structure is a good starting point for the creation of a new data analysis model, appropriate for precision medicine, in order to develop a deeper knowledge network of the disease and to improve the management of patients.

  8. A neural network classifier capable of recognizing the patterns of all major subcellular structures in fluorescence microscope images of HeLa cells.

    Science.gov (United States)

    Boland, M V; Murphy, R F

    2001-12-01

    Assessment of protein subcellular location is crucial to proteomics efforts since localization information provides a context for a protein's sequence, structure, and function. The work described below is the first to address the subcellular localization of proteins in a quantitative, comprehensive manner. Images for ten different subcellular patterns (including all major organelles) were collected using fluorescence microscopy. The patterns were described using a variety of numeric features, including Zernike moments, Haralick texture features, and a set of new features developed specifically for this purpose. To test the usefulness of these features, they were used to train a neural network classifier. The classifier was able to correctly recognize an average of 83% of previously unseen cells showing one of the ten patterns. The same classifier was then used to recognize previously unseen sets of homogeneously prepared cells with 98% accuracy. Algorithms were implemented using the commercial products Matlab, S-Plus, and SAS, as well as some functions written in C. The scripts and source code generated for this work are available at http://murphylab.web.cmu.edu/software. murphy@cmu.edu

  9. Improved predictions of nonlinear support vector regression and artificial neural network models via preprocessing of data with orthogonal projection to latent structures: A case study

    Directory of Open Access Journals (Sweden)

    Ibrahim A. Naguib

    2017-12-01

    Full Text Available In the presented study, orthogonal projection to latent structures (OPLS is introduced as a data preprocessing method that handles nonlinear data prior to modelling with two well established nonlinear multivariate models; namely support vector regression (SVR and artificial neural networks (ANN. The proposed preprocessing proved to significantly improve prediction abilities through removal of uncorrelated data.The study was established based on a case study nonlinear spectrofluorimetric data of agomelatine (AGM and its hydrolysis degradation products (Deg I and Deg II, where a 3 factor 4 level experimental design was used to provide a training set of 16 mixtures with different proportions of studied components. An independent test set which consisted of 9 mixtures was established to confirm the prediction ability of the introduced models. Excitation wavelength was 227 nm, and working range for emission spectra was 320–440 nm.The couplings of OPLS-SVR and OPLS-ANN provided better accuracy for prediction of independent nonlinear test set. The root mean square error of prediction RMSEP for the test set mixtures was used as a major comparison parameter, where RMSEP results for OPLS-SVR and OPLS-ANN are 2.19 and 1.50 respectively. Keywords: Agomelatine, SVR, ANN, OPLS, Spectrofluorimetry, Nonlinear

  10. Resistance of subventricular neural stem cells to chronic hypoxemia despite structural disorganization of the germinal center and impairment of neuronal and oligodendrocyte survival

    Science.gov (United States)

    d’Anglemont de Tassigny, Xavier; Sirerol-Piquer, M Salomé; Gómez-Pinedo, Ulises; Pardal, Ricardo; Bonilla, Sonia; Capilla-Gonzalez, Vivian; López-López, Ivette; De la Torre-Laviana, Francisco Javier; García-Verdugo, José Manuel; López-Barneo, José

    2015-01-01

    Chronic hypoxemia, as evidenced in de-acclimatized high-altitude residents or in patients with chronic obstructive respiratory disorders, is a common medical condition that can produce serious neurological alterations. However, the pathogenesis of this phenomenon is unknown. We have found that adult rodents exposed for several days/weeks to hypoxia, with an arterial oxygen tension similar to that of chronically hypoxemic patients, manifest a partially irreversible structural disarrangement of the subventricular neurogenic niche (subventricular zone) characterized by displacement of neurons and myelinated axons, flattening of the ependymal cell layer, and thinning of capillary walls. Despite these abnormalities, the number of neuronal and oligodendrocyte progenitors, neuroblasts, and neurosphere-forming cells as well as the proliferative activity in subventricular zone was unchanged. These results suggest that neural stem cells and their undifferentiated progeny are resistant to hypoxia. However, in vivo and in vitro experiments indicate that severe chronic hypoxia decreases the survival of newly generated neurons and oligodendrocytes, with damage of myelin sheaths. These findings help explain the effects of hypoxia on adult neurogenesis and provide new perspectives on brain responsiveness to persistent hypoxemia. PMID:27774479

  11. Delta-catenin is required for the maintenance of neural structure and function in mature cortex in vivo

    Science.gov (United States)

    Matter, Cheryl; Pribadi, Mochtar; Liu, Xin; Trachtenberg, Joshua T.

    2009-01-01

    Delta (™)-catenin is a brain specific member of the adherens junction complex that localizes to the post-synaptic and dendritic compartments. This protein is likely critical for normal cognitive function; its hemizygous loss is linked to the severe mental retardation syndrome, Cri-du-Chat, and it directly interacts with Presenilin-1 (PS1), the protein most frequently mutated in familial Alzheimer's disease. Mice lacking normal ™-catenin display severe impairments in learning and memory tasks and synaptic plasticity. Here we examine dendritic structure and cortical function in vivo in mice lacking ™-catenin. We find that in cerebral cortex of 5-week-old mice dendritic complexity, spine density, and cortical responsiveness are similar between mutant and littermate controls; thereafter, mutant mice experience progressive dendritic retraction, a reduction in spine density and stability, and concomitant reductions in cortical responsiveness. Our results indicate that ™-catenin regulates the maintenance of dendrites and dendritic spines in mature cortex but does not appear to be necessary for the initial establishment of these structures during development. PMID:19914181

  12. Neural network based system for equipment surveillance

    Science.gov (United States)

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

    1998-04-28

    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  13. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...

  14. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    simulated process and compared. The closing chapter describes some practical experiments, where the different control concepts and training methods are tested on the same practical process operating in very noisy environments. All tests confirm that neural networks also have the potential to be trained......The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...

  15. Neural mechanisms of hypnosis and meditation.

    Science.gov (United States)

    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

  16. Resistance of subventricular neural stem cells to chronic hypoxemia despite structural disorganization of the germinal center and impairment of neuronal and oligodendrocyte survival

    Directory of Open Access Journals (Sweden)

    d’Anglemont de Tassigny X

    2015-06-01

    Full Text Available Xavier d'Anglemont de Tassigny,1,* M Salomé Sirerol-Piquer,2,3,* Ulises Gómez-Pinedo,4 Ricardo Pardal,1 Sonia Bonilla,1 Vivian Capilla-Gonzalez,2 Ivette López-López,1 Francisco Javier De la Torre-Laviana,1 José Manuel García-Verdugo,2,3 José López-Barneo1,3 1Medical Physiology and Biophysics Department, Institute of Biomedicine of Seville (IBiS, Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain; 2Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, Valencia, Spain; 3Network Center of Biomedical Research on Neurodegenerative Diseases (CIBERNED, Spain; 4Laboratory of Regenerative Medicine, San Carlos Institute of Health Investigation, Madrid, Spain *These authors contributed equally to this work Abstract: Chronic hypoxemia, as evidenced in de-acclimatized high-altitude residents or in patients with chronic obstructive respiratory disorders, is a common medical condition that can produce serious neurological alterations. However, the pathogenesis of this phenomenon is unknown. We have found that adult rodents exposed for several days/weeks to hypoxia, with an arterial oxygen tension similar to that of chronically hypoxemic patients, manifest a partially irreversible structural disarrangement of the subventricular neurogenic niche (subventricular zone characterized by displacement of neurons and myelinated axons, flattening of the ependymal cell layer, and thinning of capillary walls. Despite these abnormalities, the number of neuronal and oligodendrocyte progenitors, neuroblasts, and neurosphere-forming cells as well as the proliferative activity in subventricular zone was unchanged. These results suggest that neural stem cells and their undifferentiated progeny are resistant to hypoxia. However, in vivo and in vitro experiments indicate that severe chronic hypoxia decreases the survival of newly generated neurons and oligodendrocytes, with damage of myelin sheaths. These

  17. Quantitative characterization of new supramolecular synthons involving fluorine atoms in the crystal structures of di- and tetrafluorinated benzamides.

    Science.gov (United States)

    Mondal, Pradip Kumar; Yadav, Hare Ram; Choudhury, Angshuman Roy; Chopra, Deepak

    2017-10-01

    Strong hydrogen bonds play a significant role in crystal packing. In particular, the involvement of interactions involving fluorine in controlling the crystal packing requires appropriate attention, especially in the presence of other strong hydrogen bonds. In the present study, a detailed quantitative assessment has been performed of the nature, energetics and topological properties derived from the electron density in model compounds based on fluorinated benzamides (a total of 46 fluorine-substituted benzamides containing multiple fluorine atoms) in the solid state. The primary motivation in the design of such molecules is to enhance the acidity of the interacting H atoms in the presence of an increasing number of F atoms on the molecular scaffold, resulting in increased propensity towards the formation of intermolecular interactions involving organic fluorine. This exercise has resulted in the identification of new and frequently occurring supramolecular synthons involving F atoms in the packing of molecules in the solid state. The energetics associated with short and directional intermolecular Csp 2 -H...F-Csp 2 interactions with significantly high electrostatic contributions is noteworthy, and the topological analysis reveals the bonding character of these ubiquitous interactions in crystal packing in addition to the presence of Csp 2 -F...F-Csp 2 contacts.

  18. Xtal-xplore-R: a graphical tool for exploring the residual function involved in crystal structure determination.

    Science.gov (United States)

    Simons, Jan Marten; Roth, Georg

    2015-08-01

    This work presents Xtal-xplore-R, a tool dedicated to the visualization of two-dimensional cuts through the multidimensional crystallographic residual function. It imports arbitrary crystal structures, generates artificial diffraction data, and calculates and investigates the residual function in parameter space. The program serves two major purposes. Firstly, it is part of a more general project dealing with structure determination via global optimization techniques. In this context, the tool is being used to systematically analyse characteristic universal features of the target function (residual function) which can be used to develop appropriate problem-specific heuristic optimization algorithms. Secondly, Xtal-xplore-R is intended as a didactic tool to visualize how changes in atom parameters affect the residual function and can be used to demonstrate manual structure optimization for simple crystal structures.

  19. Assessing genetic structure with multiple classes of molecular markers: a case study involving the introduced fire ant Solenopsis invicta

    OpenAIRE

    Ross, K. G.; Shoemaker, D. D.; Krieger, M. J.; DeHeer, C. J.; Keller, L.

    1999-01-01

    We used 30 genetic markers of 6 different classes to describe hierarchical genetic structure in introduced populations of the fire ant Solenopsis invicta. These included four classes of presumably neutral nuclear loci (allozymes, codominant random amplified polymorphic DNAs (RAPDs), microsatellites, and dominant RAPDs), a class comprising two linked protein-coding nuclear loci under selection, and a marker of the mitochondrial DNA (mtDNA). Patterns of structure revealed by F statistics and ex...

  20. Neural correlates of maintaining one's political beliefs in the face of counterevidence.

    Science.gov (United States)

    Kaplan, Jonas T; Gimbel, Sarah I; Harris, Sam

    2016-12-23

    People often discount evidence that contradicts their firmly held beliefs. However, little is known about the neural mechanisms that govern this behavior. We used neuroimaging to investigate the neural systems involved in maintaining belief in the face of counterevidence, presenting 40 liberals with arguments that contradicted their strongly held political and non-political views. Challenges to political beliefs produced increased activity in the default mode network-a set of interconnected structures associated with self-representation and disengagement from the external world. Trials with greater belief resistance showed increased response in the dorsomedial prefrontal cortex and decreased activity in the orbitofrontal cortex. We also found that participants who changed their minds more showed less BOLD signal in the insula and the amygdala when evaluating counterevidence. These results highlight the role of emotion in belief-change resistance and offer insight into the neural systems involved in belief maintenance, motivated reasoning, and related phenomena.

  1. Functional and Structural Characterization of a Receptor-Like Kinase Involved in Germination and Cell Expansion in Arabidopsis

    Directory of Open Access Journals (Sweden)

    Zhen Wu

    2017-11-01

    Full Text Available Leucine-rich repeat receptor-like kinases (LRR-RLKs are widespread in different plant species and play important roles in growth and development. Germination inhibition is vital for the completion of seed maturation and cell expansion is a fundamental cellular process driving plant growth. Here, we report genetic and structural characterizations of a functionally uncharacterized LRR-RLK, named GRACE (Germination Repression and Cell Expansion receptor-like kinase. Overexpression of GRACE in Arabidopsis exhibited delayed germination, enlarged cotyledons, rosette leaves and stubbier petioles. Conversely, these phenotypes were reversed in the T-DNA insertion knock-down mutant grace-1 plants. A crystal structure of the extracellular domain of GRACE (GRACE-LRR determined at the resolution of 3.0 Å revealed that GRACE-LRR assumed a right-handed super-helical structure with an island domain (ID. Structural comparison showed that structure of the ID in GRACE-LRR is strikingly different from those observed in other LRR-RLKs. This structural observation implies that GRACE might perceive a new ligand for signaling. Collectively, our data support roles of GRACE in repressing seed germination and promoting cell expansion of Arabidopsis, presumably by perception of unknown ligand(s.

  2. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  3. Au@SiO2 core-shell structure involved with methotrexate: Fabrication, biodegradation process and bioassay explore.

    Science.gov (United States)

    Huo, Xiaolei; Dai, Chaofan; Tian, Deying; Li, Shuping; Li, Xiaodong

    2015-12-30

    A new strategy is proposed to synthesize a kind of Au@SiO2 core-shell structure with methotrexate (MTX) loaded within it. Firstly, MTX molecules are attracted to the surface and vicinity of Au nanoparticles (NPs). Then the enriched MTX molecules on the surface of Au NPs have a good chance to be wrapped into the core-shell structure when SiO2 is uniformly deposited on the Au core. Secondly, the effect of Au amount and MTX content on the drug-loading capacity is emphatically studied and the result shows that core-shell structure plays a vital role in drug loading. In addition, the biodegradation process is also examined in phosphate buffer solution (PBS) at 37°C. The results show that the biodegradation of Au-MTX@SiO2 core-shell structure can be divided into two stages: the release of drug together with the fragmentation of core-shell structure and the subsequent dissolution of SiO2 layers. Lastly, in vitro bioassay tests give the evidence that obvious tumor inhibition can be achieved in presence of Au-MTX@SiO2 NPs even at low concentration and the efficacy can be greatly enhanced by the photothermal therapy on Au cores. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Psychophysical and neural correlates of noised-induced tinnitus in animals: Intra- and inter-auditory and non-auditory brain structure studies.

    Science.gov (United States)

    Zhang, Jinsheng; Luo, Hao; Pace, Edward; Li, Liang; Liu, Bin

    2016-04-01

    Tinnitus, a ringing in the ear or head without an external sound source, is a prevalent health problem. It is often associated with a number of limbic-associated disorders such as anxiety, sleep disturbance, and emotional distress. Thus, to investigate tinnitus, it is important to consider both auditory and non-auditory brain structures. This paper summarizes the psychophysical, immunocytochemical and electrophysiological evidence found in rats or hamsters with behavioral evidence of tinnitus. Behaviorally, we tested for tinnitus using a conditioned suppression/avoidance paradigm, gap detection acoustic reflex behavioral paradigm, and our newly developed conditioned licking suppression paradigm. Our new tinnitus behavioral paradigm requires relatively short baseline training, examines frequency specification of tinnitus perception, and achieves sensitive tinnitus testing at an individual level. To test for tinnitus-related anxiety and cognitive impairment, we used the elevated plus maze and Morris water maze. Our results showed that not all animals with tinnitus demonstrate anxiety and cognitive impairment. Immunocytochemically, we found that animals with tinnitus manifested increased Fos-like immunoreactivity (FLI) in both auditory and non-auditory structures. The manner in which FLI appeared suggests that lower brainstem structures may be involved in acute tinnitus whereas the midbrain and cortex are involved in more chronic tinnitus. Meanwhile, animals with tinnitus also manifested increased FLI in non-auditory brain structures that are involved in autonomic reactions, stress, arousal and attention. Electrophysiologically, we found that rats with tinnitus developed increased spontaneous firing in the auditory cortex (AC) and amygdala (AMG), as well as intra- and inter-AC and AMG neurosynchrony, which demonstrate that tinnitus may be actively produced and maintained by the interactions between the AC and AMG. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. In vitro verification of a 3-D regenerative neural interface design: examination of neurite growth and electrical properties within a bifurcating microchannel structure

    NARCIS (Netherlands)

    Wieringa, P.A.; Wiertz, Remy; de Weerd, Eddy L; Rutten, Wim

    2010-01-01

    Toward the development of neuroprosthesis, we propose a 3-D regenerative neural interface design for connecting with the peripheral nervous system. This approach relies on bifurcating microstructures to achieve defasciculated ingrowth patterns and, consequently, high selectivity. In vitro studies

  6. Structural biology of disease-associated repetitive DNA sequences and protein-DNA complexes involved in DNA damage and repair

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, G.; Santhana Mariappan, S.V.; Chen, X.; Catasti, P.; Silks, L.A. III; Moyzis, R.K.; Bradbury, E.M.; Garcia, A.E.

    1997-07-01

    This project is aimed at formulating the sequence-structure-function correlations of various microsatellites in the human (and other eukaryotic) genomes. Here the authors have been able to develop and apply structure biology tools to understand the following: the molecular mechanism of length polymorphism microsatellites; the molecular mechanism by which the microsatellites in the noncoding regions alter the regulation of the associated gene; and finally, the molecular mechanism by which the expansion of these microsatellites impairs gene expression and causes the disease. Their multidisciplinary structural biology approach is quantitative and can be applied to all coding and noncoding DNA sequences associated with any gene. Both NIH and DOE are interested in developing quantitative tools for understanding the function of various human genes for prevention against diseases caused by genetic and environmental effects.

  7. Experiencing Past and Future Personal Events: Functional Neuroimaging Evidence on the Neural Bases of Mental Time Travel

    Science.gov (United States)

    Botzung, Anne; Denkova, Ekaterina; Manning, Lilianne

    2008-01-01

    Functional MRI was used in healthy subjects to investigate the existence of common neural structures supporting re-experiencing the past and pre-experiencing the future. Past and future events evocation appears to involve highly similar patterns of brain activation including, in particular, the medial prefrontal cortex, posterior regions and the…

  8. The Structural Basis of Substrate Recognition in an exo-beta-d-Glucosaminidase Involved in Chitosan Hydrolysis

    Energy Technology Data Exchange (ETDEWEB)

    Lammerts van Bueren, A.; Ghinet, M; Gregg, K; Fleury, A; Brzezinski, R; Boraston, A

    2009-01-01

    Family 2 of the glycoside hydrolase classification is one of the largest families. Structurally characterized members of this family include enzymes with beta-galactosidase activity (Escherichia coli LacZ), beta-glucuronidase activity (Homo sapiens GusB), and beta-mannosidase activity (Bacteroides thetaiotaomicron BtMan2A). Here, we describe the structure of a family 2 glycoside hydrolase, CsxA, from Amycolatopsis orientalis that has exo-beta-D-glucosaminidase (exo-chitosanase) activity. Analysis of a product complex (1.85 A resolution) reveals a unique negatively charged pocket that specifically accommodates the nitrogen of nonreducing end glucosamine residues, allowing this enzyme to discriminate between glucose and glucosamine. This also provides structural evidence for the role of E541 as the catalytic nucleophile and D469 as the catalytic acid/base. The structures of an E541A mutant in complex with a natural beta-1,4-D-glucosamine tetrasaccharide substrate and both E541A and D469A mutants in complex with a pNP-beta-D-glucosaminide synthetic substrate provide insight into interactions in the +1 subsite of this enzyme. Overall, a comparison with the active sites of other GH2 enzymes highlights the unique architecture of the CsxA active site, which imparts specificity for its cationic substrate.

  9. The Structural Basis of Substrate Recognition in an exo-b-d-glucosaminidase Involved in Chitosan Hydrolysis

    Energy Technology Data Exchange (ETDEWEB)

    Van Bueren, A.; Ghinet, M; Gregg, K; Fleury, A; Brzezinski, R; Boraston, A

    2009-01-01

    Family 2 of the glycoside hydrolase classification is one of the largest families. Structurally characterized members of this family include enzymes with ?-galactosidase activity (Escherichia coli LacZ), ?-glucuronidase activity (Homo sapiens GusB), and ?-mannosidase activity (Bacteroides thetaiotaomicron BtMan2A). Here, we describe the structure of a family 2 glycoside hydrolase, CsxA, from Amycolatopsis orientalis that has exo-?-d-glucosaminidase (exo-chitosanase) activity. Analysis of a product complex (1.85 A resolution) reveals a unique negatively charged pocket that specifically accommodates the nitrogen of nonreducing end glucosamine residues, allowing this enzyme to discriminate between glucose and glucosamine. This also provides structural evidence for the role of E541 as the catalytic nucleophile and D469 as the catalytic acid/base. The structures of an E541A mutant in complex with a natural ?-1,4-d-glucosamine tetrasaccharide substrate and both E541A and D469A mutants in complex with a pNP-?-d-glucosaminide synthetic substrate provide insight into interactions in the + 1 subsite of this enzyme. Overall, a comparison with the active sites of other GH2 enzymes highlights the unique architecture of the CsxA active site, which imparts specificity for its cationic substrate.

  10. The composition of ectopic lymphoid structures suggests involvement of a local immune response in cardiac allograft vasculopathy

    NARCIS (Netherlands)

    Huibers, Manon M. H.; Gareau, Alison J.; Vink, Aryan; Kruit, Rianne; Feringa, Hannah; Beerthuijzen, Johanna M. T.; Siera-de Koning, Erica; Peeters, Ton; de Jonge, Nicolaas; de Weger, Roel A.; Lee, Timothy D. G.

    BACKGROUND: Cardiac allograft vasculopathy (CAV) is a multifactorial pathology limiting the survival of cardiac transplants. The etiology of CAV is unclear, but antibody-mediated and cellular-mediated responses have been implicated. We, and others, have observed ectopic lymphoid structures (ELS)

  11. Neural repair in the adult brain

    Science.gov (United States)

    Jessberger, Sebastian

    2016-01-01

    Acute or chronic injury to the adult brain often results in substantial loss of neural tissue and subsequent permanent functional impairment. Over the last two decades, a number of approaches have been developed to harness the regenerative potential of neural stem cells and the existing fate plasticity of neural cells in the nervous system to prevent tissue loss or to enhance structural and functional regeneration upon injury. Here, we review recent advances of stem cell-associated neural repair in the adult brain, discuss current challenges and limitations, and suggest potential directions to foster the translation of experimental stem cell therapies into the clinic. PMID:26918167

  12. Fuzzy neural networks: theory and applications

    Science.gov (United States)

    Gupta, Madan M.

    1994-10-01

    During recent years, significant advances have been made in two distinct technological areas: fuzzy logic and computational neural networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. It also provides a mathematical morphology to emulate certain perceptual and linguistic attributes associated with human cognition. On the other hand, the computational neural network paradigms have evolved in the process of understanding the incredible learning and adaptive features of neuronal mechanisms inherent in certain biological species. Computational neural networks replicate, on a small scale, some of the computational operations observed in biological learning and adaptation. The integration of these two fields, fuzzy logic and neural networks, have given birth to an emerging technological field -- fuzzy neural networks. Fuzzy neural networks, have the potential to capture the benefits of these two fascinating fields, fuzzy logic and neural networks, into a single framework. The intent of this tutorial paper is to describe the basic notions of biological and computational neuronal morphologies, and to describe the principles and architectures of fuzzy neural networks. Towards this goal, we develop a fuzzy neural architecture based upon the notion of T-norm and T-conorm connectives. An error-based learning scheme is described for this neural structure.

  13. Neural plasticity of development and learning.

    Science.gov (United States)

    Galván, Adriana

    2010-06-01

    Development and learning are powerful agents of change across the lifespan that induce robust structural and functional plasticity in neural systems. An unresolved question in developmental cognitive neuroscience is whether development and learning share the same neural mechanisms associated with experience-related neural plasticity. In this article, I outline the conceptual and practical challenges of this question, review insights gleaned from adult studies, and describe recent strides toward examining this topic across development using neuroimaging methods. I suggest that development and learning are not two completely separate constructs and instead, that they exist on a continuum. While progressive and regressive changes are central to both, the behavioral consequences associated with these changes are closely tied to the existing neural architecture of maturity of the system. Eventually, a deeper, more mechanistic understanding of neural plasticity will shed light on behavioral changes across development and, more broadly, about the underlying neural basis of cognition. (c) 2010 Wiley-Liss, Inc.

  14. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marrow stromal cells (MSCs). The effectiveness of these induced cells was evaluated by grafting them either into peripheral nerve injury, spinal cord injury, or Parkinson' s disease animal models. MSCs-derived Schwann cells supported axonal regeneration and re-constructed myelin to facilitate the functional recovery in peripheral and spinal cord injury. MSCs-derived dopaminergic neurons integrated into host striatum and contributed to behavioral repair. In this review, we introduce the differentiation potential of MSCs and finally discuss about their benefits and drawbacks of these induction systems for cell-based therapy in neuro-traumatic and neuro-degenerative diseases.

  15. Sequence and Structural Analysis of the Chitinase Insertion Domain Reveals Two Conserved Motifs Involved in Chitin-Binding

    Science.gov (United States)

    Li, Hai; Greene, Lesley H.

    2010-01-01

    Background Chitinases are prevalent in life and are found in species including archaea, bacteria, fungi, plants, and animals. They break down chitin, which is the second most abundant carbohydrate in nature after cellulose. Hence, they are important for maintaining a balance between carbon and nitrogen trapped as insoluble chitin in biomass. Chitinases are classified into two families, 18 and 19 glycoside hydrolases. In addition to a catalytic domain, which is a triosephosphate isomerase barrel, many family 18 chitinases contain another module, i.e., chitinase insertion domain. While numerous studies focus on the biological role of the catalytic domain in chitinase activity, the function of the chitinase insertion domain is not completely understood. Bioinformatics offers an important avenue in which to facilitate understanding the role of residues within the chitinase insertion domain in chitinase function. Results Twenty-seven chitinase insertion domain sequences, which include four experimentally determined structures and span five kingdoms, were aligned and analyzed using a modified sequence entropy parameter. Thirty-two positions with conserved residues were identified. The role of these conserved residues was explored by conducting a structural analysis of a number of holo-enzymes. Hydrogen bonding and van der Waals calculations revealed a distinct subset of four conserved residues constituting two sequence motifs that interact with oligosaccharides. The other conserved residues may be key to the structure, folding, and stability of this domain. Conclusions Sequence and structural studies of the chitinase insertion domains conducted within the framework of evolution identified four conserved residues which clearly interact with the substrates. Furthermore, evolutionary studies propose a link between the appearance of the chitinase insertion domain and the function of family 18 chitinases in the subfamily A. PMID:20084296

  16. Ferritin structure from Mycobacterium tuberculosis: comparative study with homologues identifies extended C-terminus involved in ferroxidase activity.

    Directory of Open Access Journals (Sweden)

    Garima Khare

    Full Text Available Ferritins are recognized as key players in the iron storage and detoxification processes. Iron acquisition in the case of pathogenic bacteria has long been established as an important virulence mechanism. Here, we report a 3.0 Å crystal structure of a ferritin, annotated as Bacterioferritin B (BfrB, from Mycobacterium tuberculosis (Mtb, the causative agent of tuberculosis that continues to be one of the world's deadliest diseases. Similar to the other members of ferritin family, the Mtb BfrB subunit exhibits the characteristic fold of a four-helical bundle that possesses the ferroxidase catalytic centre. We compare the structure of Mtb BfrB with representatives of the ferritin family belonging to the archaea, eubacteria and eukarya. Unlike most other ferritins, Mtb BfrB has an extended C-terminus. To dissect the role of this extended C-terminus, truncated Mtb BfrB was purified and biochemical studies implicate this region in ferroxidase activity and iron release in addition to providing stability to the protein. Functionally important regions in a protein of known 3D-structure can be determined by estimating the degree of conservation of the amino-acid sites with its close homologues. Based on the comparative studies, we identify the slowly evolving conserved sites as well as the rapidly evolving variable sites and analyze their role in relation to structure and function of Mtb BfrB. Further, electrostatic computations demonstrate that although the electrostatic environment of catalytic residues is preserved within the family, extensive variability is exhibited by residues defining the channels and pores, in all likelihood keeping up with the diverse functions executed by these ferritins in varied environments.

  17. Structural-dynamical investigation of the ZnuA histidine-rich loop: involvement in zinc management and transport.

    Science.gov (United States)

    Falconi, Mattia; Oteri, Francesco; Di Palma, Francesco; Pandey, Saurabh; Battistoni, Andrea; Desideri, Alessandro

    2011-02-01

    Comparative homology modelling techniques have been used to model the protein ZnuA from Salmonella enterica serovar Typhimurium using the 3D structure of the homologous protein from Escherichia coli. These two-domain proteins bind one Zn(2+) atom, with high affinity, in the inter-domain cleft and possess a histidine-rich loop in the N-terminal domain. Alternative structures of the ZnuA histidine-rich loop, never resolved by the X-ray diffraction method, have been modelled. A model of the apo form, one with the histidine-rich loop deleted and two alternative structures with a second zinc ion bound to the histidine-rich loop, have been generated. In all the modelled proteins, investigated through molecular dynamics simulation, the histidine-rich loop is highly mobile and its fluctuations are correlated to the ligand stability observed in the zinc sites. Based on the plasticity of the histidine-rich loop and its significant effects on protein mobility a possible role in the capture and/or transfer of the zinc ions has been suggested.

  18. Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology.

    Science.gov (United States)

    Schultz, Wolfram

    2004-04-01

    Neurons in a small number of brain structures detect rewards and reward-predicting stimuli and are active during the expectation of predictable food and liquid rewards. These neurons code the reward information according to basic terms of various behavioural theories that seek to explain reward-directed learning, approach behaviour and decision-making. The involved brain structures include groups of dopamine neurons, the striatum including the nucleus accumbens, the orbitofrontal cortex and the amygdala. The reward information is fed to brain structures involved in decision-making and organisation of behaviour, such as the dorsolateral prefrontal cortex and possibly the parietal cortex. The neural coding of basic reward terms derived from formal theories puts the neurophysiological investigation of reward mechanisms on firm conceptual grounds and provides neural correlates for the function of rewards in learning, approach behaviour and decision-making.

  19. Neural oscillations and information flow associated with synaptic plasticity.

    Science.gov (United States)

    Zhang, Tao

    2011-10-25

    As a rhythmic neural activity, neural oscillation exists all over the nervous system, in structures as diverse as the cerebral cortex, hippocampus, subcortical nuclei and sense organs. This review firstly presents some evidence that synchronous neural oscillations in theta and gamma bands reveal much about the origin and nature of cognitive processes such as learning and memory. And then it introduces the novel analyzing algorithms of neural oscillations, which is a directionality index of neural information flow (NIF) as a measure of synaptic plasticity. An example of application used such an analyzing algorithms of neural oscillations has been provided.

  20. Grey matter density changes of structures involved in Posttraumatic Stress Disorder (PTSD) after recovery following Eye Movement Desensitization and Reprocessing (EMDR) therapy.

    Science.gov (United States)

    Boukezzi, Sarah; El Khoury-Malhame, Myriam; Auzias, Guillaume; Reynaud, Emmanuelle; Rousseau, Pierre-François; Richard, Emmanuel; Zendjidjian, Xavier; Roques, Jacques; Castelli, Nathalie; Correard, Nadia; Guyon, Valérie; Gellato, Caroline; Samuelian, Jean-Claude; Cancel, Aida; Comte, Magali; Latinus, Marianne; Guedj, Eric; Khalfa, Stéphanie

    2017-08-30

    Recovery of stress-induced structural alterations in Posttraumatic Stress Disorder (PTSD) remains largely unexplored. This study aimed to determine whether symptoms improvement is associated with grey matter (GM) density changes of brain structures involved in PTSD. Two groups of PTSD patients were involved in this study. The first group was treated with Eye Movement Desensitization and Reprocessing (EMDR) therapy and recovered from their symptoms (recovery group) (n = 11); Patients were scanned prior to therapy (T1), one week (T2) and five months after the end of therapy (T3). The second group included patients which followed a supportive therapy and remained symptomatic (wait-list group) (n = 7). They were scanned at three time-steps mimicking the same inter-scan intervals. Voxel-based morphometry (VBM) was used to characterize GM density evolution. GM density values showed a significant group-by-time interaction effect between T1 and T3 in prefrontal cortex areas. These interaction effects were driven by a GM density increase in the recovery group with respect to the wait-list group. Symptoms removal goes hand-in-hand with GM density enhancement of structures involved in emotional regulation. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  1. The neural crest and neural crest cells: discovery and significance ...

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    such as sea urchins, flies, fish and humans. (ii) Embryos (and so larvae and adults) form by differentiation from these germ layers. (iii) Homologous structures in different animals arise from the same germ layers. The germ-layer theory exerted a profound influence on those claiming a neural crest — that is, an ectodermal.

  2. Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Ziaul Huque

    2007-08-31

    This is the final technical report for the project titled 'Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks'. The aim of the project was to develop an efficient chemistry model for combustion simulations. The reduced chemistry model was developed mathematically without the need of having extensive knowledge of the chemistry involved. To aid in the development of the model, Neural Networks (NN) was used via a new network topology known as Non-linear Principal Components Analysis (NPCA). A commonly used Multilayer Perceptron Neural Network (MLP-NN) was modified to implement NPCA-NN. The training rate of NPCA-NN was improved with the GEneralized Regression Neural Network (GRNN) based on kernel smoothing techniques. Kernel smoothing provides a simple way of finding structure in data set without the imposition of a parametric model. The trajectory data of the reaction mechanism was generated based on the optimization techniques of genetic algorithm (GA). The NPCA-NN algorithm was then used for the reduction of Dimethyl Ether (DME) mechanism. DME is a recently discovered fuel made from natural gas, (and other feedstock such as coal, biomass, and urban wastes) which can be used in compression ignition engines as a substitute for diesel. An in-house two-dimensional Computational Fluid Dynamics (CFD) code was developed based on Meshfree technique and time marching solution algorithm. The project also provided valuable research experience to two graduate students.

  3. Structures of trehalose synthase from Deinococcus radiodurans reveal that a closed conformation is involved in catalysis of the intramolecular isomerization.

    Science.gov (United States)

    Wang, Yung Lin; Chow, Sih Yao; Lin, Yi Ting; Hsieh, Yu Chiao; Lee, Guan Chiun; Liaw, Shwu Huey

    2014-12-01

    Trehalose synthase catalyzes the simple conversion of the inexpensive maltose into trehalose with a side reaction of hydrolysis. Here, the crystal structures of the wild type and the N253A mutant of Deinococcus radiodurans trehalose synthase (DrTS) in complex with the inhibitor Tris are reported. DrTS consists of a catalytic (β/α)8 barrel, subdomain B, a C-terminal β domain and two TS-unique subdomains (S7 and S8). The C-terminal domain and S8 contribute the majority of the dimeric interface. DrTS shares high structural homology with sucrose hydrolase, amylosucrase and sucrose isomerase in complex with sucrose, in particular a virtually identical active-site architecture and a similar substrate-induced rotation of subdomain B. The inhibitor Tris was bound and mimics a sugar at the -1 subsite. A maltose was modelled into the active site, and subsequent mutational analysis suggested that Tyr213, Glu320 and Glu324 are essential within the +1 subsite for the TS activity. In addition, the interaction networks between subdomains B and S7 seal the active-site entrance. Disruption of such networks through the replacement of Arg148 and Asn253 with alanine resulted in a decrease in isomerase activity by 8-9-fold and an increased hydrolase activity by 1.5-1.8-fold. The N253A structure showed a small pore created for water entry. Therefore, our DrTS-Tris may represent a substrate-induced closed conformation that will facilitate intramolecular isomerization and minimize disaccharide hydrolysis.

  4. Structural and dynamic characterization of a freestanding acyl carrier protein involved in the biosynthesis of cyclic lipopeptide antibiotics.

    Science.gov (United States)

    Paul, Subrata; Ishida, Hiroaki; Nguyen, Leonard T; Liu, Zhihong; Vogel, Hans J

    2017-05-01

    Friulimicin is a cyclic lipodecapeptide antibiotic that is produced by Actinoplanes friuliensis. Similar to the related lipopeptide drug daptomycin, the peptide skeleton of friulimicin is synthesized by a large multienzyme nonribosomal peptide synthetase (NRPS) system. The LipD protein plays a major role in the acylation reaction of friulimicin. The attachment of the fatty acid group promotes its antibiotic activity. Phylogenetic analysis reveals that LipD is most closely related to other freestanding acyl carrier proteins (ACPs), for which the genes are located near to NRPS gene clusters. Here, we report that the solution NMR structure of apo-LipD is very similar to other four-helix bundle forming ACPs from fatty acid synthase (FAS), polyketide synthase, and NRPS systems. By recording NMR dynamics data, we found that the backbone motions in holo-LipD are more restricted than in apo-LipD due to the attachment of phosphopantetheine moiety. This enhanced stability of holo-LipD was also observed in differential scanning calorimetry experiments. Furthermore, we demonstrate that, unlike several other ACPs, the folding of LipD does not depend on the presence of divalent cations, although the presence of Mg 2+ or Ca 2+ can increase the protein stability. We propose that small structural rearrangements in the tertiary structure of holo-LipD which lead to the enhanced stability are important for the cognate enzyme recognition for the acylation reaction. Our results also highlight the different surface charges of LipD and FAS-ACP from A. friuliensis that would allow the acyl-CoA ligase to interact preferentially with the LipD instead of binding to the FAS-ACP. © 2017 The Protein Society.

  5. Structural Analysis of Streptococcus pyogenes NADH Oxidase: Conformational Dynamics Involved in Formation of the C(4a)-Peroxyflavin Intermediate.

    Science.gov (United States)

    Wallen, Jamie R; Mallett, T Conn; Okuno, Takashi; Parsonage, Derek; Sakai, Hiroaki; Tsukihara, Tomitake; Claiborne, Al

    2015-11-17

    In probing the oxygen reactivity of an Enterococcus faecalis NADH oxidase (Nox; O2 → 2H2O) C42S mutant lacking the Cys42-sulfenic acid (Cys42-SOH) redox center, we provided direct evidence of a C(4a)-peroxyflavin intermediate in the oxidative half-reaction and also described a conformational or chemical change that is rate-limiting for full reoxidation of the homodimer. In this work, the Nox from Streptococcus pyogenes (SpyNox) has been expressed and crystallized, and the overoxidized wild-type [Cys44-SOH → Cys44-sulfinic acid (Cys44-SO2H)] and C44S mutant enzyme structures have been refined at 2.0 and 2.15 Å, respectively. We show that azide binds to the two-electron reduced wild-type (EH2) enzyme and to the mutant enzyme in solution, but with a significantly higher affinity for the mutant protein. The spectral course of the titration with the SpyNox EH2 form clearly indicates progressive displacement of the Cys44-S(-) → FAD charge-transfer interaction. An azide soak with C44S Nox crystals led to the structure of the complex, as refined at 2.10 Å. The active-site N3(-) ligand is proximal to the Ser44 and His11 side chains, and a significant shift in the Ser44 side chain also appears. This provides an attractive explanation for the azide-induced loss of charge-transfer absorbance seen with the wild-type EH2 form and also permits accommodation of a C(4a)-peroxyflavin structural model. The conformation of Ser44 and the associated helical element, and the resulting steric accommodation, appear to be linked to the conformational change described in the E. faecalis C42S Nox oxidative half-reaction.

  6. Enzymatic properties of a GH19 chitinase isolated from rice lacking a major loop structure involved in chitin binding.

    Science.gov (United States)

    Tanaka, Jun; Fukamizo, Tamo; Ohnuma, Takayuki

    2017-05-01

    The catalytic domains of family GH19 chitinases have been found to consist of a conserved, α-helical core-region and different numbers (1-6) of loop structures, located at both ends of the substrate-binding groove and which extend over the glycon- and aglycon-binding sites. We expressed, purified and enzymatically characterized a GH19 chitinase from rice, Oryza sativa L. cv. Nipponbare (OsChia2a), lacking a major loop structure (loop III) connected to the functionally important β-stranded region. The new enzyme thus contained the five remaining loop structures (loops I, II, IV, V and C-term). The OsChia2a recombinant protein catalyzed hydrolysis of chitin oligosaccharides, (GlcNAc)n (n = 3-6), with inversion of anomeric configuration, indicating that OsChia2a correctly folded without loop III. From thermal unfolding experiments and calorimetric titrations using the inactive OsChia2a mutant (OsChia2a-E68Q), in which the catalytic residue Glu68 was mutated to glutamine, we found that the binding affinities towards (GlcNAc)n (n = 2-6) were almost proportional to the degree of polymerization of (GlcNAc)n, but were much lower than those obtained for a moss GH19 chitinase having only loop III [Ohnuma T, Sørlie M, Fukuda T, Kawamoto N, Taira T, Fukamizo T. 2011. Chitin oligosaccharide binding to a family GH19 chitinase from the moss, Bryum coronatum. FEBS J. 278:3991-4001]. Nevertheless, OsChia2a exhibited significant antifungal activity. It appears that loop III connected to the β-stranded region is important for (GlcNAc)n binding, but is not essential for antifungal activity. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. Structural analysis of PseH, the Campylobacter jejuni N-acetyltransferase involved in bacterial O-linked glycosylation

    Energy Technology Data Exchange (ETDEWEB)

    Song, Wan Seok; Nam, Mi Sun; Namgung, Byeol [Department of Systems Immunology, College of Biomedical Science, Kangwon National University, Chuncheon 200-701 (Korea, Republic of); Yoon, Sung-il, E-mail: sungil@kangwon.ac.kr [Department of Systems Immunology, College of Biomedical Science, Kangwon National University, Chuncheon 200-701 (Korea, Republic of); Institute of Bioscience and Biotechnology, Kangwon National University, Chuncheon 200-701 (Korea, Republic of)

    2015-03-20

    Campylobacter jejuni is a bacterium that uses flagella for motility and causes worldwide acute gastroenteritis in humans. The C. jejuni N-acetyltransferase PseH (cjPseH) is responsible for the third step in flagellin O-linked glycosylation and plays a key role in flagellar formation and motility. cjPseH transfers an acetyl group from an acetyl donor, acetyl coenzyme A (AcCoA), to the amino group of UDP-4-amino-4,6-dideoxy-N-acetyl-β-L-altrosamine to produce UDP-2,4-diacetamido-2,4,6-trideoxy-β-L-altropyranose. To elucidate the catalytic mechanism of cjPseH, crystal structures of cjPseH alone and in complex with AcCoA were determined at 1.95 Å resolution. cjPseH folds into a single-domain structure of a central β-sheet decorated by four α-helices with two continuously connected grooves. A deep groove (groove-A) accommodates the AcCoA molecule. Interestingly, the acetyl end of AcCoA points toward an open space in a neighboring shallow groove (groove-S), which is occupied by extra electron density that potentially serves as a pseudosubstrate, suggesting that the groove-S may provide a substrate-binding site. Structure-based comparative analysis suggests that cjPseH utilizes a unique catalytic mechanism of acetylation that has not been observed in other glycosylation-associated acetyltransferases. Thus, our studies on cjPseH will provide valuable information for the design of new antibiotics to treat C. jejuni-induced gastroenteritis. - Highlights: • cjPseH adopts a single-domain structure of a central β-sheet decorated by α-helices. • cjPseH features two continuously connected grooves on the protein surface. • Acetyl coenzyme A (AcCoA) binds into a deep groove of cjPseH in an ‘L’ shape. • The acetyl end of AcCoA points to a wide groove, a potential substrate-binding site.

  8. Neural network topology design for nonlinear control

    Science.gov (United States)

    Haecker, Jens; Rudolph, Stephan

    2001-03-01

    Neural networks, especially in nonlinear system identification and control applications, are typically considered to be black-boxes which are difficult to analyze and understand mathematically. Due to this reason, an in- depth mathematical analysis offering insight into the different neural network transformation layers based on a theoretical transformation scheme is desired, but up to now neither available nor known. In previous works it has been shown how proven engineering methods such as dimensional analysis and the Laplace transform may be used to construct a neural controller topology for time-invariant systems. Using the knowledge of neural correspondences of these two classical methods, the internal nodes of the network could also be successfully interpreted after training. As further extension to these works, the paper describes the latest of a theoretical interpretation framework describing the neural network transformation sequences in nonlinear system identification and control. This can be achieved By incorporation of the method of exact input-output linearization in the above mentioned two transform sequences of dimensional analysis and the Laplace transformation. Based on these three theoretical considerations neural network topologies may be designed in special situations by pure translation in the sense of a structural compilation of the known classical solutions into their correspondent neural topology. Based on known exemplary results, the paper synthesizes the proposed approach into the visionary goals of a structural compiler for neural networks. This structural compiler for neural networks is intended to automatically convert classical control formulations into their equivalent neural network structure based on the principles of equivalence between formula and operator, and operator and structure which are discussed in detail in this work.

  9. Neural network optimization, components, and design selection

    Science.gov (United States)

    Weller, Scott W.

    1991-01-01

    Neural Networks are part of a revived technology which has received a lot of hype in recent years. As is apt to happen in any hyp