WorldWideScience

Sample records for neural structures involved

  1. Identification of neural structures involved in stuttering using vibrotactile feedback.

    Science.gov (United States)

    Cheadle, Oliver; Sorger, Clarissa; Howell, Peter

    Feedback delivered over auditory and vibratory afferent pathways has different effects on the fluency of people who stutter (PWS). These features were exploited to investigate the neural structures involved in stuttering. The speech signal vibrated locations on the body (vibrotactile feedback, VTF). Eleven PWS read passages under VTF and control (no-VTF) conditions. All combinations of vibration amplitude, synchronous or delayed VTF and vibrator position (hand, sternum or forehead) were presented. Control conditions were performed at the beginning, middle and end of test sessions. Stuttering rate, but not speaking rate, differed between the control and VTF conditions. Notably, speaking rate did not change between when VTF was delayed versus when it was synchronous in contrast with what happens with auditory feedback. This showed that cerebellar mechanisms, which are affected when auditory feedback is delayed, were not implicated in the fluency-enhancing effects of VTF, suggesting that there is a second fluency-enhancing mechanism. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Effects of Time-Compressed Speech Training on Multiple Functional and Structural Neural Mechanisms Involving the Left Superior Temporal Gyrus.

    Science.gov (United States)

    Maruyama, Tsukasa; Takeuchi, Hikaru; Taki, Yasuyuki; Motoki, Kosuke; Jeong, Hyeonjeong; Kotozaki, Yuka; Nakagawa, Seishu; Nouchi, Rui; Iizuka, Kunio; Yokoyama, Ryoichi; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Sakaki, Kohei; Sasaki, Yukako; Magistro, Daniele; Kawashima, Ryuta

    2018-01-01

    Time-compressed speech is an artificial form of rapidly presented speech. Training with time-compressed speech (TCSSL) in a second language leads to adaptation toward TCSSL. Here, we newly investigated the effects of 4 weeks of training with TCSSL on diverse cognitive functions and neural systems using the fractional amplitude of spontaneous low-frequency fluctuations (fALFF), resting-state functional connectivity (RSFC) with the left superior temporal gyrus (STG), fractional anisotropy (FA), and regional gray matter volume (rGMV) of young adults by magnetic resonance imaging. There were no significant differences in change of performance of measures of cognitive functions or second language skills after training with TCSSL compared with that of the active control group. However, compared with the active control group, training with TCSSL was associated with increased fALFF, RSFC, and FA and decreased rGMV involving areas in the left STG. These results lacked evidence of a far transfer effect of time-compressed speech training on a wide range of cognitive functions and second language skills in young adults. However, these results demonstrated effects of time-compressed speech training on gray and white matter structures as well as on resting-state intrinsic activity and connectivity involving the left STG, which plays a key role in listening comprehension.

  3. 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...

  4. New approach to ECG's features recognition involving neural network

    International Nuclear Information System (INIS)

    Babloyantz, A.; Ivanov, V.V.; Zrelov, P.V.

    2001-01-01

    A new approach for the detection of slight changes in the form of the ECG signal is proposed. It is based on the approximation of raw ECG data inside each RR-interval by the expansion in polynomials of special type and on the classification of samples represented by sets of expansion coefficients using a layered feed-forward neural network. The transformation applied provides significantly simpler data structure, stability to noise and to other accidental factors. A by-product of the method is the compression of ECG data with factor 5

  5. Polarized DIS Structure Functions from Neural Networks

    International Nuclear Information System (INIS)

    Del Debbio, L.; Guffanti, A.; Piccione, A.

    2007-01-01

    We present a parametrization of polarized Deep-Inelastic-Scattering (DIS) structure functions based on Neural Networks. The parametrization provides a bias-free determination of the probability measure in the space of structure functions, which retains information on experimental errors and correlations. As an example we discuss the application of this method to the study of the structure function g 1 p (x,Q 2 )

  6. 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....

  7. 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....

  8. 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.

  9. Psychedelics Promote Structural and Functional Neural Plasticity

    Directory of Open Access Journals (Sweden)

    Calvin Ly

    2018-06-01

    Full Text Available Summary: Atrophy of neurons in the prefrontal cortex (PFC plays a key role in the pathophysiology of depression and related disorders. The ability to promote both structural and functional plasticity in the PFC has been hypothesized to underlie the fast-acting antidepressant properties of the dissociative anesthetic ketamine. Here, we report that, like ketamine, serotonergic psychedelics are capable of robustly increasing neuritogenesis and/or spinogenesis both in vitro and in vivo. These changes in neuronal structure are accompanied by increased synapse number and function, as measured by fluorescence microscopy and electrophysiology. The structural changes induced by psychedelics appear to result from stimulation of the TrkB, mTOR, and 5-HT2A signaling pathways and could possibly explain the clinical effectiveness of these compounds. Our results underscore the therapeutic potential of psychedelics and, importantly, identify several lead scaffolds for medicinal chemistry efforts focused on developing plasticity-promoting compounds as safe, effective, and fast-acting treatments for depression and related disorders. : Ly et al. demonstrate that psychedelic compounds such as LSD, DMT, and DOI increase dendritic arbor complexity, promote dendritic spine growth, and stimulate synapse formation. These cellular effects are similar to those produced by the fast-acting antidepressant ketamine and highlight the potential of psychedelics for treating depression and related disorders. Keywords: neural plasticity, psychedelic, spinogenesis, synaptogenesis, depression, LSD, DMT, ketamine, noribogaine, MDMA

  10. 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.

  11. 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...

  12. Evaluation of the cranial base in amnion rupture sequence involving the anterior neural tube: implications regarding recurrence risk.

    Science.gov (United States)

    Jones, Kenneth Lyons; Robinson, Luther K; Benirschke, Kurt

    2006-09-01

    Amniotic bands can cause disruption of the cranial end of the developing fetus, leading in some cases to a neural tube closure defect. Although recurrence for unaffected parents of an affected child with a defect in which the neural tube closed normally but was subsequently disrupted by amniotic bands is negligible; for a primary defect in closure of the neural tube to which amnion has subsequently adhered, recurrence risk is 1.7%. In that primary defects of neural tube closure are characterized by typical abnormalities of the base of the skull, evaluation of the cranial base in such fetuses provides an approach for making a distinction between these 2 mechanisms. This distinction has implications regarding recurrence risk. The skull base of 2 fetuses with amnion rupture sequence involving the cranial end of the neural tube were compared to that of 1 fetus with anencephaly as well as that of a structurally normal fetus. The skulls were cleaned, fixed in 10% formalin, recleaned, and then exposed to 10% KOH solution. After washing and recleaning, the skulls were exposed to hydrogen peroxide for bleaching and photography. Despite involvement of the anterior neural tube in both fetuses with amnion rupture sequence, in Case 3 the cranial base was normal while in Case 4 the cranial base was similar to that seen in anencephaly. This technique provides a method for determining the developmental pathogenesis of anterior neural tube defects in cases of amnion rupture sequence. As such, it provides information that can be used to counsel parents of affected children with respect to recurrence risk.

  13. 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.

  14. 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.

  15. Early perception and structural identity: neural implementation

    Science.gov (United States)

    Ligomenides, Panos A.

    1992-03-01

    It is suggested that there exists a minimal set of rules for the perceptual composition of the unending variety of spatio-temporal patterns in our perceptual world. Driven by perceptual discernment of "sudden change" and "unexpectedness", these rules specify conditions (such as co-linearity and virtual continuation) for perceptual grouping and for recursive compositions of perceptual "modalities" and "signatures". Beginning with a smallset of primitive perceptual elements, selected contextually at some relevant level of abstraction, perceptual compositions can graduate to an unlimited variety of spatiotemporal signatures, scenes and activities. Local discernible elements, often perceptually ambiguous by themselves, may be integrated into spatiotemporal compositions, which generate unambiguous perceptual separations between "figure" and "ground". The definition of computational algorithms for the effective instantiation of the rules of perceptual grouping remains a principal problem. In this paper we present our approach for solving the problem of perceptual recognition within the confines of one-D variational profiles. More specifically, concerning "early" (pre-attentive) recognition, we define the "structural identity of a k-norm, k ∈ K,"--SkID--as a tool for discerning and locating the instantiation of spatiotemporal objects or events. The SkID profile also serves a s a reference coordinate framework for the "perceptual focusing of attention" and the eventual assessment of resemblance. Neural network implementations of pre-attentive and attentive recognition are also discussed briefly. Our principles are exemplified by application to one-D perceptual profiles, which allows simplicity of definitions and of the rules of perceptual composition.

  16. 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

  17. The neural crest, a multifaceted structure of the vertebrates.

    Science.gov (United States)

    Dupin, Elisabeth; Le Douarin, Nicole M

    2014-09-01

    In this review, several features of the cells originating from the lateral borders of the primitive neural anlagen, the neural crest (NC) are considered. Among them, their multipotentiality, which together with their migratory properties, leads them to colonize the developing body and to participate in the development of many tissues and organs. The in vitro analysis of the developmental capacities of single NC cells (NCC) showed that they present several analogies with the hematopoietic cells whose differentiation involves the activity of stem cells endowed with different arrays of developmental potentialities. The permanence of such NC stem cells in the adult organism raises the problem of their role at that stage of life. The NC has appeared during evolution in the vertebrate phylum and is absent in their Protocordates ancestors. The major role of the NCC in the development of the vertebrate head points to a critical role for this structure in the remarkable diversification and radiation of this group of animals. © 2014 Wiley Periodicals, Inc.

  18. 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.

  19. A Possible Neural Representation of Mathematical Group Structures.

    Science.gov (United States)

    Pomi, Andrés

    2016-09-01

    Every cognitive activity has a neural representation in the brain. When humans deal with abstract mathematical structures, for instance finite groups, certain patterns of activity are occurring in the brain that constitute their neural representation. A formal neurocognitive theory must account for all the activities developed by our brain and provide a possible neural representation for them. Associative memories are neural network models that have a good chance of achieving a universal representation of cognitive phenomena. In this work, we present a possible neural representation of mathematical group structures based on associative memory models that store finite groups through their Cayley graphs. A context-dependent associative memory stores the transitions between elements of the group when multiplied by each generator of a given presentation of the group. Under a convenient election of the vector basis mapping the elements of the group in the neural activity, the input of a vector corresponding to a generator of the group collapses the context-dependent rectangular matrix into a virtual square permutation matrix that is the matrix representation of the generator. This neural representation corresponds to the regular representation of the group, in which to each element is assigned a permutation matrix. This action of the generator on the memory matrix can also be seen as the dissection of the corresponding monochromatic subgraph of the Cayley graph of the group, and the adjacency matrix of this subgraph is the permutation matrix corresponding to the generator.

  20. Neural responses to ambiguity involve domain-general and domain-specific emotion processing systems.

    Science.gov (United States)

    Neta, Maital; Kelley, William M; Whalen, Paul J

    2013-04-01

    Extant research has examined the process of decision making under uncertainty, specifically in situations of ambiguity. However, much of this work has been conducted in the context of semantic and low-level visual processing. An open question is whether ambiguity in social signals (e.g., emotional facial expressions) is processed similarly or whether a unique set of processors come on-line to resolve ambiguity in a social context. Our work has examined ambiguity using surprised facial expressions, as they have predicted both positive and negative outcomes in the past. Specifically, whereas some people tended to interpret surprise as negatively valenced, others tended toward a more positive interpretation. Here, we examined neural responses to social ambiguity using faces (surprise) and nonface emotional scenes (International Affective Picture System). Moreover, we examined whether these effects are specific to ambiguity resolution (i.e., judgments about the ambiguity) or whether similar effects would be demonstrated for incidental judgments (e.g., nonvalence judgments about ambiguously valenced stimuli). We found that a distinct task control (i.e., cingulo-opercular) network was more active when resolving ambiguity. We also found that activity in the ventral amygdala was greater to faces and scenes that were rated explicitly along the dimension of valence, consistent with findings that the ventral amygdala tracks valence. Taken together, there is a complex neural architecture that supports decision making in the presence of ambiguity: (a) a core set of cortical structures engaged for explicit ambiguity processing across stimulus boundaries and (b) other dedicated circuits for biologically relevant learning situations involving faces.

  1. 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.

  2. 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.

  3. 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

  4. Structured Memory for Neural Turing Machines

    OpenAIRE

    Zhang, Wei; Yu, Yang; Zhou, Bowen

    2015-01-01

    Neural Turing Machines (NTM) contain memory component that simulates "working memory" in the brain to store and retrieve information to ease simple algorithms learning. So far, only linearly organized memory is proposed, and during experiments, we observed that the model does not always converge, and overfits easily when handling certain tasks. We think memory component is key to some faulty behaviors of NTM, and better organization of memory component could help fight those problems. In this...

  5. 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.

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

    NARCIS (Netherlands)

    van den Dries, Sjoerd; Wiering, Marco A.

    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

  7. 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.

  8. 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.

  9. The functional and structural neural basis of individual differences in loss aversion.

    Science.gov (United States)

    Canessa, Nicola; Crespi, Chiara; Motterlini, Matteo; Baud-Bovy, Gabriel; Chierchia, Gabriele; Pantaleo, Giuseppe; Tettamanti, Marco; Cappa, Stefano F

    2013-09-04

    Decision making under risk entails the anticipation of prospective outcomes, typically leading to the greater sensitivity to losses than gains known as loss aversion. Previous studies on the neural bases of choice-outcome anticipation and loss aversion provided inconsistent results, showing either bidirectional mesolimbic responses of activation for gains and deactivation for losses, or a specific amygdala involvement in processing losses. Here we focused on loss aversion with the aim to address interindividual differences in the neural bases of choice-outcome anticipation. Fifty-six healthy human participants accepted or rejected 104 mixed gambles offering equal (50%) chances of gaining or losing different amounts of money while their brain activity was measured with functional magnetic resonance imaging (fMRI). We report both bidirectional and gain/loss-specific responses while evaluating risky gambles, with amygdala and posterior insula specifically tracking the magnitude of potential losses. At the individual level, loss aversion was reflected both in limbic fMRI responses and in gray matter volume in a structural amygdala-thalamus-striatum network, in which the volume of the "output" centromedial amygdala nuclei mediating avoidance behavior was negatively correlated with monetary performance. We conclude that outcome anticipation and ensuing loss aversion involve multiple neural systems, showing functional and structural individual variability directly related to the actual financial outcomes of choices. By supporting the simultaneous involvement of both appetitive and aversive processing in economic decision making, these results contribute to the interpretation of existing inconsistencies on the neural bases of anticipating choice outcomes.

  10. 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...... we developed a discriminative training algorithm for SHC models, where each SHC model for a specific speech pattern is trained with utterances of the pattern to be recognized and with other utterances. The discriminative training of SHC neural models has been tested on the TIDIGITS database...

  11. The Involvement of Endogenous Neural Oscillations in the Processing of Rhythmic Input: More Than a Regular Repetition of Evoked Neural Responses

    Science.gov (United States)

    Zoefel, Benedikt; ten Oever, Sanne; Sack, Alexander T.

    2018-01-01

    It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature. PMID:29563860

  12. Psychedelics Promote Structural and Functional Neural Plasticity.

    Science.gov (United States)

    Ly, Calvin; Greb, Alexandra C; Cameron, Lindsay P; Wong, Jonathan M; Barragan, Eden V; Wilson, Paige C; Burbach, Kyle F; Soltanzadeh Zarandi, Sina; Sood, Alexander; Paddy, Michael R; Duim, Whitney C; Dennis, Megan Y; McAllister, A Kimberley; Ori-McKenney, Kassandra M; Gray, John A; Olson, David E

    2018-06-12

    Atrophy of neurons in the prefrontal cortex (PFC) plays a key role in the pathophysiology of depression and related disorders. The ability to promote both structural and functional plasticity in the PFC has been hypothesized to underlie the fast-acting antidepressant properties of the dissociative anesthetic ketamine. Here, we report that, like ketamine, serotonergic psychedelics are capable of robustly increasing neuritogenesis and/or spinogenesis both in vitro and in vivo. These changes in neuronal structure are accompanied by increased synapse number and function, as measured by fluorescence microscopy and electrophysiology. The structural changes induced by psychedelics appear to result from stimulation of the TrkB, mTOR, and 5-HT2A signaling pathways and could possibly explain the clinical effectiveness of these compounds. Our results underscore the therapeutic potential of psychedelics and, importantly, identify several lead scaffolds for medicinal chemistry efforts focused on developing plasticity-promoting compounds as safe, effective, and fast-acting treatments for depression and related disorders. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  13. Optimal neural networks for protein-structure prediction

    International Nuclear Information System (INIS)

    Head-Gordon, T.; Stillinger, F.H.

    1993-01-01

    The successful application of neural-network algorithms for prediction of protein structure is stymied by three problem areas: the sparsity of the database of known protein structures, poorly devised network architectures which make the input-output mapping opaque, and a global optimization problem in the multiple-minima space of the network variables. We present a simplified polypeptide model residing in two dimensions with only two amino-acid types, A and B, which allows the determination of the global energy structure for all possible sequences of pentamer, hexamer, and heptamer lengths. This model simplicity allows us to compile a complete structural database and to devise neural networks that reproduce the tertiary structure of all sequences with absolute accuracy and with the smallest number of network variables. These optimal networks reveal that the three problem areas are convoluted, but that thoughtful network designs can actually deconvolute these detrimental traits to provide network algorithms that genuinely impact on the ability of the network to generalize or learn the desired mappings. Furthermore, the two-dimensional polypeptide model shows sufficient chemical complexity so that transfer of neural-network technology to more realistic three-dimensional proteins is evident

  14. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

    Science.gov (United States)

    Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

    2016-01-11

    Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

  15. 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...

  16. Parallel protein secondary structure prediction based on neural networks.

    Science.gov (United States)

    Zhong, Wei; Altun, Gulsah; Tian, Xinmin; Harrison, Robert; Tai, Phang C; Pan, Yi

    2004-01-01

    Protein secondary structure prediction has a fundamental influence on today's bioinformatics research. In this work, binary and tertiary classifiers of protein secondary structure prediction are implemented on Denoeux belief neural network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 and PSSM (position specific scoring matrix) are experimented separately as the encoding schemes for DBNN. The experimental results contribute to the design of new encoding schemes. New binary classifier for Helix versus not Helix ( approximately H) for DBNN produces prediction accuracy of 87% when PSSM is used for the input profile. The performance of DBNN binary classifier is comparable to other best prediction methods. The good test results for binary classifiers open a new approach for protein structure prediction with neural networks. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the hyperthreading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that hyperthreading technology for Intel architecture is efficient for parallel biological algorithms.

  17. The relationship between structural and functional connectivity: graph theoretical analysis of an EEG neural mass model

    NARCIS (Netherlands)

    Ponten, S.C.; Daffertshofer, A.; Hillebrand, A.; Stam, C.J.

    2010-01-01

    We investigated the relationship between structural network properties and both synchronization strength and functional characteristics in a combined neural mass and graph theoretical model of the electroencephalogram (EEG). Thirty-two neural mass models (NMMs), each representing the lump activity

  18. 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

    2013-01-01

    Introduction 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). Methods 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. Results 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

  19. 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.

  20. 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.

  1. The Elementary Nature of Purposive Behavior: Evolving Minimal Neural Structures that Display Intrinsic Intentionality

    Directory of Open Access Journals (Sweden)

    John S. Watson

    2005-01-01

    Full Text Available A study of the evolution of agency in artificial life was designed to access the potential emergence of purposiveness and intentionality as these attributes of behavior have been defined in psychology and philosophy. The study involved Darwinian evolution of mobile neural nets (autonomous agents in terms of their adaptive weight patterning and structure (number of sensory, hidden, and memory units that controlled movement. An agent was embedded in a 10 × 10 toroidal matrix along with “containers” that held benefit or harm if entered. Sensory exposure to content of a container was only briefly available at a distance so that adaptive response to a nearby container required use of relevant memory. The best 20% of each generation of agents, based on net benefit consumed during limited lifetime, were selected to parent the following generation. Purposiveness emerged for all selected agents by 300 generations. By 4000 generations, 90% passed a test of purposive intentionality based on Piaget's criteria for Stage IV object permanence in human infants. An additional test of these agents confirmed that the behavior of 67% of them was consistent with the philosophical criterion of intention being “about” the container's contents. Given that the evolved neural structure of more than half of the successful agents had only 1 hidden and 1 memory node, it is argued that, contrary to common assumption, purposive and intentional aspects of adaptive behavior require an evolution of minimal complexity of supportive neural structure.

  2. 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.

  3. Radiant energy during infrared neural stimulation at the target structure

    Science.gov (United States)

    Richter, Claus-Peter; Rajguru, Suhrud; Stafford, Ryan; Stock, Stuart R.

    2013-03-01

    Infrared neural stimulation (INS) describes a method, by which an infrared laser is used to stimulate neurons. The major benefit of INS over stimulating neurons with electrical current is its spatial selectivity. To translate the technique into a clinical application it is important to know the energy required to stimulate the neural structure. With this study we provide measurements of the radiant exposure, at the target structure that is required to stimulate the auditory neurons. Flat polished fibers were inserted into scala tympani so that the spiral ganglion was in front of the optical fiber. Angle polished fibers were inserted along scala tympani, and rotating the beveled surface of the fiber allowed the radiation beam to be directed perpendicular to the spiral ganglion. The radiant exposure for stimulation at the modiolus for flat and angle polished fibers averaged 6.78+/-2.15 mJ/cm2. With the angle polished fibers, a 90º change in the orientation of the optical beam from an orientation that resulted in an INS-evoked maximum response, resulted in a 50% drop in the response amplitude. When the orientation of the beam was changed by 180º, such that it was directed opposite to the orientation with the maxima, minimum response amplitude was observed.

  4. Cascaded bidirectional recurrent neural networks for protein secondary structure prediction.

    Science.gov (United States)

    Chen, Jinmiao; Chaudhari, Narendra

    2007-01-01

    Protein secondary structure (PSS) prediction is an important topic in bioinformatics. Our study on a large set of non-homologous proteins shows that long-range interactions commonly exist and negatively affect PSS prediction. Besides, we also reveal strong correlations between secondary structure (SS) elements. In order to take into account the long-range interactions and SS-SS correlations, we propose a novel prediction system based on cascaded bidirectional recurrent neural network (BRNN). We compare the cascaded BRNN against another two BRNN architectures, namely the original BRNN architecture used for speech recognition as well as Pollastri's BRNN that was proposed for PSS prediction. Our cascaded BRNN achieves an overall three state accuracy Q3 of 74.38\\%, and reaches a high Segment OVerlap (SOV) of 66.0455. It outperforms the original BRNN and Pollastri's BRNN in both Q3 and SOV. Specifically, it improves the SOV score by 4-6%.

  5. 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.

  6. 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.

  7. A modular structure to accident identification using neural networks

    International Nuclear Information System (INIS)

    Duque Estrada, Cassius Rodrigo

    2005-01-01

    This work uses the accident identification method based on Artificial Neural Networks (ANN) as basic blocks of a modular structure, allowing the inclusion of new accidents to be identified without modifying the ANN already trained. This structure comprises several modules for accident identification and one module for analysis. Each identification module follows the structure of the basic block. The identification modules are responsible for the recognition of an accident belonging to the specific set of events for which it were trained. The analysis module processes the output from the identification module to determine the system response. In order to test this structure it was proposed a transient identification problem comprising fifty accidents distributed in five identification modules. The results have demonstrated that the accident identification method used as basic block of a modular structure allows the inclusion of new sets of accidents, or variations of a same accident, without modifying the ANN already trained. For this, it is enough to include into the system an specific module for this new set of accidents. (author)

  8. A feedback regulatory loop involving microRNA-9 and nuclear receptor TLX in neural stem cell fate determination.

    Science.gov (United States)

    Zhao, Chunnian; Sun, GuoQiang; Li, Shengxiu; Shi, Yanhong

    2009-04-01

    MicroRNAs have been implicated as having important roles in stem cell biology. MicroRNA-9 (miR-9) is expressed specifically in neurogenic areas of the brain and may be involved in neural stem cell self-renewal and differentiation. We showed previously that the nuclear receptor TLX is an essential regulator of neural stem cell self-renewal. Here we show that miR-9 suppresses TLX expression to negatively regulate neural stem cell proliferation and accelerate neural differentiation. Introducing a TLX expression vector that is not prone to miR-9 regulation rescued miR-9-induced proliferation deficiency and inhibited precocious differentiation. In utero electroporation of miR-9 in embryonic brains led to premature differentiation and outward migration of the transfected neural stem cells. Moreover, TLX represses expression of the miR-9 pri-miRNA. By forming a negative regulatory loop with TLX, miR-9 provides a model for controlling the balance between neural stem cell proliferation and differentiation.

  9. Neural networks involved in learning lexical-semantic and syntactic information in a second language.

    Science.gov (United States)

    Mueller, Jutta L; Rueschemeyer, Shirley-Ann; Ono, Kentaro; Sugiura, Motoaki; Sadato, Norihiro; Nakamura, Akinori

    2014-01-01

    The present study used functional magnetic resonance imaging (fMRI) to investigate the neural correlates of language acquisition in a realistic learning environment. Japanese native speakers were trained in a miniature version of German prior to fMRI scanning. During scanning they listened to (1) familiar sentences, (2) sentences including a novel sentence structure, and (3) sentences containing a novel word while visual context provided referential information. Learning-related decreases of brain activation over time were found in a mainly left-hemispheric network comprising classical frontal and temporal language areas as well as parietal and subcortical regions and were largely overlapping for novel words and the novel sentence structure in initial stages of learning. Differences occurred at later stages of learning during which content-specific activation patterns in prefrontal, parietal and temporal cortices emerged. The results are taken as evidence for a domain-general network supporting the initial stages of language learning which dynamically adapts as learners become proficient.

  10. 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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

  12. 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.

  13. Simple neural substrate predicts complex rhythmic structure in duetting birds

    Science.gov (United States)

    Amador, Ana; Trevisan, M. A.; Mindlin, G. B.

    2005-09-01

    Horneros (Furnarius Rufus) are South American birds well known for their oven-looking nests and their ability to sing in couples. Previous work has analyzed the rhythmic organization of the duets, unveiling a mathematical structure behind the songs. In this work we analyze in detail an extended database of duets. The rhythms of the songs are compatible with the dynamics presented by a wide class of dynamical systems: forced excitable systems. Compatible with this nonlinear rule, we build a biologically inspired model for how the neural and the anatomical elements may interact to produce the observed rhythmic patterns. This model allows us to synthesize songs presenting the acoustic and rhythmic features observed in real songs. We also make testable predictions in order to support our hypothesis.

  14. 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).

  15. Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

    Science.gov (United States)

    Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

    2018-05-01

    To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

  16. Effects of turbidity on the neural structures of two closely related ...

    African Journals Online (AJOL)

    The neural structures of the sister species Pseudobarbus afer and P. asper were compared. P. afer, a redfin minnow which inhabits clear, perennial mountain streams, was found to have larger neural structures related to vision than P. asper, which inhabits turbid, intermittent streams of the Gamtoos River system, ...

  17. Disentangling the neural mechanisms involved in Hinduism- and Buddhism-related meditations.

    Science.gov (United States)

    Tomasino, Barbara; Chiesa, Alberto; Fabbro, Franco

    2014-10-01

    The most diffuse forms of meditation derive from Hinduism and Buddhism spiritual traditions. Different cognitive processes are set in place to reach these meditation states. According to an historical-philological hypothesis (Wynne, 2009) the two forms of meditation could be disentangled. While mindfulness is the focus of Buddhist meditation reached by focusing sustained attention on the body, on breathing and on the content of the thoughts, reaching an ineffable state of nothigness accompanied by a loss of sense of self and duality (Samadhi) is the main focus of Hinduism-inspired meditation. It is possible that these different practices activate separate brain networks. We tested this hypothesis by conducting an activation likelihood estimation (ALE) meta-analysis of functional magnetic resonance imaging (fMRI) studies. The network related to Buddhism-inspired meditation (16 experiments, 263 subjects, and 96 activation foci) included activations in some frontal lobe structures associated with executive attention, possibly confirming the fundamental role of mindfulness shared by many Buddhist meditations. By contrast, the network related to Hinduism-inspired meditation (8 experiments, 54 activation foci and 66 subjects) triggered a left lateralized network of areas including the postcentral gyrus, the superior parietal lobe, the hippocampus and the right middle cingulate cortex. The dissociation between anterior and posterior networks support the notion that different meditation styles and traditions are characterized by different patterns of neural activation. Copyright © 2014. Published by Elsevier Inc.

  18. 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.

  19. Convolution neural-network-based detection of lung structures

    Science.gov (United States)

    Hasegawa, Akira; Lo, Shih-Chung B.; Freedman, Matthew T.; Mun, Seong K.

    1994-05-01

    Chest radiography is one of the most primary and widely used techniques in diagnostic imaging. Nowadays with the advent of digital radiology, the digital medical image processing techniques for digital chest radiographs have attracted considerable attention, and several studies on the computer-aided diagnosis (CADx) as well as on the conventional image processing techniques for chest radiographs have been reported. In the automatic diagnostic process for chest radiographs, it is important to outline the areas of the lungs, the heart, and the diaphragm. This is because the original chest radiograph is composed of important anatomic structures and, without knowing exact positions of the organs, the automatic diagnosis may result in unexpected detections. The automatic extraction of an anatomical structure from digital chest radiographs can be a useful tool for (1) the evaluation of heart size, (2) automatic detection of interstitial lung diseases, (3) automatic detection of lung nodules, and (4) data compression, etc. Based on the clearly defined boundaries of heart area, rib spaces, rib positions, and rib cage extracted, one should be able to use this information to facilitate the tasks of the CADx on chest radiographs. In this paper, we present an automatic scheme for the detection of lung field from chest radiographs by using a shift-invariant convolution neural network. A novel algorithm for smoothing boundaries of lungs is also presented.

  20. Protein 8-class secondary structure prediction using conditional neural fields.

    Science.gov (United States)

    Wang, Zhiyong; Zhao, Feng; Peng, Jian; Xu, Jinbo

    2011-10-01

    Compared with the protein 3-class secondary structure (SS) prediction, the 8-class prediction gains less attention and is also much more challenging, especially for proteins with few sequence homologs. This paper presents a new probabilistic method for 8-class SS prediction using conditional neural fields (CNFs), a recently invented probabilistic graphical model. This CNF method not only models the complex relationship between sequence features and SS, but also exploits the interdependency among SS types of adjacent residues. In addition to sequence profiles, our method also makes use of non-evolutionary information for SS prediction. Tested on the CB513 and RS126 data sets, our method achieves Q8 accuracy of 64.9 and 64.7%, respectively, which are much better than the SSpro8 web server (51.0 and 48.0%, respectively). Our method can also be used to predict other structure properties (e.g. solvent accessibility) of a protein or the SS of RNA. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

    Science.gov (United States)

    Zhu, Zhenyu; Wang, Rubin; Zhu, Fengyun

    2018-01-01

    Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

  2. 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.

  3. Overlap in the functional neural systems involved in semantic and episodic memory retrieval.

    Science.gov (United States)

    Rajah, M N; McIntosh, A R

    2005-03-01

    Neuroimaging and neuropsychological data suggest that episodic and semantic memory may be mediated by distinct neural systems. However, an alternative perspective is that episodic and semantic memory represent different modes of processing within a single declarative memory system. To examine whether the multiple or the unitary system view better represents the data we conducted a network analysis using multivariate partial least squares (PLS ) activation analysis followed by covariance structural equation modeling (SEM) of positron emission tomography data obtained while healthy adults performed episodic and semantic verbal retrieval tasks. It is argued that if performance of episodic and semantic retrieval tasks are mediated by different memory systems, then there should differences in both regional activations and interregional correlations related to each type of retrieval task, respectively. The PLS results identified brain regions that were differentially active during episodic retrieval versus semantic retrieval. Regions that showed maximal differences in regional activity between episodic retrieval tasks were used to construct separate functional models for episodic and semantic retrieval. Omnibus tests of these functional models failed to find a significant difference across tasks for both functional models. The pattern of path coefficients for the episodic retrieval model were not different across tasks, nor were the path coefficients for the semantic retrieval model. The SEM results suggest that the same memory network/system was engaged across tasks, given the similarities in path coefficients. Therefore, activation differences between episodic and semantic retrieval may ref lect variation along a continuum of processing during task performance within the context of a single memory system.

  4. Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

    NARCIS (Netherlands)

    Veldhoen, S.; Hupkes, D.; Zuidema, W.

    2016-01-01

    We investigate how neural networks can be used for hierarchical, compositional semantics. To this end, we define the simple but nontrivial artificial task of processing nested arithmetic expressions and study whether different types of neural networks can learn to add and subtract. We find that

  5. Readout from iconic memory and selective spatial attention involve similar neural processes.

    Science.gov (United States)

    Ruff, Christian C; Kristjánsson, Arni; Driver, Jon

    2007-10-01

    Iconic memory and spatial attention are often considered separately, but they may have functional similarities. Here we provide functional magnetic resonance imaging evidence for some common underlying neural effects. Subjects judged three visual stimuli in one hemifield of a bilateral array comprising six stimuli. The relevant hemifield for partial report was indicated by an auditory cue, administered either before the visual array (precue, spatial attention) or shortly after the array (postcue, iconic memory). Pre- and postcues led to similar activity modulations in lateral occipital cortex contralateral to the cued side. This finding indicates that readout from iconic memory can have some neural effects similar to those of spatial attention. We also found common bilateral activation of a fronto-parietal network for postcue and precue trials. These neuroimaging data suggest that some common neural mechanisms underlie selective spatial attention and readout from iconic memory. Some differences were also found; compared with precues, postcues led to higher activity in the right middle frontal gyrus.

  6. 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

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

    KAUST Repository

    Yong Wan,; Otsuna, H.; Chi-Bin Chien,; Hansen, C.

    2012-01-01

    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.

  8. 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.

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

    DEFF Research Database (Denmark)

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

    RNA serves a number of functions in the cell: mRNAs are the carriers of information between gene and protein, tRNAs and rRNAs are involved in the synthesis of proteins, whereas a number of additional RNA species are responsible for other functions in the cell. The quality of the different RNAs...... RNAs. We have solved the structures of two nucleases involved in 3'-5' degradation of RNA; the S. pombe Pop2p and the S. cerevisiae Rrp6p. Pop2p is part of the main cytoplasmatic deadenylation complex in yeast, which also contains the nuclease Ccr4p. Deadenylation, where the poly(A)-tail is removed...... specific transcripts. Here, we present the crystal structure of the S. pombe Pop2p protein to 1.4 Å resolution. The high resolution structure provides a clear picture of the active site architecture. Structural alignment of single nucleotides and poly(A)-oligonucleotides from earlier co-crystal structures...

  10. Concepts in context: Processing mental state concepts with internal or external focus involves different neural systems

    Science.gov (United States)

    Oosterwijk, Suzanne; Mackey, Scott; Wilson-Mendenhall, Christine; Winkielman, Piotr; Paulus, Martin P.

    2015-01-01

    According to embodied cognition theories concepts are contextually-situated and grounded in neural systems that produce experiential states. This view predicts that processing mental state concepts recruits neural regions associated with different aspects of experience depending on the context in which people understand a concept. This neuroimaging study tested this prediction using a set of sentences that described emotional (e.g., fear, joy) and non-emotional (e.g., thinking, hunger) mental states with internal focus (i.e. focusing on bodily sensations and introspection) or external focus (i.e. focusing on expression and action). Consistent with our predictions, data suggested that the inferior frontal gyrus, a region associated with action representation, was engaged more by external than internal sentences. By contrast, the ventromedial prefrontal cortex, a region associated with the generation of internal states, was engaged more by internal emotion sentences than external sentence categories. Similar patterns emerged when we examined the relationship between neural activity and independent ratings of sentence focus. Furthermore, ratings of emotion were associated with activation in the medial prefrontal cortex, whereas ratings of activity were associated with activation in the inferior frontal gyrus. These results suggest that mental state concepts are represented in a dynamic way, using context-relevant interoceptive and sensorimotor resources. PMID:25748274

  11. Structural reliability calculation method based on the dual neural network and direct integration method.

    Science.gov (United States)

    Li, Haibin; He, Yun; Nie, Xiaobo

    2018-01-01

    Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

  12. 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.

  13. 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.

  14. 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)

    1998-12-31

    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.

  15. An object recognition using structured light and neural networks

    International Nuclear Information System (INIS)

    Kim, Byeong Gab; Kim, Dong Gi; Kang, E Sok; Yoon, Ji Sup

    1997-01-01

    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

  16. 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.

  17. Involvement of extracellular factors in maintaining self-renewal of neural stem cell by nestin.

    Science.gov (United States)

    Di, Chun Guang; Xiang, Andy Peng; Jia, Lei; Liu, Jun Feng; Lahn, Bruce T; Ma, Bao Feng

    2014-07-09

    Nestin knockout leads to embryonic lethality and self-renewal deficiency in neural stem cells (NSCs). However, how nestin maintains self-renewal remains uncertain. Here, we used the dosage effect of nestin in heterozygous mice (Nes+/-) to study self-renewal of NSCs. With existing extracellular signaling in vivo or in vitro, nestin levels do not affect proliferation ability or apoptosis when compared between Nes+/- and Nes+/+ NSCs. However, self-renewal ability of Nes+/- NSCs is impaired when plated at a low cell density and completely lost at a clonal density. This deficiency in self-renewal at a clonal density is rescued using a medium conditioned by Nes+/+ NSCs. In addition, the Akt signaling pathway is altered at low density and reversed by conditioned medium. Our data show that secreted factors contribute toward maintaining self-renewal of NSCs by nestin, potentially through Akt signaling.

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

    Science.gov (United States)

    Younger, Jarred; Aron, Arthur; Parke, Sara; Chatterjee, Neil; Mackey, Sean

    2010-10-13

    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.

  19. The neural network involved in a bimanual tactile-tactile matching discrimination task: a functional imaging study at 3 T

    Energy Technology Data Exchange (ETDEWEB)

    Habas, Christophe; Cabanis, Emmanuel A. [UPMC Paris 6, Service de NeuroImagerie, Hopital des Quinze-Vingts, Paris (France)

    2007-08-15

    The cerebral and cerebellar network involved in a bimanual object recognition was studied in blood oxygenation dependent level functional magnetic resonance imaging (fMRI). Nine healthy right-handed volunteers were scanned (1) while performing bilateral finger movements (nondiscrimination motor task), and (2) while performing a bimanual tactile-tactile matching discrimination task using small chess pieces (tactile discrimination task). Extensive activations were specifically observed in the parietal (SII, superior lateral lobule), insular, prefrontal, cingulate and neocerebellar cortices (HVIII), with a left predominance in motor areas, during the tactile discrimination task in contrast to the findings during the nondiscrimination motor task. Bimanual tactile-tactile matching discrimination recruits multiple sensorimotor and associative cerebral and neocerebellar networks (including the cerebellar second homunculus, HVIII), comparable to the neural circuits involved in unimanual tactile object recognition. (orig.)

  20. High glucose alters the expression of genes involved in proliferation and cell-fate specification of embryonic neural stem cells.

    Science.gov (United States)

    Fu, J; Tay, S S W; Ling, E A; Dheen, S T

    2006-05-01

    Maternal diabetes induces neural tube defects during embryogenesis. Since the neural tube is derived from neural stem cells (NSCs), it is hypothesised that in diabetic pregnancy neural tube defects result from altered expression of developmental control genes, leading to abnormal proliferation and cell-fate choice of NSCs. Cell viability, proliferation index and apoptosis of NSCs and differentiated cells from mice exposed to physiological or high glucose concentration medium were examined by a tetrazolium salt assay, 5-bromo-2'-deoxyuridine incorporation, terminal deoxynucleotidyl transferase-mediated dUTP nick end labelling and immunocytochemistry. Expression of developmental genes, including sonic hedgehog (Shh), bone morphogenetic protein 4 (Bmp4), neurogenin 1/2 (Neurog1/2), achaete-scute complex-like 1 (Ascl1), oligodendrocyte transcription factor 1 (Olig1), oligodendrocyte lineage transcription factor 2 (Olig2), hairy and enhancer of split 1/5 (Hes1/5) and delta-like 1 (Dll1), was analysed by real-time RT-PCR. Proliferation index and neuronal specification in the forebrain of embryos at embryonic day 11.5 were examined histologically. High glucose decreased the proliferation of NSCs and differentiated cells. The incidence of apoptosis was increased in NSCs treated with high glucose, but not in the differentiated cells. High glucose also accelerated neuronal and glial differentiation from NSCs. The decreased proliferation index and early differentiation of neurons were evident in the telencephalon of embryos derived from diabetic mice. Exposure to high glucose altered the mRNA expression levels of Shh, Bmp4, Neurog1/2, Ascl1, Hes1, Dll1 and Olig1 in NSCs and Shh, Dll1, Neurog1/2 and Hes5 in differentiated cells. The changes in proliferation and differentiation of NSCs exposed to high glucose are associated with altered expression of genes that are involved in cell-cycle progression and cell-fate specification during neurulation. These changes may form the

  1. Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

    Science.gov (United States)

    Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

    2017-03-01

    Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

  2. Lunar Circular Structure Classification from Chang 'e 2 High Resolution Lunar Images with Convolutional Neural Network

    Science.gov (United States)

    Zeng, X. G.; Liu, J. J.; Zuo, W.; Chen, W. L.; Liu, Y. X.

    2018-04-01

    Circular structures are widely distributed around the lunar surface. The most typical of them could be lunar impact crater, lunar dome, et.al. In this approach, we are trying to use the Convolutional Neural Network to classify the lunar circular structures from the lunar images.

  3. 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…

  4. 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.

  5. Mapping and signaling of neural pathways involved in the regulation of hydromineral homeostasis

    Directory of Open Access Journals (Sweden)

    J. Antunes-Rodrigues

    2013-04-01

    Full Text Available Several forebrain and brainstem neurochemical circuitries interact with peripheral neural and humoral signals to collaboratively maintain both the volume and osmolality of extracellular fluids. Although much progress has been made over the past decades in the understanding of complex mechanisms underlying neuroendocrine control of hydromineral homeostasis, several issues still remain to be clarified. The use of techniques such as molecular biology, neuronal tracing, electrophysiology, immunohistochemistry, and microinfusions has significantly improved our ability to identify neuronal phenotypes and their signals, including those related to neuron-glia interactions. Accordingly, neurons have been shown to produce and release a large number of chemical mediators (neurotransmitters, neurohormones and neuromodulators into the interstitial space, which include not only classic neurotransmitters, such as acetylcholine, amines (noradrenaline, serotonin and amino acids (glutamate, GABA, but also gaseous (nitric oxide, carbon monoxide and hydrogen sulfide and lipid-derived (endocannabinoids mediators. This efferent response, initiated within the neuronal environment, recruits several peripheral effectors, such as hormones (glucocorticoids, angiotensin II, estrogen, which in turn modulate central nervous system responsiveness to systemic challenges. Therefore, in this review, we shall evaluate in an integrated manner the physiological control of body fluid homeostasis from the molecular aspects to the systemic and integrated responses.

  6. Neural Networks Involved in Adolescent Reward Processing: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies

    Science.gov (United States)

    Silverman, Merav H.; Jedd, Kelly; Luciana, Monica

    2015-01-01

    Behavioral responses to, and the neural processing of, rewards change dramatically during adolescence and may contribute to observed increases in risk-taking during this developmental period. Functional MRI (fMRI) studies suggest differences between adolescents and adults in neural activation during reward processing, but findings are contradictory, and effects have been found in non-predicted directions. The current study uses an activation likelihood estimation (ALE) approach for quantitative meta-analysis of functional neuroimaging studies to: 1) confirm the network of brain regions involved in adolescents’ reward processing, 2) identify regions involved in specific stages (anticipation, outcome) and valence (positive, negative) of reward processing, and 3) identify differences in activation likelihood between adolescent and adult reward-related brain activation. Results reveal a subcortical network of brain regions involved in adolescent reward processing similar to that found in adults with major hubs including the ventral and dorsal striatum, insula, and posterior cingulate cortex (PCC). Contrast analyses find that adolescents exhibit greater likelihood of activation in the insula while processing anticipation relative to outcome and greater likelihood of activation in the putamen and amygdala during outcome relative to anticipation. While processing positive compared to negative valence, adolescents show increased likelihood for activation in the posterior cingulate cortex (PCC) and ventral striatum. Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults. Unlike adolescents, adults also activate executive control regions of the frontal and parietal lobes. These findings support hypothesized elevations in motivated activity during adolescence. PMID:26254587

  7. A loop-based neural architecture for structured behavior encoding and decoding.

    Science.gov (United States)

    Gisiger, Thomas; Boukadoum, Mounir

    2018-02-01

    We present a new type of artificial neural network that generalizes on anatomical and dynamical aspects of the mammal brain. Its main novelty lies in its topological structure which is built as an array of interacting elementary motifs shaped like loops. These loops come in various types and can implement functions such as gating, inhibitory or executive control, or encoding of task elements to name a few. Each loop features two sets of neurons and a control region, linked together by non-recurrent projections. The two neural sets do the bulk of the loop's computations while the control unit specifies the timing and the conditions under which the computations implemented by the loop are to be performed. By functionally linking many such loops together, a neural network is obtained that may perform complex cognitive computations. To demonstrate the potential offered by such a system, we present two neural network simulations. The first illustrates the structure and dynamics of a single loop implementing a simple gating mechanism. The second simulation shows how connecting four loops in series can produce neural activity patterns that are sufficient to pass a simplified delayed-response task. We also show that this network reproduces electrophysiological measurements gathered in various regions of the brain of monkeys performing similar tasks. We also demonstrate connections between this type of neural network and recurrent or long short-term memory network models, and suggest ways to generalize them for future artificial intelligence research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Shared memories reveal shared structure in neural activity across individuals

    Science.gov (United States)

    Chen, J.; Leong, Y.C.; Honey, C.J.; Yong, C.H.; Norman, K.A.; Hasson, U.

    2016-01-01

    Our lives revolve around sharing experiences and memories with others. When different people recount the same events, how similar are their underlying neural representations? Participants viewed a fifty-minute movie, then verbally described the events during functional MRI, producing unguided detailed descriptions lasting up to forty minutes. As each person spoke, event-specific spatial patterns were reinstated in default-network, medial-temporal, and high-level visual areas. Individual event patterns were both highly discriminable from one another and similar between people, suggesting consistent spatial organization. In many high-order areas, patterns were more similar between people recalling the same event than between recall and perception, indicating systematic reshaping of percept into memory. These results reveal the existence of a common spatial organization for memories in high-level cortical areas, where encoded information is largely abstracted beyond sensory constraints; and that neural patterns during perception are altered systematically across people into shared memory representations for real-life events. PMID:27918531

  9. Neural circuits containing olfactory neurons are involved in prepulse inhibition of the startle reflex in rats

    Directory of Open Access Journals (Sweden)

    Haichen eNiu

    2015-03-01

    Full Text Available Many neuropsychiatric disorders, such as schizophrenia, have been associated with abnormalities in the function of the olfactory system and prepulse inhibition (PPI of the startle reflex. However, whether these two abnormalities are related is unclear. The present study was designed to determine whether inhibiting olfactory sensory input via the infusion of zinc sulfate (ZnE, 0.17 M, 0.5 ml into the olfactory naris disrupts PPI. Furthermore, lidocaine/MK801 was bilaterally microinjected into the olfactory bulb (OB to examine whether the blockade of olfactory sensory input impairs PPI. To identify the neural projections that connect the olfaction- and PPI-related areas of the CNS, trans-synaptic retrograde tracing using a recombinant pseudorabies virus (PRV was performed. Our results demonstrated that blocking olfactory sensory input altered olfaction-related behavior. At the functional level, we demonstrated that the inhibition of olfactory sensory input impaired PPI of the startle response subsequent to a decrease in c-fos expression in relevant brain regions. Furthermore, the results of a similar and more robust experiment indicated that blocking olfactory sensory input via the microinjection of lidocaine/MK801 into the OB impaired PPI. At the circuit level, based on trans-synaptic retrograde tracing using PRV, we demonstrated that a large portion of the labeled neurons in several regions of the olfactory cortices connected to the pedunculopontine tegmental nucleus (PPTg. Thus, these data suggest that the olfactory system participates in the regulation of PPI and plays a role in the effect of PPI on the startle response in rats.

  10. Mapping the neural substrates involved in maternal responsiveness and lamb olfactory memory in parturient ewes using Fos imaging.

    Science.gov (United States)

    Keller, Matthieu; Meurisse, Maryse; Lévy, Frédéric

    2004-12-01

    In sheep, recognition of the familiar lamb by the mother depends on the learning of its olfactory signature after parturition. The authors quantified Fos changes in order to identify brain regions activated during lamb odor memory formation. Brain activation was compared with those measured in anosmic ewes displaying maternal behavior but not individual lamb recognition. In intact ewes, parturition induced significant increase in Fos expression in olfactory cortical regions and in cortical amygdala, whereas in anosmic mothers, Fos expression was very low. In contrast, no difference was observed between intact and anosmic ewes in hypothalamic areas and medial amygdala, suggesting a differentiation between the neural network controlling maternal responsiveness and that involved in olfactory lamb memory.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Two Scales, Hybrid Model for Soils, Involving Artificial Neural Network and Finite Element Procedure

    Directory of Open Access Journals (Sweden)

    Krasiński Marcin

    2015-02-01

    Full Text Available A hybrid ANN-FE solution is presented as a result of two level analysis of soils: a level of a laboratory sample and a level of engineering geotechnical problem. Engineering properties of soils (sands are represented directly in the form of ANN (this is in contrast with our former paper where ANN approximated constitutive relationships. Initially the ANN is trained with Duncan formula (Duncan and Chang [2], then it is re-trained (calibrated with some available experimental data, specific for the soil considered. The obtained approximation of the constitutive parameters is used directly in finite element method at the level of a single element at the scale of the laboratory sample to check the correct representation of the laboratory test. Then, the finite element that was successfully tested at the level of laboratory sample is used at the macro level to solve engineering problems involving the soil for which it was calibrated.

  16. Adaptive neural network/expert system that learns fault diagnosis for different structures

    Science.gov (United States)

    Simon, Solomon H.

    1992-08-01

    Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

  17. Hierarchical modular structure enhances the robustness of self-organized criticality in neural networks

    International Nuclear Information System (INIS)

    Wang Shengjun; Zhou Changsong

    2012-01-01

    One of the most prominent architecture properties of neural networks in the brain is the hierarchical modular structure. How does the structure property constrain or improve brain function? It is thought that operating near criticality can be beneficial for brain function. Here, we find that networks with modular structure can extend the parameter region of coupling strength over which critical states are reached compared to non-modular networks. Moreover, we find that one aspect of network function—dynamical range—is highest for the same parameter region. Thus, hierarchical modularity enhances robustness of criticality as well as function. However, too much modularity constrains function by preventing the neural networks from reaching critical states, because the modular structure limits the spreading of avalanches. Our results suggest that the brain may take advantage of the hierarchical modular structure to attain criticality and enhanced function. (paper)

  18. Chronic stress disrupts neural coherence between cortico-limbic structures

    Directory of Open Access Journals (Sweden)

    João Filipe Oliveira

    2013-02-01

    Full Text Available Chronic stress impairs cognitive function, namely on tasks that rely on the integrity of cortico-limbic networks. To unravel the functional impact of progressive stress in cortico-limbic networks we measured neural activity and spectral coherences between the ventral hippocampus (vHIP and the medial prefrontal cortex (mPFC in rats subjected to short term (STS and chronic unpredictable stress (CUS. CUS exposure consistently disrupted the spectral coherence between both areas for a wide range of frequencies, whereas STS exposure failed to trigger such effect. The chronic stress-induced coherence decrease correlated inversely with the vHIP power spectrum, but not with the mPFC power spectrum, which supports the view that hippocampal dysfunction is the primary event after stress exposure. Importantly, we additionally show that the variations in vHIP-to-mPFC coherence and power spectrum in the vHIP correlated with stress-induced behavioral deficits in a spatial reference memory task. Altogether, these findings result in an innovative readout to measure, and follow, the functional events that underlie the stress-induced reference memory impairments.

  19. Invariant 2D object recognition using the wavelet transform and structured neural networks

    Science.gov (United States)

    Khalil, Mahmoud I.; Bayoumi, Mohamed M.

    1999-03-01

    This paper applies the dyadic wavelet transform and the structured neural networks approach to recognize 2D objects under translation, rotation, and scale transformation. Experimental results are presented and compared with traditional methods. The experimental results showed that this refined technique successfully classified the objects and outperformed some traditional methods especially in the presence of noise.

  20. 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...

  1. Emotional face processing and flat affect in schizophrenia: functional and structural neural correlates.

    Science.gov (United States)

    Lepage, M; Sergerie, K; Benoit, A; Czechowska, Y; Dickie, E; Armony, J L

    2011-09-01

    There is a general consensus in the literature that schizophrenia causes difficulties with facial emotion perception and discrimination. Functional brain imaging studies have observed reduced limbic activity during facial emotion perception but few studies have examined the relation to flat affect severity. A total of 26 people with schizophrenia and 26 healthy controls took part in this event-related functional magnetic resonance imaging study. Sad, happy and neutral faces were presented in a pseudo-random order and participants indicated the gender of the face presented. Manual segmentation of the amygdala was performed on a structural T1 image. Both the schizophrenia group and the healthy control group rated the emotional valence of facial expressions similarly. Both groups exhibited increased brain activity during the perception of emotional faces relative to neutral ones in multiple brain regions, including multiple prefrontal regions bilaterally, the right amygdala, right cingulate cortex and cuneus. Group comparisons, however, revealed increased activity in the healthy group in the anterior cingulate, right parahippocampal gyrus and multiple visual areas. In schizophrenia, the severity of flat affect correlated significantly with neural activity in several brain areas including the amygdala and parahippocampal region bilaterally. These results suggest that many of the brain regions involved in emotional face perception, including the amygdala, are equally recruited in both schizophrenia and controls, but flat affect can also moderate activity in some other brain regions, notably in the left amygdala and parahippocampal gyrus bilaterally. There were no significant group differences in the volume of the amygdala.

  2. 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.

  3. 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.

  4. 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; Rankin, Katherine P

    2014-08-01

    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 overlooking

  5. 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.

  6. 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…

  7. Bayesian Inference using Neural Net Likelihood Models for Protein Secondary Structure Prediction

    Directory of Open Access Journals (Sweden)

    Seong-Gon Kim

    2011-06-01

    Full Text Available Several techniques such as Neural Networks, Genetic Algorithms, Decision Trees and other statistical or heuristic methods have been used to approach the complex non-linear task of predicting Alpha-helicies, Beta-sheets and Turns of a proteins secondary structure in the past. This project introduces a new machine learning method by using an offline trained Multilayered Perceptrons (MLP as the likelihood models within a Bayesian Inference framework to predict secondary structures proteins. Varying window sizes are used to extract neighboring amino acid information and passed back and forth between the Neural Net models and the Bayesian Inference process until there is a convergence of the posterior secondary structure probability.

  8. Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network

    Science.gov (United States)

    Geng, Xiangyi; Lu, Shizeng; Jiang, Mingshun; Sui, Qingmei; Lv, Shanshan; Xiao, Hang; Jia, Yuxi; Jia, Lei

    2018-06-01

    A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

  9. Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.

    Science.gov (United States)

    Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali

    2010-12-01

    The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  10. 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.

  11. Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

    Science.gov (United States)

    Gardner, Brian; Sporea, Ioana; Grüning, André

    2015-12-01

    Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we examine how multilayered networks of spiking neurons can learn to encode for input patterns using a fully temporal coding scheme. To this end, we introduce a new supervised learning rule, MultilayerSpiker, that can train spiking networks containing hidden layer neurons to perform transformations between spatiotemporal input and output spike patterns. The performance of the proposed learning rule is demonstrated in terms of the number of pattern mappings it can learn, the complexity of network structures it can be used on, and its classification accuracy when using multispike-based encodings. In particular, the learning rule displays robustness against input noise and can generalize well on an example data set. Our approach contributes to both a systematic understanding of how computations might take place in the nervous system and a learning rule that displays strong technical capability.

  12. 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.

  13. Forecasting the term structure of crude oil futures prices with neural networks

    Czech Academy of Sciences Publication Activity Database

    Baruník, Jozef; Malinská, B.

    2016-01-01

    Roč. 164, č. 1 (2016), s. 366-379 ISSN 0306-2619 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : Term structure * Nelson–Siegel model * Dynamic neural networks * Crude oil futures Subject RIV: AH - Economics Impact factor: 7.182, year: 2016 http://library.utia.cas.cz/separaty/2016/E/barunik-0453168.pdf

  14. Probabilistic analysis of structures involving random stress-strain behavior

    Science.gov (United States)

    Millwater, H. R.; Thacker, B. H.; Harren, S. V.

    1991-01-01

    The present methodology for analysis of structures with random stress strain behavior characterizes the uniaxial stress-strain curve in terms of (1) elastic modulus, (2) engineering stress at initial yield, (3) initial plastic-hardening slope, (4) engineering stress at point of ultimate load, and (5) engineering strain at point of ultimate load. The methodology is incorporated into the Numerical Evaluation of Stochastic Structures Under Stress code for probabilistic structural analysis. The illustrative problem of a thick cylinder under internal pressure, where both the internal pressure and the stress-strain curve are random, is addressed by means of the code. The response value is the cumulative distribution function of the equivalent plastic strain at the inner radius.

  15. 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.

  16. 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.

  17. 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...

  18. 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

  19. 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.

  20. Transcriptomic Analysis Of Purified Embryonic Neural Stem Cells From Zebrafish Embryos Reveals Signalling Pathways Involved In Glycine-dependent Neurogenesis

    Directory of Open Access Journals (Sweden)

    Eric eSAMARUT

    2016-03-01

    Full Text Available How is the initial set of neurons correctly established during the development of the vertebrate central nervous system? In the embryo, glycine and GABA are depolarizing due the immature chloride gradient, which is only reversed to become hyperpolarizing later in post-natal development. We previously showed that glycine regulates neurogenesis via paracrine signalling that promotes calcium transients in neural stem cells (NSCs and their differentiation into interneurons within the spinal cord of the zebrafish embryo. However, the subjacent molecular mechanisms are not yet understood. Our previous work suggests that early neuronal progenitors were not differentiating correctly in the developing spinal cord. As a result, we aimed at identifying the downstream molecular mechanisms involved specifically in NSCs during glycine-dependent embryonic neurogenesis. Using a gfap:GFP transgenic line, we successfully purified NSCs by fluorescence-activated cell sorting (FACS from whole zebrafish embryos and in embryos in which the glycine receptor was knocked down. The strength of this approach is that it focused on the NSC population while tackling the biological issue in an in vivo context in whole zebrafish embryos. After sequencing the transcriptome by RNA-sequencing, we analyzed the genes whose expression was changed upon disruption of glycine signalling and we confirmed the differential expression by independent RTqPCR assay. While over a thousand genes showed altered expression levels, through pathway analysis we identified 14 top candidate genes belonging to five different canonical signalling pathways (signalling by calcium, TGF-beta, sonic hedgehog, Wnt and p53-related apoptosis that are likely to mediate the promotion of neurogenesis by glycine.

  1. 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.

  2. Structural and functional involvement of amygdale in posttraumatic stress disorder

    International Nuclear Information System (INIS)

    Hakamata, Yuko; Matsuoka, Yutaka

    2007-01-01

    Pathophysiological imaging studies of brain neuro-network concerned with posttraumatic stress disorder (PTSD) have given several models, where the interaction in the amygdala-ventral/medial prefrontal cortex-hippocampus (Am-vmPFC-Hp) system is widely noticed. This paper describes the review of the structure, function and functional connectivity of Am in PTSD in relation to the Am-vmPFC-Hp system. For the structure of Am in PTSD, many studies by MRI have shown that its volume is unchanged but, exceptionally, authors have found the significant 6% volume reduction. Increased functional activity of Am has been demonstrated in PTSD by positron emission tomography (PET), but refuting findings are still presented. Studies in a larger scale are awaited for conclusion. The functional connectivity of Am in PTSD seems still controversial in an aspect of its direction in the Am-vmPFC-Hp system and participation of other systems, not studied hitherto, is thought possible. Authors expect further progress of PTSD imaging study not only from its pathophysiologic aspect but also from its therapeutic (mental and medical) view, which can compensate our knowledge of PTSD from both standpoints. (R.T.)

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

    Science.gov (United States)

    Mrówczyńska, Maria

    2016-06-01

    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. 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.

  5. Different Neural Networks are Involved in Cross-Modal Non-Spatial Inhibition of Return (IOR: The Effect of the Sensory Modality of Behavioral Targets

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    Qi Chen

    2011-10-01

    Full Text Available We employed a novel cross-modal non-spatial inhibition of return (IOR paradigm with fMRI to investigate whether object concept is organized by supramodal or modality-specific systems. A precue-neutral cue-target sequence was presented and participants were asked to discriminate whether the target was a dog or a cat. The precue and the target could be either a picture or vocalization of a dog or a cat. The neutral cue (bird was always from the same modality as the precue. Behaviorally, for both visual and auditory targets, the main effect of cue validity was the only significant effect, p<0.01, with equivalent effects for within- and cross-modal IOR. Neurally, for visual targets, left inferior frontal gyrus and left medial temporal gyrus showed significantly higher neural activity in cued than uncued condition, irrespective of the precue-target relationship, indicating that the two areas are involved in inhibiting a supramodal representation of previously attended object concept. For auditory targets, left lateral occipital gyrus and right postcentral gyrus showed significantly higher neural activity in uncued than cued condition irrespective of the cue-target relationship, indicating that the two areas are involved in creating a new supramodal representation when a novel object concept appears.

  6. 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.

  7. 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.

  8. Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

    Science.gov (United States)

    Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

    2018-03-01

    Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

  9. Augmented neural networks and problem structure-based heuristics for the bin-packing problem

    Science.gov (United States)

    Kasap, Nihat; Agarwal, Anurag

    2012-08-01

    In this article, we report on a research project where we applied augmented-neural-networks (AugNNs) approach for solving the classical bin-packing problem (BPP). AugNN is a metaheuristic that combines a priority rule heuristic with the iterative search approach of neural networks to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also propose a decomposition approach for solving harder BPP, in which subproblems are solved using a combination of AugNN approach and heuristics that exploit the problem structure. We discuss the characteristics of problems on which such problem structure-based heuristics could be applied. We empirically show the effectiveness of the AugNN and the decomposition approach on many benchmark problems in the literature. For the 1210 benchmark problems tested, 917 problems were solved to optimality and the average gap between the obtained solution and the upper bound for all the problems was reduced to under 0.66% and computation time averaged below 33 s per problem. We also discuss the computational complexity of our approach.

  10. 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...

  11. 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

  12. 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...

  13. 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.

  14. Prediction of the Fundamental Period of Infilled RC Frame Structures Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Panagiotis G. Asteris

    2016-01-01

    Full Text Available The fundamental period is one of the most critical parameters for the seismic design of structures. There are several literature approaches for its estimation which often conflict with each other, making their use questionable. Furthermore, the majority of these approaches do not take into account the presence of infill walls into the structure despite the fact that infill walls increase the stiffness and mass of structure leading to significant changes in the fundamental period. In the present paper, artificial neural networks (ANNs are used to predict the fundamental period of infilled reinforced concrete (RC structures. For the training and the validation of the ANN, a large data set is used based on a detailed investigation of the parameters that affect the fundamental period of RC structures. The comparison of the predicted values with analytical ones indicates the potential of using ANNs for the prediction of the fundamental period of infilled RC frame structures taking into account the crucial parameters that influence its value.

  15. 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.

  16. 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.

  17. Community structure analysis of rejection sensitive personality profiles: A common neural response to social evaluative threat?

    Science.gov (United States)

    Kortink, Elise D; Weeda, Wouter D; Crowley, Michael J; Gunther Moor, Bregtje; van der Molen, Melle J W

    2018-06-01

    Monitoring social threat is essential for maintaining healthy social relationships, and recent studies suggest a neural alarm system that governs our response to social rejection. Frontal-midline theta (4-8 Hz) oscillatory power might act as a neural correlate of this system by being sensitive to unexpected social rejection. Here, we examined whether frontal-midline theta is modulated by individual differences in personality constructs sensitive to social disconnection. In addition, we examined the sensitivity of feedback-related brain potentials (i.e., the feedback-related negativity and P3) to social feedback. Sixty-five undergraduate female participants (mean age = 19.69 years) participated in the Social Judgment Paradigm, a fictitious peer-evaluation task in which participants provided expectancies about being liked/disliked by peer strangers. Thereafter, they received feedback signaling social acceptance/rejection. A community structure analysis was employed to delineate personality profiles in our data. Results provided evidence of two subgroups: one group scored high on attachment-related anxiety and fear of negative evaluation, whereas the other group scored high on attachment-related avoidance and low on fear of negative evaluation. In both groups, unexpected rejection feedback yielded a significant increase in theta power. The feedback-related negativity was sensitive to unexpected feedback, regardless of valence, and was largest for unexpected rejection feedback. The feedback-related P3 was significantly enhanced in response to expected social acceptance feedback. Together, these findings confirm the sensitivity of frontal midline theta oscillations to the processing of social threat, and suggest that this alleged neural alarm system behaves similarly in individuals that differ in personality constructs relevant to social evaluation.

  18. Crustal block structure by GPS data using neural network in the Northern Tien Shan

    Science.gov (United States)

    Kostuk, A.; Carmenate, D.

    2010-05-01

    For over ten years regular GPS measurements have been carried out by Research Station RAS in the Central Asia. The results of these measurements have not only proved the conclusion that the Earth's crust meridional compression equals in total about 17 mm/year from the Tarim massif to the Kazakh shield, but have also allowed estimating deformation behavior in the region. As is known, deformation behavior of continental crust is an actively discussed issue. On the one hand, the Earth's crust is presented as a set of microplates (blocks) and deformation here is a result of shifting along the blocks boundaries, on the other hand, lithospheric deformation is distributed by volume and meets the rheological model of nonlinear viscous fluid. This work represents an attempt to detect the block structure of the surface of the Northern Tien Shan using GPS velocity fields. As a significant difference from analogous works, appears the vector field clustering with the help of neural network used as a classifier by many criteria that allows dividing input space into areas and using of all three components of GPS velocity. In this case, we use such a feature of neural networks as self-organization. Among the mechanisms of self-organization there are two main classes: self-organization based on the Hebb associative rule and the mechanism of neuronal competition based on the generalized Kohonen rule. In this case, we use an approach of self-organizing networks in which we take neuronal competition as an algorithm for their training. As a rule, these are single-layer networks where each neuron is connected to all components of m-dimensional input vector. GPS vectors of the Central Asian velocity field located within the territory of the Northern Tien Shan were used as input patterns. Measurements at GPS sites were fulfilled in 36 hour-long sessions by double-frequency receivers Trimble and Topcon. In so doing, measurement discreteness equaled 30 seconds; the data were processed by

  19. 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.

  20. T1r3 taste receptor involvement in gustatory neural responses to ethanol and oral ethanol preference.

    Science.gov (United States)

    Brasser, Susan M; Norman, Meghan B; Lemon, Christian H

    2010-05-01

    Elevated alcohol consumption is associated with enhanced preference for sweet substances across species and may be mediated by oral alcohol-induced activation of neurobiological substrates for sweet taste. Here, we directly examined the contribution of the T1r3 receptor protein, important for sweet taste detection in mammals, to ethanol intake and preference and the neural processing of ethanol taste by measuring behavioral and central neurophysiological responses to oral alcohol in T1r3 receptor-deficient mice and their C57BL/6J background strain. T1r3 knockout and wild-type mice were tested in behavioral preference assays for long-term voluntary intake of a broad concentration range of ethanol, sucrose, and quinine. For neurophysiological experiments, separate groups of mice of each genotype were anesthetized, and taste responses to ethanol and stimuli of different taste qualities were electrophysiologically recorded from gustatory neurons in the nucleus of the solitary tract. Mice lacking the T1r3 receptor were behaviorally indifferent to alcohol (i.e., ∼50% preference values) at concentrations typically preferred by wild-type mice (5-15%). Central neural taste responses to ethanol in T1r3-deficient mice were significantly lower compared with C57BL/6J controls, a strain for which oral ethanol stimulation produced a concentration-dependent activation of sweet-responsive NTS gustatory neurons. An attenuated difference in ethanol preference between knockouts and controls at concentrations >15% indicated that other sensory and/or postingestive effects of ethanol compete with sweet taste input at high concentrations. As expected, T1r3 knockouts exhibited strongly suppressed behavioral and neural taste responses to sweeteners but did not differ from wild-type mice in responses to prototypic salt, acid, or bitter stimuli. These data implicate the T1r3 receptor in the sensory detection and transduction of ethanol taste.

  1. 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.

  2. 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.…

  3. Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

    Science.gov (United States)

    Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

    2015-01-01

    Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

  4. 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.

  5. I think therefore I am: Rest-related prefrontal cortex neural activity is involved in generating the sense of self.

    Science.gov (United States)

    Gruberger, M; Levkovitz, Y; Hendler, T; Harel, E V; Harari, H; Ben Simon, E; Sharon, H; Zangen, A

    2015-05-01

    The sense of self has always been a major focus in the psychophysical debate. It has been argued that this complex ongoing internal sense cannot be explained by any physical measure and therefore substantiates a mind-body differentiation. Recently, however, neuro-imaging studies have associated self-referential spontaneous thought, a core-element of the ongoing sense of self, with synchronous neural activations during rest in the medial prefrontal cortex (PFC), as well as the medial and lateral parietal cortices. By applying deep transcranial magnetic stimulation (TMS) over human PFC before rest, we disrupted activity in this neural circuitry thereby inducing reports of lowered self-awareness and strong feelings of dissociation. This effect was not found with standard or sham TMS, or when stimulation was followed by a task instead of rest. These findings demonstrate for the first time a critical, causal role of intact rest-related PFC activity patterns in enabling integrated, enduring, self-referential mental processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. A Neural Circuit Mechanism for the Involvements of Dopamine in Effort-Related Choices: Decay of Learned Values, Secondary Effects of Depletion, and Calculation of Temporal Difference Error

    Science.gov (United States)

    2018-01-01

    Abstract Dopamine has been suggested to be crucially involved in effort-related choices. Key findings are that dopamine depletion (i) changed preference for a high-cost, large-reward option to a low-cost, small-reward option, (ii) but not when the large-reward option was also low-cost or the small-reward option gave no reward, (iii) while increasing the latency in all the cases but only transiently, and (iv) that antagonism of either dopamine D1 or D2 receptors also specifically impaired selection of the high-cost, large-reward option. The underlying neural circuit mechanisms remain unclear. Here we show that findings i–iii can be explained by the dopaminergic representation of temporal-difference reward-prediction error (TD-RPE), whose mechanisms have now become clarified, if (1) the synaptic strengths storing the values of actions mildly decay in time and (2) the obtained-reward-representing excitatory input to dopamine neurons increases after dopamine depletion. The former is potentially caused by background neural activity–induced weak synaptic plasticity, and the latter is assumed to occur through post-depletion increase of neural activity in the pedunculopontine nucleus, where neurons representing obtained reward exist and presumably send excitatory projections to dopamine neurons. We further show that finding iv, which is nontrivial given the suggested distinct functions of the D1 and D2 corticostriatal pathways, can also be explained if we additionally assume a proposed mechanism of TD-RPE calculation, in which the D1 and D2 pathways encode the values of actions with a temporal difference. These results suggest a possible circuit mechanism for the involvements of dopamine in effort-related choices and, simultaneously, provide implications for the mechanisms of TD-RPE calculation. PMID:29468191

  7. 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.

  8. 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.

  9. Identification of crystalline structures using Moessbauer parameters and artificial neural network

    International Nuclear Information System (INIS)

    Salles, E.O.T.; Souza Junior, P.A. De; Garg, V.K.

    1995-01-01

    Moessbauer spectroscopy is a useful technique for characterizing the valences, electronic and magnetic states, coordination symmetric and site occupancies of Fe cations. The Moessbauer parameters of Isomer Shift (I.S.) and Quadrupole Splitting (Q.S.) are useful to distinguish paramagnetic ferrous and ferric ions in several substances, while the internal magnetic field provides information on the crystallinity. A correlation is being sought between Moessbauer parameters and several structure properties of some iron-containing minerals using Artificial Neural Networks (ANN). Distinct regions of crystalline structures are defined when any two parameters are plotted, but in several cases superposition of these regions leads to erroneous conclusions. We have tried to eliminate this difficulty by using convenient axes. These axes form n-dimensional vectors as input to our ANN. In recent years ANN has shown to be a powerful technique to solve problems as pattern recognition, optimization, preview ups and downs in stock market, automatic control and identification of a mineral from a Moessbauer spectrum of Moessbauer data bank. Using ANN we have been successful in identification of crystalline structures from plots of Moessbauer spectral parameters of I.S., Q.S., and structure using Moessbauer parameters of I.S., Q.S., and polyhedral volume of a coordination site are presented. (author) 28 refs.; 4 figs.; 2 tabs

  10. Relationship among visual field, blood flow, and neural structure measurements in glaucoma.

    Science.gov (United States)

    Hwang, John C; Konduru, Ranjith; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Varma, Rohit; Sehi, Mitra; Greenfield, David S; Sadda, Srinivas R; Huang, David

    2012-05-17

    To determine the relationship among visual field, neural structural, and blood flow measurements in glaucoma. Case-control study. Forty-seven eyes of 42 patients with perimetric glaucoma were age-matched with 27 normal eyes of 27 patients. All patients underwent Doppler Fourier-domain optical coherence tomography to measure retinal blood flow and standard glaucoma evaluation with visual field testing and quantitative structural imaging. Linear regression analysis was performed to analyze the relationship among visual field, blood flow, and structure, after all variables were converted to logarithmic decibel scale. Retinal blood flow was reduced in glaucoma eyes compared to normal eyes (P flow and structural loss of rim area and retinal nerve fiber layer (RNFL). There was no correlation or paradoxical correlation between blood flow and structure. Multivariate regression analysis revealed that reduced blood flow and structural loss are independent predictors of visual field loss. Each dB decrease in blood flow was associated with at least 1.62 dB loss in mean deviation (P ≤ 0.001), whereas each dB decrease in rim area and RNFL was associated with 1.15 dB and 2.56 dB loss in mean deviation, respectively (P ≤ 0.03). There is a close link between reduced retinal blood flow and visual field loss in glaucoma that is largely independent of structural loss. Further studies are needed to elucidate the causes of the vascular dysfunction and potential avenues for therapeutic intervention. Blood flow measurement may be useful as an independent assessment of glaucoma severity.

  11. Cell death in neural precursor cells and neurons before neurite formation prevents the emergence of abnormal neural structures in the Drosophila optic lobe.

    Science.gov (United States)

    Hara, Yusuke; Sudo, Tatsuya; Togane, Yu; Akagawa, Hiromi; Tsujimura, Hidenobu

    2018-04-01

    Programmed cell death is a conserved strategy for neural development both in vertebrates and invertebrates and is recognized at various developmental stages in the brain from neurogenesis to adulthood. To understand the development of the central nervous system, it is essential to reveal not only molecular mechanisms but also the role of neural cell death (Pinto-Teixeira et al., 2016). To understand the role of cell death in neural development, we investigated the effect of inhibition of cell death on optic lobe development. Our data demonstrate that, in the optic lobe of Drosophila, cell death occurs in neural precursor cells and neurons before neurite formation and functions to prevent various developmental abnormalities. When neuronal cell death was inhibited by an effector caspase inhibitor, p35, multiple abnormal neuropil structures arose during optic lobe development-e.g., enlarged or fused neuropils, misrouted neurons and abnormal neurite lumps. Inhibition of cell death also induced morphogenetic defects in the lamina and medulla development-e.g., failures in the separation of the lamina and medulla cortices and the medulla rotation. These defects were reproduced in the mutant of an initiator caspase, dronc. If cell death was a mechanism for removing the abnormal neuropil structures, we would also expect to observe them in mutants defective for corpse clearance. However, they were not observed in these mutants. When dead cell-membranes were visualized with Apoliner, they were observed only in cortices and not in neuropils. These results suggest that the cell death occurs before mature neurite formation. Moreover, we found that inhibition of cell death induced ectopic neuroepithelial cells, neuroblasts and ganglion mother cells in late pupal stages, at sites where the outer and inner proliferation centers were located at earlier developmental stages. Caspase-3 activation was observed in the neuroepithelial cells and neuroblasts in the proliferation centers

  12. Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

    Science.gov (United States)

    Fei, Juntao; Lu, Cheng

    2018-04-01

    In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

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

    Science.gov (United States)

    El-Nagar, Ahmad M

    2018-01-01

    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.

  14. 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.

  15. Structural Reliability: An Assessment Using a New and Efficient Two-Phase Method Based on Artificial Neural Network and a Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    Naser Kazemi Elaki

    2016-06-01

    Full Text Available In this research, a two-phase algorithm based on the artificial neural network (ANN and a harmony search (HS algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. The proposed method involves the generation of datasets to be used specifically for training by Finite Element analysis, to establish an ANN model using a proven ANN model in the reliability assessment process as an analyzer for structures, and finally estimate the reliability index and failure probability by using the HS algorithm, without any requirements for the explicit form of limit state function. The proposed algorithm is investigated here, and its accuracy and efficiency are demonstrated by using several numerical examples. The results obtained show that the proposed algorithm gives an appropriate estimate for the assessment of reliability of structures.

  16. 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.

  17. Identifying the Integrated Neural Networks Involved in Capsaicin-Induced Pain Using fMRI in Awake TRPV1 Knockout and Wild-Type Rats

    Directory of Open Access Journals (Sweden)

    Jason Richard Yee

    2015-02-01

    Full Text Available In the present study, we used functional MRI in awake rats to investigate the pain response that accompanies intradermal injection of capsaicin into the hindpaw. To this end, we used BOLD imaging together with a 3D segmented, annotated rat atlas and computational analysis to identify the integrated neural circuits involved in capsaicin-induced pain. The specificity of the pain response to capsaicin was tested in a transgenic model that contains a biallelic deletion of the gene encoding for the transient receptor potential cation channel subfamily V member 1 (TRPV1. Capsaicin is an exogenous ligand for the TRPV1 receptor, and in wild-type rats, activated the putative pain neural circuit. In addition, capsaicin-treated wild-type rats exhibited activation in brain regions comprising the Papez circuit and habenular system, systems that play important roles in the integration of emotional information, and learning and memory of aversive information, respectively. As expected, capsaicin administration to TRPV1-KO rats failed to elicit the robust BOLD activation pattern observed in wild-type controls. However, the intradermal injection of formalin elicited a significant activation of the putative pain pathway as represented by such areas as the anterior cingulate, somatosensory cortex, parabrachial nucleus, and periaqueductal gray. Notably, comparison of neural responses to capsaicin in wild-type versus knock-out rats uncovered evidence that capsaicin may function in an antinociceptive capacity independent of TRPV1 signaling. Our data suggest that neuroimaging of pain in awake, conscious animals has the potential to inform the neurobiological basis of full and integrated perceptions of pain.

  18. Analysis of Neural Stem Cells from Human Cortical Brain Structures In Vitro.

    Science.gov (United States)

    Aleksandrova, M A; Poltavtseva, R A; Marei, M V; Sukhikh, G T

    2016-05-01

    Comparative immunohistochemical analysis of the neocortex from human fetuses showed that neural stem and progenitor cells are present in the brain throughout the gestation period, at least from week 8 through 26. At the same time, neural stem cells from the first and second trimester fetuses differed by the distribution, morphology, growth, and quantity. Immunocytochemical analysis of neural stem cells derived from fetuses at different gestation terms and cultured under different conditions showed their differentiation capacity. Detailed analysis of neural stem cell populations derived from fetuses on gestation weeks 8-9, 18-20, and 26 expressing Lex/SSEA1 was performed.

  19. 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.

  20. Multi-Level Interval Estimation for Locating damage in Structures by Using Artificial Neural Networks

    International Nuclear Information System (INIS)

    Pan Danguang; Gao Yanhua; Song Junlei

    2010-01-01

    A new analysis technique, called multi-level interval estimation method, is developed for locating damage in structures. In this method, the artificial neural networks (ANN) analysis method is combined with the statistics theory to estimate the range of damage location. The ANN is multilayer perceptron trained by back-propagation. Natural frequencies and modal shape at a few selected points are used as input to identify the location and severity of damage. Considering the large-scale structures which have lots of elements, multi-level interval estimation method is developed to reduce the estimation range of damage location step-by-step. Every step, estimation range of damage location is obtained from the output of ANN by using the method of interval estimation. The next ANN training cases are selected from the estimation range after linear transform, and the output of new ANN estimation range of damage location will gained a reduced estimation range. Two numerical example analyses on 10-bar truss and 100-bar truss are presented to demonstrate the effectiveness of the proposed method.

  1. 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.

  2. Acoustic leak detection at complicated geometrical structures using fuzzy logic and neural networks

    International Nuclear Information System (INIS)

    Hessel, G.; Schmitt, W.; Weiss, F.P.

    1993-10-01

    An acoustic method based on pattern recognition is being developed. During the learning phase, the localization classifier is trained with sound patterns that are generated with simulated leaks at all locations endangered by leak. The patterns are extracted from the signals of an appropriate sensor array. After training unknown leak positions can be recognized through comparison with the training patterns. The experimental part is performed at an acoustic 1:3 model of the reactor vessel and head and at an original VVER-440 reactor in the former NPP Greifswald. The leaks were simulated at the vessel head using mobile sound sources driven either by compressed air, a piezoelectric transmitter or by a thin metal blade excited through a jet of compressed air. The sound patterns of the simulated leaks are simultaneously detected with an AE-sensor array and with high frequency microphones measuring structure-borne sound and airborne sound, respectively. Pattern classifiers based on Fuzzy Pattern Classification (FPC) and Artificial Neural Networks (ANN) are currently tested for validation of the acoustic emission-sensor array (FPC), leak localization via structure-borne sound (FPC) and the leak localization using microphones (ANN). The initial results show the used classifiers principally to be capable of detecting and locating leaks, but they also show that further investigations are necessary to develop a reliable method applicable at NPPs. (orig./HP)

  3. Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.

    Science.gov (United States)

    Mendenhall, Jeffrey; Meiler, Jens

    2016-02-01

    Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.

  4. 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

    2016-01-01

    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 frontal regions may underlie age-related decline of working memory function.

  5. 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

    . The deviations were mostly in the posterior part of the dorsum sellae. Individuals with VCFS had increased cranial base angles. The results of this study combined with the information in the literature on the main defects in VCFS (palatal abnormalities, cardiac anomalies, thymic hypoplasia or aplasia......, hypothyroidism, and posterior brain abnormality), suggest involvement of a specific developmental field....

  6. Neural Resilience to Traumatic Brain Injury: Identification of Bioactive Metabolites of Docosahexaenoic Acids Involved in Neuroprotection and Recovery

    Science.gov (United States)

    2015-05-01

    Involved in Neuroprotection and Recovery PRINCIPAL INVESTIGATOR: Hee-Yong Kim CONTRACTING ORGANIZATION: Henry M. Jackson Foundation for the...O’Dell DM, Lyeth BG, Jenkins LW (1994) The rotarod test: an evaluation of its effectiveness in assessing motor deficits following traumatic brain injury

  7. Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis.

    Science.gov (United States)

    Adamović, Vladimir M; Antanasijević, Davor Z; Ristić, Mirjana Đ; Perić-Grujić, Aleksandra A; Pocajt, Viktor V

    2017-01-01

    This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development level. Proper modelling of MSW generation is essential for the planning of MSW management system as well as for the simulation of various environmental impact scenarios. The main objective of this work was to examine the potential influence of economy crisis (global or local) on the forecast of MSW generation obtained by the GRNN model. The existence of the so-called structural breaks that occur because of the economic crisis in the studied period (2000-2012) for each country was determined and confirmed using the Chow test and Quandt-Andrews test. Two GRNN models, one which did not take into account the influence of the economic crisis (GRNN) and another one which did (SB-GRNN), were developed. The novelty of the applied method is that it uses broadly available social, economic and demographic indicators and indicators of sustainability, together with GRNN and structural break testing for the prediction of MSW generation at the national level. The obtained results demonstrate that the SB-GRNN model provide more accurate predictions than the model which neglected structural breaks, with a mean absolute percentage error (MAPE) of 4.0 % compared to 6.7 % generated by the GRNN model. The proposed model enhanced with structural breaks can be a viable alternative for a more accurate prediction of MSW generation at the national level, especially for developing countries for which a lack of MSW data is notable.

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

    Science.gov (United States)

    Sihvonen, Aleksi J; Ripollés, Pablo; Rodríguez-Fornells, Antoni; Soinila, Seppo; Särkämö, Teppo

    2017-01-01

    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 the lesions

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

    Science.gov (United States)

    Sihvonen, Aleksi J.; Ripollés, Pablo; Rodríguez-Fornells, Antoni; Soinila, Seppo; Särkämö, Teppo

    2017-01-01

    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 the lesions

  10. 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

  11. Chaotic diagonal recurrent neural network

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Zhang Yi

    2012-01-01

    We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

  12. A neural network approach to the study of dynamics and structure of molecular systems

    International Nuclear Information System (INIS)

    Getino, C.; Sumpter, B.G.; Noid, D.W.

    1994-01-01

    Neural networks are used to study intramolecular energy flow in molecular systems (tetratomics to macromolecules), developing new techniques for efficient analysis of data obtained from molecular-dynamics and quantum mechanics calculations. Neural networks can map phase space points to intramolecular vibrational energies along a classical trajectory (example of complicated coordinate transformation), producing reasonably accurate values for any region of the multidimensional phase space of a tetratomic molecule. Neural network energy flow predictions are found to significantly enhance the molecular-dynamics method to longer time-scales and extensive averaging of trajectories for macromolecular systems. Pattern recognition abilities of neural networks can be used to discern phase space features. Neural networks can also expand model calculations by interpolation of costly quantum mechanical ab initio data, used to develop semiempirical potential energy functions

  13. The emission of α,ω-diphenylpolyenes: A model involving several molecular structures

    International Nuclear Information System (INIS)

    Catalan, Javier

    2007-01-01

    Available photophysical evidence for the emission of α,ω-diphenylpolyenes is shown to be consistent with a previously reported model [J. Catalan, J.L.G. de Paz, J. Chem. Phys. 124 (2006) 034306] involving two electronically excited molecular structures of 1B u and C s symmetry, respectively. The 1B u structure is produced by direct light absorption from the all-trans form of the α,ω-diphenylpolyene in the ground state and its emission exhibits mirror symmetry with respect to the absorption of the compound. On the other hand, the C s structure is generated from the 1B u structure of the α,ω-diphenylpolyene by rotation about a C-C single bond in the polyene chain, its emission being red-shifted with respect to the previous one and exhibiting markedly decreased vibrational structure. At room temperature, both emissions give the excitation spectrum, which are ascribed to the first absorption band for the compound. It is shown that some polyenes may exist in more than one structure of C s symmetry in the excited electronic state with lower energy than that of the 1B u state, from which the C s structures are produced. Hence, more than one electronic structure may be involved in the deactivation processes of the 1B u state, which is initially populated upon photo-excitation of the polyene molecule in the ground electronic state

  14. 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…

  15. Structure and activity of lacustrine sediment bacteria involved in nutrient and iron cycles

    DEFF Research Database (Denmark)

    da Silva Martins, Gilberto Jorge; Terada, Akihiko; Ribeiro, Daniel C

    2011-01-01

    Knowledge of the bacterial community structure in sediments is essential to better design restoration strategies for eutrophied lakes. In this regard, the aim of this study was to quantify the abundance and activity of bacteria involved in nutrient and iron cycling in sediments from four Azorean...

  16. Unique mosaicism of structural chromosomal rearrangement: is chromosome 18 preferentially involved?

    NARCIS (Netherlands)

    Pater, J.M. de; Smeets, D.F.C.M.; Scheres, J.M.J.C.

    2003-01-01

    The mentally normal mother of a 4-year-old boy with del(18)(q21.3) syndrome was tested cytogenetically to study the possibility of an inherited structural rearrangement of chromosome 18. She was found to carry an unusual mosaicism involving chromosomes 18 and 21. Two unbalanced cell lines were seen

  17. Structures of two exonucleases involved in controlled RNA turnover in yeast

    DEFF Research Database (Denmark)

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

    divalent cations. The Pop2p structure reveals that the ability of this enzyme to degrade poly(A)/(U)/(C), but not poly(G) may be determined by structural hindrance of interaction with this specific nucleotide. In Rrp6p, mutations known to confer specific RNA degradation phenotypes in yeast nuclei can now...... rid of aberrant RNAs. Here we describe the structures of two 3'-5' exonucleases involved in controlled RNA decay in yeast, Pop2p and Rrp6p. Rrp6p is associated with the nuclear exosome where it participates in the degradation of improperly processed precursor mRNAs and trimming of stable RNAs [1]. Pop...

  18. 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.

  19. Development of relative humidity models by using optimized neural network structures

    Energy Technology Data Exchange (ETDEWEB)

    Martinez-romero, A.; Ortega, J. F.; Juan, J. A.; Tarjuelo, J. M.; Moreno, M. A.

    2010-07-01

    Climate has always had a very important role in life on earth, as well as human activity and health. The influence of relative humidity (RH) in controlled environments (e.g. industrial processes in agro-food processing, cold storage of foods such as fruits, vegetables and meat, or controls in greenhouses) is very important. Relative humidity is a main factor in agricultural production and crop yield (due to the influence on crop water demand or the development and distribution of pests and diseases, for example). The main objective of this paper is to estimate RH [maximum (RHmax), average (RHave), and minimum (RHmin)] data in a specific area, being applied to the Region of Castilla-La Mancha (C-LM) in this case, from available data at thermo-pluviometric weather stations. In this paper Artificial neural networks (ANN) are used to generate RH considering maximum and minimum temperatures and extraterrestrial solar radiation data. Model validation and generation is based on data from the years 2000 to 2008 from 44 complete agroclimatic weather stations. Relative errors are estimated as 1) spatial errors of 11.30%, 6.80% and 10.27% and 2) temporal errors of 10.34%, 6.59% and 9.77% for RHmin, RHmax and RHave, respectively. The use of ANNs is interesting in generating climate parameters from available climate data. For determining optimal ANN structure in estimating RH values, model calibration and validation is necessary, considering spatial and temporal variability. (Author) 44 refs.

  20. 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%.

  1. Bayesian inversion of surface wave data for discontinuities and velocity structure in the upper mantle using Neural Networks. Geologica Ultraiectina (287)

    NARCIS (Netherlands)

    Meier, U.

    2008-01-01

    We present a neural network approach to invert surface wave data for discontinuities and velocity structure in the upper mantle. We show how such a neural network can be trained on a set of random samples to give a continuous approximation to the inverse relation in a compact and computationally

  2. Topographic and functional neuroanatomical study of GABAergic disinhibitory striatum-nigral inputs and inhibitory nigrocollicular pathways: neural hodology recruiting the substantia nigra, pars reticulata, for the modulation of the neural activity in the inferior colliculus involved with panic-like emotions.

    Science.gov (United States)

    Castellan-Baldan, Lissandra; da Costa Kawasaki, Mateus; Ribeiro, Sandro José; Calvo, Fabrício; Corrêa, Vani Maria Alves; Coimbra, Norberto Cysne

    2006-08-01

    Considering the influence of the substantia nigra on mesencephalic neurons involved with fear-induced reactions organized in rostral aspects of the dorsal midbrain, the present work investigated the topographical and functional neuroanatomy of similar influence on caudal division of the corpora quadrigemina, addressing: (a) the neural hodology connecting the neostriatum, the substantia nigra, periaqueductal gray matter and inferior colliculus (IC) neural networks; (b) the influence of the inhibitory neostriatonigral-nigrocollicular GABAergic links on the control of the defensive behavior organized in the IC. The effects of the increase or decrease of activity of nigrocollicular inputs on defensive responses elicited by either electrical or chemical stimulation of the IC were also determined. Electrolytic or chemical lesions of the substantia nigra, pars reticulata (SNpr), decreased the freezing and escape behaviors thresholds elicited by electrical stimulation of the IC, and increased the behavioral responses evoked by the GABAA blockade in the same sites of the mesencephalic tectum (MT) electrically stimulated. These findings were corroborated by similar effects caused by microinjections of the GABAA-receptor agonist muscimol in the SNpr, followed by electrical and chemical stimulations of the IC. The GABAA blockade in the SNpr caused a significant increase in the defensive behavior thresholds elicited by electrical stimulation of the IC and a decrease in the mean incidence of panic-like responses induced by microinjections of bicuculline in the mesencephalic tectum (inferior colliculus). These findings suggest that the substantia nigra receives GABAergic inputs that modulate local and also inhibitory GABAergic outputs toward the IC. In fact, neurotracing experiments with fast blue and iontophoretic microinjections of biotinylated dextran amine either into the inferior colliculus or in the reticular division of the substantia nigra demonstrated a neural link

  3. Do neural tube defects lead to structural alterations in the human bladder?

    Science.gov (United States)

    Pazos, Helena M F; Lobo, Márcio Luiz de P; Costa, Waldemar S; Sampaio, Francisco J B; Cardoso, Luis Eduardo M; Favorito, Luciano Alves

    2011-05-01

    Anencephaly is the most severe neural tube defect in human fetuses. The objective of this paper is to analyze the structure of the bladder in anencephalic human fetuses. We studied 40 bladders of normal human fetuses (20 male and 20 female, aged 14 to 23 WPC) and 12 bladders of anencephalic fetuses (5 male and 7 female, aged 18 to 22 WPC). The bladders were removed and processed by routine histological techniques. Stereological analysis of collagen, elastic system fibers and smooth muscle was performed in sections. Data were expressed as volumetric density (Vv-%). The images were captured with Olympus BX51 microscopy and Olympus DP70 camera. The stereological analysis was done using the software Image Pro and Image J. For biochemical analysis, samples were fixed in acetone, and collagen concentrations were expressed as micrograms of hydroxyproline per mg of dry tissue. Means were statistically compared using the unpaired t-test (p<0.05). We observed a significant increase (p<0.0001) in the Vv of collagen in the bladders of anencephalic fetuses (69.71%) when compared to normal fetuses (52.74%), and a significant decrease (p<0.0001) in the Vv of smooth muscle cells in the bladders of anencephalic fetuses (23.96%) when compared to normal fetuses (38.35%). The biochemical analyses showed a higher concentration of total collagen in the bladders of anencephalic fetuses (37354 µg/mg) when compared to normal fetuses (48117 µg/mg, p<0.02). The structural alterations of the bladder found in this study may suggest the existence of functional alterations in the bladder of anencephalic human fetuses.

  4. 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.

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

    Science.gov (United States)

    Montigny, Chantale; Castellanos-Ryan, Natalie; Whelan, Robert; Banaschewski, Tobias; Barker, Gareth J; Büchel, Christian; Gallinat, Jürgen; Flor, Herta; Mann, Karl; Paillère-Martinot, Marie-Laure; Nees, Frauke; Lathrop, Mark; Loth, Eva; Paus, Tomas; Pausova, Zdenka; Rietschel, Marcella; Schumann, Gunter; Smolka, Michael N; Struve, Maren; Robbins, Trevor W; Garavan, Hugh; Conrod, Patricia J

    2013-01-01

    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.

  6. A Phenotypic Structure and Neural Correlates of Compulsive Behaviors in Adolescents

    Science.gov (United States)

    Montigny, Chantale; Castellanos-Ryan, Natalie; Whelan, Robert; Banaschewski, Tobias; Barker, Gareth J.; Büchel, Christian; Gallinat, Jürgen; Flor, Herta; Mann, Karl; Paillère-Martinot, Marie-Laure; Nees, Frauke; Lathrop, Mark; Loth, Eva; Paus, Tomas; Pausova, Zdenka; Rietschel, Marcella; Schumann, Gunter; Smolka, Michael N.; Struve, Maren; Robbins, Trevor W.; Garavan, Hugh; Conrod, Patricia J.

    2013-01-01

    Background 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. Method 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. Results 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. Conclusions 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. PMID:24244633

  7. 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.

  8. 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

    2008-11-01

    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.

  9. User involvement in structured violence risk management within forensic mental health facilities -- a systematic literature review.

    Science.gov (United States)

    Eidhammer, Gunnar; Fluttert, Frans A J; Bjørkly, Stål

    2014-10-01

    To examine empirical literature on user involvement in collaboration between patients and nurses. The scope of the review was limited to structured violence risk management interventions in forensic mental health settings. Violence in forensic mental health settings represents a significant problem for patients and staff. Structured violence risk management interventions in forensic mental health have been reported to ignore patient participation, despite the growing attention on user involvement in clinical practice. A systematic review. Searches were conducted in six databases: the Cochrane Systematic Reviews, MEDLINE, CINAHL, ProQuest, ScienceDirect and PsycINFO. Papers were assessed according to a predetermined set of inclusion and exclusion criteria. After searches of the reference lists of retrieved articles were conducted, only three papers met the inclusion criteria. This review has shown that empirical research on the topic of risk management interventions in which patients are involved is scarce. There is barely any research evidence of the clinical effect of user involvement approaches on violence risk management in forensic mental health practice. Therefore, we suggest that clinicians may learn from positive experiences concerning user involvement in general psychiatry and carefully adapt and test them out in the forensic treatment context. © 2014 John Wiley & Sons Ltd.

  10. Impact of pH on the structure and function of neural cadherin.

    Science.gov (United States)

    Jungles, Jared M; Dukes, Matthew P; Vunnam, Nagamani; Pedigo, Susan

    2014-12-02

    Neural (N-) cadherin is a transmembrane protein within adherens junctions that mediates cell-cell adhesion. It has 5 modular extracellular domains (EC1-EC5) that bind 3 calcium ions between each of the modules. Calcium binding is required for dimerization. N-Cadherin is involved in diverse processes including tissue morphogenesis, excitatory synapse formation and dynamics, and metastasis of cancer. During neurotransmission and tumorigenesis, fluctuations in extracellular pH occur, causing tissue acidosis with associated physiological consequences. Studies reported here aim to determine the effect of pH on the dimerization properties of a truncated construct of N-cadherin containing EC1-EC2. Since N-cadherin is an anionic protein, we hypothesized that acidification of solution would cause an increase in stability of the apo protein, a decrease in the calcium-binding affinity, and a concomitant decrease in the formation of adhesive dimer. The stability of the apo monomer was increased and the calcium-binding affinity was decreased at reduced pH, consistent with our hypothesis. Surprisingly, analytical SEC studies showed an increase in calcium-induced dimerization as solution pH decreased from 7.4 to 5.0. Salt-dependent dimerization studies indicated that electrostatic repulsion attenuates dimerization affinity. These results point to a possible electrostatic mechanism for moderating dimerization affinity of the Type I cadherin family. Extrapolating these results to cell adhesion in vivo leads to the assertion that decreased pH promotes adhesion by N-cadherin, thereby stabilizing synaptic junctions.

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

    KAUST Repository

    Zhang, Xuesong; Liang, Faming; Yu, Beibei; Zong, Ziliang

    2011-01-01

    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

  12. 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.

  13. 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

  14. 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

    2015-02-01

    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. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  15. Social and structural barriers to housing among street-involved youth who use illicit drugs.

    Science.gov (United States)

    Krüsi, Andrea; Fast, Danya; Small, Will; Wood, Evan; Kerr, Thomas

    2010-05-01

    In Canada, approximately 150,000 youth live on the street. Street-involvement and homelessness have been associated with various health risks, including increased substance use, blood-borne infections and sexually transmitted diseases. We undertook a qualitative study to better understand the social and structural barriers street-involved youth who use illicit drugs encounter when seeking housing. We conducted 38 semi-structured interviews with street-involved youth in Vancouver, Canada from May to October 2008. Interviewees were recruited from the At-risk Youth Study (ARYS) cohort, which follows youth aged 14 to 26 who have experience with illicit drug use. All interviews were thematically analyzed, with particular emphasis on participants' perspectives regarding their housing situation and their experiences seeking housing. Many street-involved youth reported feeling unsupported in their efforts to find housing. For the majority of youth, existing abstinence-focused shelters did not constitute a viable option and, as a result, many felt excluded from these facilities. Many youth identified inflexible shelter rules and a lack of privacy as outweighing the benefits of sleeping indoors. Single-room occupancy hotels (SROs) were reported to be the only affordable housing options, as many landlords would not rent to youth on welfare. Many youth reported resisting moving to SROs as they viewed them as unsafe and as giving up hope for a return to mainstream society. The findings of the present study shed light on the social and structural barriers street-involved youth face in attaining housing and challenge the popular view of youth homelessness constituting a lifestyle choice. Our findings point to the need for housing strategies that include safe, low threshold, harm reduction focused housing options for youth who engage in illicit substance use.

  16. Structural and neural network analyses of fracture systems at the Aespoe Hard Rock Laboratory, SE Sweden

    International Nuclear Information System (INIS)

    Sirat, M.

    1999-01-01

    The > 10,000 fractures documented in the 450 m deep Aespoe Hard Rock Laboratory (HRL) provide a unique opportunity to study brittle deformation of a Swedish bedrock mass. The fracture population consists of six major sets, one sub-horizontal and five sub-vertical. A classical structural analysis explored the interrelations between geometry and frequency of both dry and wet fractures with respect to depth and in-situ stresses. Three main findings are: In-situ stresses govern frequency distributions of dilated, hence water-bearing fractures. About 68.5% of sub-horizontal fractures are dilated in the thrust regime above a depth of ca. 230 m while 53% of sub-vertical fractures are dilated in the underlying wrench regime. Fractures curve both horizontally and vertically, a finding confirmed by the application of artificial neural networks that included Back-Propagation and Self-Organizing (Kohonen) networks. The asymmetry of the total fracture population and tilts of the sub-Cambrian peneplain demonstrates that multiple reactivations of fractures have tilted the Aespoe rock mass 6 deg to the west. The potential space problem raised by this tilt is negated by systematic curvature of steep fractures, some of which sole out to gently dipping fracture zones. Fractures probably developed their curvature when they formed deep in crystalline crust in Precambrian times but have since reactivated at shallow depths. These findings add significantly to the conceptual model of Aespoe and should be taken into account in future studies regarding the isolation of Sweden's high-grade radioactive waste in crystalline bedrock

  17. 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.

  18. 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.

  19. 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.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

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

    International Nuclear Information System (INIS)

    Mieloszyk, Magdalena; Skarbek, Lukasz; Ostachowicz, Wieslaw; Krawczuk, Marek

    2011-01-01

    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.

  2. 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.

  3. 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.

  4. Dissecting CNBP, a zinc-finger protein required for neural crest development, in its structural and functional domains.

    Science.gov (United States)

    Armas, Pablo; Agüero, Tristán H; Borgognone, Mariana; Aybar, Manuel J; Calcaterra, Nora B

    2008-10-17

    Cellular nucleic-acid-binding protein (CNBP) plays an essential role in forebrain and craniofacial development by controlling cell proliferation and survival to mediate neural crest expansion. CNBP binds to single-stranded nucleic acids and displays nucleic acid chaperone activity in vitro. The CNBP family shows a conserved modular organization of seven Zn knuckles and an arginine-glycine-glycine (RGG) box between the first and second Zn knuckles. The participation of these structural motifs in CNBP biochemical activities has still not been addressed. Here, we describe the generation of CNBP mutants that dissect the protein into regions with structurally and functionally distinct properties. Mutagenesis approaches were followed to generate: (i) an amino acid replacement that disrupted the fifth Zn knuckle; (ii) N-terminal deletions that removed the first Zn knuckle and the RGG box, or the RGG box alone; and (iii) a C-terminal deletion that eliminated the three last Zn knuckles. Mutant proteins were overexpressed in Escherichia coli, purified, and used to analyze their biochemical features in vitro, or overexpressed in Xenopus laevis embryos to study their function in vivo during neural crest cell development. We found that the Zn knuckles are required, but not individually essential, for CNBP biochemical activities, whereas the RGG box is essential for RNA-protein binding and nucleic acid chaperone activity. Removal of the RGG box allowed CNBP to preserve a weak single-stranded-DNA-binding capability. A mutant mimicking the natural N-terminal proteolytic CNBP form behaved as the RGG-deleted mutant. By gain-of-function and loss-of-function experiments in Xenopus embryos, we confirmed the participation of CNBP in neural crest development, and we demonstrated that the CNBP mutants lacking the N-terminal region or the RGG box alone may act as dominant negatives in vivo. Based on these data, we speculate about the existence of a specific proteolytic mechanism for the

  5. Structure-from-motion: dissociating perception, neural persistence, and sensory memory of illusory depth and illusory rotation.

    Science.gov (United States)

    Pastukhov, Alexander; Braun, Jochen

    2013-02-01

    In the structure-from-motion paradigm, physical motion on a screen produces the vivid illusion of an object rotating in depth. Here, we show how to dissociate illusory depth and illusory rotation in a structure-from-motion stimulus using a rotationally asymmetric shape and reversals of physical motion. Reversals of physical motion create a conflict between the original illusory states and the new physical motion: Either illusory depth remains constant and illusory rotation reverses, or illusory rotation stays the same and illusory depth reverses. When physical motion reverses after the interruption in presentation, we find that illusory rotation tends to remain constant for long blank durations (T (blank) ≥ 0.5 s), but illusory depth is stabilized if interruptions are short (T (blank) ≤ 0.1 s). The stability of illusory depth over brief interruptions is consistent with the effect of neural persistence. When this is curtailed using a mask, stability of ambiguous vision (for either illusory depth or illusory rotation) is disrupted. We also examined the selectivity of the neural persistence of illusory depth. We found that it relies on a static representation of an interpolated illusory object, since changes to low-level display properties had little detrimental effect. We discuss our findings with respect to other types of history dependence in multistable displays (sensory stabilization memory, neural fatigue, etc.). Our results suggest that when brief interruptions are used during the presentation of multistable displays, switches in perception are likely to rely on the same neural mechanisms as spontaneous switches, rather than switches due to the initial percept choice at the stimulus onset.

  6. 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...... to determine the damper current based on the derived optimal damper force. For that reason an inverse MR damper model is also designed based on the neural network identification of the particular rotary MR damper. The performance of the proposed controller is compared to that of an optimal pure viscous damper...

  7. 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

  8. 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

  9. 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

  10. P-proteins in Arabidopsis are heteromeric structures involved in rapid sieve tube sealing.

    Science.gov (United States)

    Jekat, Stephan B; Ernst, Antonia M; von Bohl, Andreas; Zielonka, Sascia; Twyman, Richard M; Noll, Gundula A; Prüfer, Dirk

    2013-01-01

    Structural phloem proteins (P-proteins) are characteristic components of the sieve elements in all dicotyledonous and many monocotyledonous angiosperms. Tobacco P-proteins were recently confirmed to be encoded by the widespread sieve element occlusion (SEO) gene family, and tobacco SEO proteins were shown to be directly involved in sieve tube sealing thus preventing the loss of photosynthate. Analysis of the two Arabidopsis SEO proteins (AtSEOa and AtSEOb) indicated that the corresponding P-protein subunits do not act in a redundant manner. However, there are still pending questions regarding the interaction properties and specific functions of AtSEOa and AtSEOb as well as the general function of structural P-proteins in Arabidopsis. In this study, we characterized the Arabidopsis P-proteins in more detail. We used in planta bimolecular fluorescence complementation assays to confirm the predicted heteromeric interactions between AtSEOa and AtSEOb. Arabidopsis mutants depleted for one or both AtSEO proteins lacked the typical P-protein structures normally found in sieve elements, underlining the identity of AtSEO proteins as P-proteins and furthermore providing the means to determine the role of Arabidopsis P-proteins in sieve tube sealing. We therefore developed an assay based on phloem exudation. Mutants with reduced AtSEO expression levels lost twice as much photosynthate following injury as comparable wild-type plants, confirming that Arabidopsis P-proteins are indeed involved in sieve tube sealing.

  11. P-proteins in Arabidopsis are heteromeric structures involved in rapid sieve tube sealing

    Directory of Open Access Journals (Sweden)

    Stephan B Jekat

    2013-07-01

    Full Text Available Structural phloem proteins (P-proteins are characteristic components of the sieve elements in all dicotyledonous and many monocotyledonous angiosperms. Tobacco P-proteins were recently evidenced to be encoded by the widespread SEO gene family, and tobacco SEO proteins were shown to be directly involved in sieve tube sealing thus preventing the loss of photosynthate. Analysis of the two Arabidopsis SEO proteins (AtSEOa and AtSEOb indicated that the corresponding P-protein subunits do not act in a redundant manner. However, there are still pending questions regarding the interaction properties and specific functions of AtSEOa and AtSEOb as well as the general function of structural P-proteins in Arabidopsis. In this study, we characterized the Arabidopsis P-proteins in more detail. We used in planta bimolecular fluorescence complementation assays to confirm the predicted heteromeric interactions between AtSEOa and AtSEOb. Arabidopsis mutants depleted for one or both AtSEO proteins lacked the typical P-protein structures normally found in sieve elements, underlining the identity of AtSEO proteins as P-proteins and furthermore providing the means to determine the role of Arabidopsis P-proteins in sieve tube sealing. We therefore developed an assay based on phloem exudation. Mutants with reduced AtSEO expression levels lost twice as much photosynthate following injury as comparable wild-type plants, confirming that Arabidopsis P-proteins are indeed involved in sieve tube sealing. 

  12. Infective endocarditis involving an apparently structurally normal valve: new epidemiological trend?

    Science.gov (United States)

    Song, Jae-Kwan

    2015-07-01

    Infective endocarditis (IE) has been increasingly diagnosed in patients without previously detected predisposing heart disease, but its clinical features have yet to be fully determined. A recent single-center study including echocardiographic images and surgical findings investigated the incidence of undiagnosed, clinically silent valvular or congenital heart diseases and healthcare-associated infective endocarditis (HAIE). The study confirmed that a large proportion of patients with IE have no previous history of heart disease. Analysis of underlying disease in these patients showed that undetected mitral valve prolapse was the most common disease, followed by an apparently structurally normal valve. The patients who developed IE of apparently structurally normal valves had different clinical characteristics and worse outcomes. IE involving a structurally normal valve was associated with both nosocomial and non-nosocomial HAIE, whereas community-acquired IE was more frequent than HAIE. The pathophysiologic mechanism involving the development of non-HAIE or community-acquired IE due to predominantly staphylococcal infection in an apparently structurally normal valve is not yet clearly understood. Structurally normal valves are not necessarily free of regurgitation or abnormal turbulence and, given the dynamic nature and fluctuating hemodynamic effects of conditions such as poorly controlled hypertension, end-stage renal disease, and sleep apnea, further investigation is necessary to evaluate the potential role of these diseases in the development of IE. An apparently normal-looking valve is associated with IE development in patients without previously recognized predisposing heart disease, warranting repartition of at-risk groups to achieve better clinical outcomes.

  13. 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

    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...

  14. 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

  15. 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.

  16. 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

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

    International Nuclear Information System (INIS)

    Yeh, Joanne I.; Chinte, Unmesh; Du, Shoucheng

    2008-01-01

    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.

  18. 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...

  19. Genomics and structure/function studies of Rhabdoviridae proteins involved in replication and transcription.

    Science.gov (United States)

    Assenberg, R; Delmas, O; Morin, B; Graham, S C; De Lamballerie, X; Laubert, C; Coutard, B; Grimes, J M; Neyts, J; Owens, R J; Brandt, B W; Gorbalenya, A; Tucker, P; Stuart, D I; Canard, B; Bourhy, H

    2010-08-01

    Some mammalian rhabdoviruses may infect humans, and also infect invertebrates, dogs, and bats, which may act as vectors transmitting viruses among different host species. The VIZIER programme, an EU-funded FP6 program, has characterized viruses that belong to the Vesiculovirus, Ephemerovirus and Lyssavirus genera of the Rhabdoviridae family to perform ground-breaking research on the identification of potential new drug targets against these RNA viruses through comprehensive structural characterization of the replicative machinery. The contribution of VIZIER programme was of several orders. First, it contributed substantially to research aimed at understanding the origin, evolution and diversity of rhabdoviruses. This diversity was then used to obtain further structural information on the proteins involved in replication. Two strategies were used to produce recombinant proteins by expression of both full length or domain constructs in either E. coli or insect cells, using the baculovirus system. In both cases, parallel cloning and expression screening at small-scale of multiple constructs based on different viruses including the addition of fusion tags, was key to the rapid generation of expression data. As a result, some progress has been made in the VIZIER programme towards dissecting the multi-functional L protein into components suitable for structural and functional studies. However, the phosphoprotein polymerase co-factor and the structural matrix protein, which play a number of roles during viral replication and drives viral assembly, have both proved much more amenable to structural biology. Applying the multi-construct/multi-virus approach central to protein production processes in VIZIER has yielded new structural information which may ultimately be exploitable in the derivation of novel ways of intervening in viral replication. Copyright 2010 Elsevier B.V. All rights reserved.

  20. Germinoma with Involvement of Midline and Off-Midline Intracranial Structures

    Directory of Open Access Journals (Sweden)

    Monica Graciela Loto

    2014-01-01

    Full Text Available Germinomas are malignant intracranial germ tumors, usually found in suprasellar regions. Less than 10% are localized in off-middle structures, and synchronous involvement of both structures has only exceptionally been published. A case of an 18-year-old male patient with progressive right-sided hemiparesis and panhypopituitarism was reviewed. Brain MRI showed a solid mass involving pituitary and hypothalamus with thickening of pituitary stalk, high intensity lesions on T2-weighted imaging in left internal capsule, caudate nucleus, globus pallidus, and mild atrophy of the left internal capsule and cerebral peduncle. Nonadenomatous lesions were considered in the differential diagnosis. Alfa-fetoprotein (AFP levels were negative in both serum and cerebrospinal fluid (CSF, while β-human chorionic gonadotrophin (β-HCG levels were slightly increased in CSF. A transsphenoidal biopsy identified a germinoma. Four cycles of chemotherapy with bleomicine, etoposide, and cysplatin were given, followed by radiotherapy, but patients died due to a recidiva. Conclusion. Germinoma must be considered in patients with insipidus diabetes with a sellar mass with thickening of pituitary stalk; and ectopic germinoma must be suspected in patients with slowly progressive hemiparesis with cerebral hemiatrophy. Even with a rare condition, colocalization of midline and off-midline germinoma must be suspected in the presence of these typical signs of both localizations.

  1. Neural Integration of Information Specifying Human Structure from Form, Motion, and Depth

    Science.gov (United States)

    Jackson, Stuart; Blake, Randolph

    2010-01-01

    Recent computational models of biological motion perception operate on ambiguous two-dimensional representations of the body (e.g., snapshots, posture templates) and contain no explicit means for disambiguating the three-dimensional orientation of a perceived human figure. Are there neural mechanisms in the visual system that represent a moving human figure’s orientation in three dimensions? To isolate and characterize the neural mechanisms mediating perception of biological motion, we used an adaptation paradigm together with bistable point-light (PL) animations whose perceived direction of heading fluctuates over time. After exposure to a PL walker with a particular stereoscopically defined heading direction, observers experienced a consistent aftereffect: a bistable PL walker, which could be perceived in the adapted orientation or reversed in depth, was perceived predominantly reversed in depth. A phase-scrambled adaptor produced no aftereffect, yet when adapting and test walkers differed in size or appeared on opposite sides of fixation aftereffects did occur. Thus, this heading direction aftereffect cannot be explained by local, disparity-specific motion adaptation, and the properties of scale and position invariance imply higher-level origins of neural adaptation. Nor is disparity essential for producing adaptation: when suspended on top of a stereoscopically defined, rotating globe, a context-disambiguated “globetrotter” was sufficient to bias the bistable walker’s direction, as were full-body adaptors. In sum, these results imply that the neural signals supporting biomotion perception integrate information on the form, motion, and three-dimensional depth orientation of the moving human figure. Models of biomotion perception should incorporate mechanisms to disambiguate depth ambiguities in two-dimensional body representations. PMID:20089892

  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. Deconstructing IgG4-related disease involvement of midline structures: Comparison to common mimickers.

    Science.gov (United States)

    Lanzillotta, Marco; Campochiaro, Corrado; Trimarchi, Matteo; Arrigoni, Gianluigi; Gerevini, Simonetta; Milani, Raffaella; Bozzolo, Enrica; Biafora, Matteo; Venturini, Elena; Cicalese, Maria Pia; Stone, John H; Sabbadini, Maria Grazia; Della-Torre, Emanuel

    2017-07-01

    A series of destructive and tumefactive lesions of the midline structures have been recently added to the spectrum of IgG4-related disease (IgG4-RD). We examined the clinical, serological, endoscopic, radiological, and histological features that might be of utility in distinguishing IgG4-RD from other forms of inflammatory conditions with the potential to involve the sinonasal area and the oral cavity. We studied 11 consecutive patients with erosive and/or tumefactive lesions of the midline structures referred to our tertiary care center. All patients underwent serum IgG4 measurement, flow cytometry for circulating plasmablast counts, nasal endoscopy, radiological studies, and histological evaluation of tissue specimens. The histological studies included immunostaining studies to assess the number of IgG4 + plasma cells/HPF for calculation of the IgG4+/IgG + plasma cell ratio. Five patients with granulomatosis with polyangiitis (GPA), three with cocaine-induced midline destructive lesions (CIMDL), and three with IgG4-RD were studied. We found no clinical, endoscopic, or radiological findings specific for IgG4-RD. Increased serum IgG4 and plasmablasts levels were not specific for IgG4-RD. Rather, all 11 patients had elevated blood plasmablast concentrations, and several patients with GPA and CIMDL had elevated serum IgG4 levels. Storiform fibrosis and an IgG4+/IgG + plasma cell ratio >20% on histological examination, however, were observed only in patients with IgG4-RD. Histological examination of bioptic samples from the sinonasal area and oral cavity represents the mainstay for the diagnosis of IgG4-RD involvement of the midline structures.

  4. 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.

  5. Structural abnormalities and altered regional brain activity in multiple sclerosis with simple spinal cord involvement.

    Science.gov (United States)

    Yin, Ping; Liu, Yi; Xiong, Hua; Han, Yongliang; Sah, Shambhu Kumar; Zeng, Chun; Wang, Jingjie; Li, Yongmei

    2018-02-01

    To assess the changes of the structural and functional abnormalities in multiple sclerosis with simple spinal cord involvement (MS-SSCI) by using resting-state functional MRI (RS-fMRI), voxel based morphology (VBM) and diffusion tensor tractography. The amplitude of low-frequency fluctuation (ALFF) of 22 patients with MS-SSCI and 22 healthy controls (HCs) matched for age, gender and education were compared by using RS-fMRI. We also compared the volume, fractional anisotropy (FA) and apparent diffusion coefficient of the brain regions in baseline brain activity by using VBM and diffusion tensor imaging. The relationships between the expanded disability states scale (EDSS) scores, changed parameters of structure and function were further explored. (1) Compared with HCs, the ALFF of the bilateral hippocampus and right middle temporal gyrus in MS-SSCI decreased significantly. However, patients exhibited increased ALFF in the left middle frontal gyrus, left posterior cingulate gyrus and right middle occipital gyrus ( two-sample t-test, after AlphaSim correction, p 40). The volume of right middle frontal gyrus reduced significantly (p right hippocampus, the FA of left hippocampus and right middle temporal gyrus were significantly different. (2) A significant correlation between EDSS scores and ALFF was noted only in the left posterior cingulate gyrus. Our results detected structural and functional abnormalities in MS-SSCI and functional parameters were associated with clinical abnormalities. Multimodal imaging plays an important role in detecting structural and functional abnormalities in MS-SSCI. Advances in knowledge: This is the first time to apply RS-fMRI, VBM and diffusion tensor tractography to study the structural and functional abnormalities in MS-SSCI, and to explore its correlation with EDSS score.

  6. Structural insights into human Kif7, a kinesin involved in Hedgehog signalling

    Energy Technology Data Exchange (ETDEWEB)

    Klejnot, Marta, E-mail: m.klejnot@beatson.gla.ac.uk; Kozielski, Frank, E-mail: m.klejnot@beatson.gla.ac.uk [The Beatson Institute for Cancer Research, Garscube Estate, Switchback Road, Glasgow G61 1BD, Scotland (United Kingdom)

    2012-02-01

    The human Kif7 motor domain structure provides insights into a kinesin of medical significance. Kif7, a member of the kinesin 4 superfamily, is implicated in a variety of diseases including Joubert, hydrolethalus and acrocallosal syndromes. It is also involved in primary cilium formation and the Hedgehog signalling pathway and may play a role in cancer. Its activity is crucial for embryonic development. Kif7 and Kif27, a closely related kinesin in the same subfamily, are orthologues of the Drosophila melano@@gaster kinesin-like protein Costal-2 (Cos2). In vertebrates, they work together to fulfil the role of the single Cos2 gene in Drosophila. Here, the high-resolution structure of the human Kif7 motor domain is reported and is compared with that of conventional kinesin, the founding member of the kinesin superfamily. These data are a first step towards structural characterization of a kinesin-4 family member and of this interesting molecular motor of medical significance.

  7. 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.

  8. 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.

  9. Spatio-temporal neural stem cell behavior that leads to both perfect and imperfect structural brain regeneration in adult newts.

    Science.gov (United States)

    Urata, Yuko; Yamashita, Wataru; Inoue, Takeshi; Agata, Kiyokazu

    2018-06-14

    Adult newts can regenerate large parts of their brain from adult neural stem cells (NSCs), but how adult NSCs reorganize brain structures during regeneration remains unclear. In development, elaborate brain structures are produced under broadly coordinated regulations of embryonic NSCs in the neural tube, whereas brain regeneration entails exquisite control of the reestablishment of certain brain parts, suggesting a yet-unknown mechanism directs NSCs upon partial brain excision. Here we report that upon one-quarter excision of the adult newt ( Pleurodeles waltl ) mesencephalon, active participation of local NSCs around specific brain subregions' boundaries leads to some imperfect and some perfect brain regeneration along an individual's rostrocaudal axis. Regeneration phenotypes depend on how the wound closing occurs using local NSCs, and perfect regeneration replicates development-like processes but takes more than one year. Our findings indicate that newt brain regeneration is supported by modularity of boundary-domain NSCs with self-organizing ability in neighboring fields. © 2018. Published by The Company of Biologists Ltd.

  10. The neural correlates of highly iconic structures and topographic discourse in French Sign Language as observed in six hearing native signers.

    Science.gov (United States)

    Courtin, C; Hervé, P-Y; Petit, L; Zago, L; Vigneau, M; Beaucousin, V; Jobard, G; Mazoyer, B; Mellet, E; Tzourio-Mazoyer, N

    2010-09-01

    "Highly iconic" structures in Sign Language enable a narrator to act, switch characters, describe objects, or report actions in four-dimensions. This group of linguistic structures has no real spoken-language equivalent. Topographical descriptions are also achieved in a sign-language specific manner via the use of signing-space and spatial-classifier signs. We used functional magnetic resonance imaging (fMRI) to compare the neural correlates of topographic discourse and highly iconic structures in French Sign Language (LSF) in six hearing native signers, children of deaf adults (CODAs), and six LSF-naïve monolinguals. LSF materials consisted of videos of a lecture excerpt signed without spatially organized discourse or highly iconic structures (Lect LSF), a tale signed using highly iconic structures (Tale LSF), and a topographical description using a diagrammatic format and spatial-classifier signs (Topo LSF). We also presented texts in spoken French (Lect French, Tale French, Topo French) to all participants. With both languages, the Topo texts activated several different regions that are involved in mental navigation and spatial working memory. No specific correlate of LSF spatial discourse was evidenced. The same regions were more activated during Tale LSF than Lect LSF in CODAs, but not in monolinguals, in line with the presence of signing-space structure in both conditions. Motion processing areas and parts of the fusiform gyrus and precuneus were more active during Tale LSF in CODAs; no such effect was observed with French or in LSF-naïve monolinguals. These effects may be associated with perspective-taking and acting during personal transfers. 2010 Elsevier Inc. All rights reserved.

  11. 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.

  12. Neural network AE source location apart from structure size and material

    Czech Academy of Sciences Publication Activity Database

    Chlada, Milan; Převorovský, Zdeněk; Blaháček, Michal

    2010-01-01

    Roč. 28, - (2010), s. 99-107 ISSN 0730-0050. [European Conference on Acoustic Emission Testing 2010 /29./. Vídeň, 08.09.2010-10.09.2010] R&D Projects: GA ČR(CZ) GAP104/10/1430; GA MPO(CZ) FR-TI1/274 Institutional research plan: CEZ:AV0Z20760514 Keywords : AE source location * artificial neural network * arrival time profiles Subject RIV: BI - Acoustics http://www.ndt.net/search/abstract.php3?AbsID=10828

  13. Structures based on semi-degradable biomaterials for neural regeneration in the central nervous system

    OpenAIRE

    Perez Garnes, Manuel

    2015-01-01

    Se pretende obtener un material semibiodegradable basado en ácido hialurónico químicamente enlazado a cadenas de polímeros acrílicos. Los hidrogeles de ácido hialurónico presentan en general buenas características para su utilización en regeneración del sistema nervioso central: es biodegradable, es un componente importante del tejido neural, sus propiedades mecánicas son semejantes a las del tejido cerebral, promueve la formación de nuevos capilares (angiogénesis), y limita la inflamación. C...

  14. 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.

  15. Structure of a preternary complex involving a prokaryotic NHEJ DNA polymerase.

    Science.gov (United States)

    Brissett, Nigel C; Martin, Maria J; Pitcher, Robert S; Bianchi, Julie; Juarez, Raquel; Green, Andrew J; Fox, Gavin C; Blanco, Luis; Doherty, Aidan J

    2011-01-21

    In many prokaryotes, a specific DNA primase/polymerase (PolDom) is required for nonhomologous end joining (NHEJ) repair of DNA double-strand breaks (DSBs). Here, we report the crystal structure of a catalytically active conformation of Mycobacterium tuberculosis PolDom, consisting of a polymerase bound to a DNA end with a 3' overhang, two metal ions, and an incoming nucleotide but, significantly, lacking a primer strand. This structure represents a polymerase:DNA complex in a preternary intermediate state. This polymerase complex occurs in solution, stabilizing the enzyme on DNA ends and promoting nucleotide extension of short incoming termini. We also demonstrate that the invariant Arg(220), contained in a conserved loop (loop 2), plays an essential role in catalysis by regulating binding of a second metal ion in the active site. We propose that this NHEJ intermediate facilitates extension reactions involving critically short or noncomplementary DNA ends, thus promoting break repair and minimizing sequence loss during DSB repair. Copyright © 2011 Elsevier Inc. All rights reserved.

  16. Functional and structural characterization of a β-glucosidase involved in saponin metabolism from intestinal bacteria.

    Science.gov (United States)

    Yan, Shan; Wei, Peng-Cheng; Chen, Qiao; Chen, Xin; Wang, Shi-Cheng; Li, Jia-Ru; Gao, Chuan

    2018-02-19

    Saponins are natural glycosides widely used in medicine and the food industry. Although saponin metabolism in human is dependent on intestinal microbes, few involving bacteria enzymes have been identified. We cloned BlBG3, a GH3 β-glucosidase from Bifidobacterium longum, from human stool. We found that BlBG3 catalyzes the hydrolysis of glycoside furostanol and ginsenoside Rb1 at higher efficiency than other microbial β-glucosidases. Structural analysis of BlBG3 in complex with d-glucose revealed its three unique loops, which form a deep pocket and participate in substrate binding. To understand how substrate is bound to the pocket, molecular docking was performed and the binding interactions of protobioside with BlBG3 were revealed. Mutational study suggested that R484 and H642 are critical for enzymatic activity. Our study presents the first structural and functional analysis of a saponin-processing enzyme from human microbiota. Copyright © 2018 Elsevier Inc. All rights reserved.

  17. THE INFLUENCE OF SHRINKAGE AND MOISTURE DIFFUSION ON IDEALIZED TOOTH STRUCTURE INVOLVING DEBONDING DAMAGE

    Institute of Scientific and Technical Information of China (English)

    FanJianping; TangChak-Yin

    2005-01-01

    This study highlights the joint effect of early polymerization shrinkage and longtermmoisture diffusion on the behavior of the restoration-tooth structure. The interphase debonding between particle and polymer resin in dental composite is taken into account by introducing the damage variable. The idealized model is designed and constructed for representing the restorationtooth structure, which consists of enamel, dentin, composite and interphase, each considered as homogenous material. The simulation is carried out using the general-purpose finite element software package, ABAQUS incorporated with a user subroutine for definition of damaged material behavior. The influence of Young's moduli of composite and interphase on stress and displacement is discussed. The compensating effect of water sorption on the polymerization shrinkage is examined with and without involving damage evolution. A comparison is made between the influence of hyper-, equi- and hypo-water sorption. Interfacial failure in the specific regions as well as cuspal movement has been predicated. The damage evolving in dental composite reduces the rigidity of composite, thus in turn reducing consequent stress and increasing consequent displacement. The development of stresses at the restoration-tooth interface can have a detrimental effect on the longevity of a restoration.

  18. Structure of Mycobacterium tuberculosis RuvA, a protein involved in recombination

    International Nuclear Information System (INIS)

    Prabu, J. Rajan; Thamotharan, S.; Khanduja, Jasbeer Singh; Alipio, Emily Zabala; Kim, Chang-Yub; Waldo, Geoffrey S.; Terwilliger, Thomas C.; Segelke, Brent; Lekin, Tim; Toppani, Dominique; Hung, Li-Wei; Yu, Minmin; Bursey, Evan; Muniyappa, K.; Chandra, Nagasuma R.; Vijayan, M.

    2006-01-01

    RuvA, a protein from M. tuberculosis H37Rv involved in recombination, has been cloned, expressed, purified and analysed by X-ray crystallography. The process of recombinational repair is crucial for maintaining genomic integrity and generating biological diversity. In association with RuvB and RuvC, RuvA plays a central role in processing and resolving Holliday junctions, which are a critical intermediate in homologous recombination. Here, the cloning, purification and structure determination of the RuvA protein from Mycobacterium tuberculosis (MtRuvA) are reported. Analysis of the structure and comparison with other known RuvA proteins reveal an octameric state with conserved subunit–subunit interaction surfaces, indicating the requirement of octamer formation for biological activity. A detailed analysis of plasticity in the RuvA molecules has led to insights into the invariant and variable regions, thus providing a framework for understanding regional flexibility in various aspects of RuvA function

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

    Science.gov (United States)

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

    2018-04-01

    We derive two new sum rules for the unpolarized doubly virtual Compton scattering process on a nucleon, which establish novel low-Q2 relations involving the nucleon's generalized polarizabilities and moments of the nucleon's unpolarized structure functions F1(x ,Q2) and F2(x ,Q2). These relations facilitate the determination of some structure constants which can only be accessed in off-forward doubly virtual Compton scattering, not experimentally accessible at present. We perform an empirical determination for the proton and compare our results with a next-to-leading-order chiral perturbation theory prediction. We also show how these relations may be useful for a model-independent determination of the low-Q2 subtraction function in the Compton amplitude, which enters the two-photon-exchange contribution to the Lamb shift of (muonic) hydrogen. An explicit calculation of the Δ (1232 )-resonance contribution to the muonic-hydrogen 2 P -2 S Lamb shift yields -1 ±1 μ eV , confirming the previously conjectured smallness of this effect.

  20. 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.

  1. 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.

  2. An Electricity Price Forecasting Model by Hybrid Structured Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Ping-Huan Kuo

    2018-04-01

    Full Text Available Electricity price is a key influencer in the electricity market. Electricity market trades by each participant are based on electricity price. The electricity price adjusted with the change in supply and demand relationship can reflect the real value of electricity in the transaction process. However, for the power generating party, bidding strategy determines the level of profit, and the accurate prediction of electricity price could make it possible to determine a more accurate bidding price. This cannot only reduce transaction risk, but also seize opportunities in the electricity market. In order to effectively estimate electricity price, this paper proposes an electricity price forecasting system based on the combination of 2 deep neural networks, the Convolutional Neural Network (CNN and the Long Short Term Memory (LSTM. In order to compare the overall performance of each algorithm, the Mean Absolute Error (MAE and Root-Mean-Square error (RMSE evaluating measures were applied in the experiments of this paper. Experiment results show that compared with other traditional machine learning methods, the prediction performance of the estimating model proposed in this paper is proven to be the best. By combining the CNN and LSTM models, the feasibility and practicality of electricity price prediction is also confirmed in this paper.

  3. 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.

  4. 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.

  5. Neural network system and methods for analysis of organic materials and structures using spectral data

    Science.gov (United States)

    Meyer, Bernd J.; Sellers, Jeffrey P.; Thomsen, Jan U.

    1993-01-01

    Apparatus and processes for recognizing and identifying materials. Characteristic spectra are obtained for the materials via spectroscopy techniques including nuclear magnetic resonance spectroscopy, infrared absorption analysis, x-ray analysis, mass spectroscopy and gas chromatography. Desired portions of the spectra may be selected and then placed in proper form and format for presentation to a number of input layer neurons in an offline neural network. The network is first trained according to a predetermined training process; it may then be employed to identify particular materials. Such apparatus and processes are particularly useful for recognizing and identifying organic compounds such as complex carbohydrates, whose spectra conventionally require a high level of training and many hours of hard work to identify, and are frequently indistinguishable from one another by human interpretation.

  6. Crystal structure of Spy0129, a Streptococcus pyogenes class B sortase involved in pilus assembly.

    Directory of Open Access Journals (Sweden)

    Hae Joo Kang

    2011-01-01

    Full Text Available Sortase enzymes are cysteine transpeptidases that mediate the covalent attachment of substrate proteins to the cell walls of gram-positive bacteria, and thereby play a crucial role in virulence, infection and colonisation by pathogens. Many cell-surface proteins are anchored by the housekeeping sortase SrtA but other more specialised sortases exist that attach sub-sets of proteins or function in pilus assembly. The sortase Spy0129, or SrtC1, from the M1 SF370 strain of Streptococcus pyogenes is responsible for generating the covalent linkages between the pilin subunits in the pili of this organism. The crystal structure of Spy0129 has been determined at 2.3 Å resolution (R = 20.4%, Rfree  = 26.0%. The structure shows that Spy0129 is a class B sortase, in contrast to other characterised pilin polymerases, which belong to class C. Spy0129 lacks a flap believed to function in substrate recognition in class C enzymes and instead has an elaborated β6/β7 loop. The two independent Spy0129 molecules in the crystal show differences in the positions and orientations of the catalytic Cys and His residues, Cys221 and His126, correlated with movements of the β7/β8 and β4/β5 loops that respectively follow these residues. Bound zinc ions stabilise these alternative conformations in the crystal. This conformational variability is likely to be important for function although there is no evidence that zinc is involved in vivo.

  7. Crystal structure of Spy0129, a Streptococcus pyogenes class B sortase involved in pilus assembly.

    Science.gov (United States)

    Kang, Hae Joo; Coulibaly, Fasséli; Proft, Thomas; Baker, Edward N

    2011-01-11

    Sortase enzymes are cysteine transpeptidases that mediate the covalent attachment of substrate proteins to the cell walls of gram-positive bacteria, and thereby play a crucial role in virulence, infection and colonisation by pathogens. Many cell-surface proteins are anchored by the housekeeping sortase SrtA but other more specialised sortases exist that attach sub-sets of proteins or function in pilus assembly. The sortase Spy0129, or SrtC1, from the M1 SF370 strain of Streptococcus pyogenes is responsible for generating the covalent linkages between the pilin subunits in the pili of this organism. The crystal structure of Spy0129 has been determined at 2.3 Å resolution (R = 20.4%, Rfree  = 26.0%). The structure shows that Spy0129 is a class B sortase, in contrast to other characterised pilin polymerases, which belong to class C. Spy0129 lacks a flap believed to function in substrate recognition in class C enzymes and instead has an elaborated β6/β7 loop. The two independent Spy0129 molecules in the crystal show differences in the positions and orientations of the catalytic Cys and His residues, Cys221 and His126, correlated with movements of the β7/β8 and β4/β5 loops that respectively follow these residues. Bound zinc ions stabilise these alternative conformations in the crystal. This conformational variability is likely to be important for function although there is no evidence that zinc is involved in vivo.

  8. 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.

  9. On structure-exploiting trust-region regularized nonlinear least squares algorithms for neural-network learning.

    Science.gov (United States)

    Mizutani, Eiji; Demmel, James W

    2003-01-01

    This paper briefly introduces our numerical linear algebra approaches for solving structured nonlinear least squares problems arising from 'multiple-output' neural-network (NN) models. Our algorithms feature trust-region regularization, and exploit sparsity of either the 'block-angular' residual Jacobian matrix or the 'block-arrow' Gauss-Newton Hessian (or Fisher information matrix in statistical sense) depending on problem scale so as to render a large class of NN-learning algorithms 'efficient' in both memory and operation costs. Using a relatively large real-world nonlinear regression application, we shall explain algorithmic strengths and weaknesses, analyzing simulation results obtained by both direct and iterative trust-region algorithms with two distinct NN models: 'multilayer perceptrons' (MLP) and 'complementary mixtures of MLP-experts' (or neuro-fuzzy modular networks).

  10. Investigation of the various structure parameters for predicting impact sensitivity of energetic molecules via artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Keshavarz, Mohammad Hossein; Jaafari, Mohammad [Department of Chemistry, Malek-Ashtar University of Technology, Shahin-Shahr, P.O. Box 83145/115 (Iran)

    2006-06-15

    A generalized scheme is introduced for predicting impact sensitivity of any explosives by using artificial neural networks. Experimental values for the impact sensitivity for 291 compounds containing C, H, N and O have been used for training and testing sets. The input descriptors include aromatic character, heteroaromatic character, the number of N-NO{sub 2} bonds and the number of {alpha}-hydrogen atoms as well as the number of carbon, hydrogen, nitrogen, and oxygen divided by molecular weight. The reliability of the proposed model was assessed by comparing the results against measured values as well as five models of complicated quantum mechanical computed values of 14 CHNO explosives from a variety of chemical structures. The model gives root mean squares errors of 41 cm and 56 cm for training and test sets, respectively, of the H{sub 50} quantity. (Abstract Copyright [2006], Wiley Periodicals, Inc.)

  11. Correlations between vascular invasion, neural structures invasion and microvessel density with clinicopathological parameters in gastric cancer

    Directory of Open Access Journals (Sweden)

    Bădescu Alina

    2014-06-01

    Full Text Available Scopul: Scopul studiului efectuat a fost acela de a estima prezenţa invaziei tumorale la nivelul vaselor limfatice, sanguine şi la nivel neural în carcinoamele gastrice pe preparatele colorate hematoxilină-eozină (H-E şi, de asemenea, densitatea microvascularizatiei tumorale (MVD, detectată imunohistochimic, precum şi relaţia acestora cu parametrii clinico-patologici şi biologici ai tumorilor. Material şi metodă. Pentru evaluarea invaziei limfo-vasculare şi neurale am inclus în studiu 367 de pacienţi diagnosticaţi cu carcinoame gastrice. Pentru studiul imunohistochimic al MVD, au fost selectaţi 28 de pacienţi, din care 16 pacienţi cu gastrectomomie totală, în urma căreia s-a stabilit stadiul TNM al tumorii primare şi 12 pacienţi cu biopsie gastrică. Biopsiile gastrice şi probele chirurgicale au fost procesate folosind tehnica de includere la parafină şi coloraţia hematoxilină-eozină, iar pentru evaluarea imunohistochimică a MVD s-au utilizat anticorpii anti-CD31 şi anti-CD34. Rezultate: Prezenţa invaziei tumorale la nivelul vaselor sanguine a fost semnificativ asociată cu stadiile avansate de boală (p<0,01 şi cu carcinoamele gastrice slab diferenţiate (p<0,01, în timp ce invazia vaselor limfatice s-a asociat semnificativ doar cu stadiul avansat al tumorilor (p<0,001. În ceea ce priveşte invazia tumorală peri- sau intraneurală, s-a observat o corelaţie semnificativă a acesteia cu sexul feminin (p<0,05, cu stadiile avansate de boală (p<0,001, cu tipul difuz al carcinoamelor gastrice (p<0,05 şi cu tumorile slab diferenţiate (p<0,05. S-a observat o legătură strânsă între valoarea MVD determinată cu anticorpul anti CD34 şi doi dintre parametrii histopatologici importanţi: tipul histologic al carcinoamelor gastrice conform clasificării Lauren (tipul difuz; p<0,05 şi gradul de diferenţiere al tumorilor (tumorile slab diferenţiate; p<0,05. S-a observat de asemenea o corelaţie semnificativă a

  12. Transcrition factor c-Myb is involved in the regulation of the epithelial-mesenchymal transition in the avian neural crest

    Czech Academy of Sciences Publication Activity Database

    Karafiát, Vít; Dvořáková, Marta; Krejčí, E.; Králová, Jarmila; Pajer, Petr; Šnajdr, P.; Mandíková, Sonja; Bartůněk, Petr; Grim, M.; Dvořák, Michal

    2005-01-01

    Roč. 62, č. 21 (2005), s. 2516-2525 ISSN 1420-682X R&D Projects: GA ČR GA304/03/0463; GA AV ČR IAA5052309 Institutional research plan: CEZ:AV0Z50520514 Keywords : c-myb gene * epithelial-mesenchymal transition * neural crest Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.582, year: 2005

  13. 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

    2017-05-28

    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 (Au 147 ), 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 Au 147 , 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 Au 147 is performed, and it is concluded that Au 147 has a dynamic surface, thus opening a new window for studying its reaction dynamics.

  14. 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.

  15. 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.

  16. Equilibrium point control of a monkey arm simulator by a fast learning tree structured artificial neural network.

    Science.gov (United States)

    Dornay, M; Sanger, T D

    1993-01-01

    A planar 17 muscle model of the monkey's arm based on realistic biomechanical measurements was simulated on a Symbolics Lisp Machine. The simulator implements the equilibrium point hypothesis for the control of arm movements. Given initial and final desired positions, it generates a minimum-jerk desired trajectory of the hand and uses the backdriving algorithm to determine an appropriate sequence of motor commands to the muscles (Flash 1987; Mussa-Ivaldi et al. 1991; Dornay 1991b). These motor commands specify a temporal sequence of stable (attractive) equilibrium positions which lead to the desired hand movement. A strong disadvantage of the simulator is that it has no memory of previous computations. Determining the desired trajectory using the minimum-jerk model is instantaneous, but the laborious backdriving algorithm is slow, and can take up to one hour for some trajectories. The complexity of the required computations makes it a poor model for biological motor control. We propose a computationally simpler and more biologically plausible method for control which achieves the benefits of the backdriving algorithm. A fast learning, tree-structured network (Sanger 1991c) was trained to remember the knowledge obtained by the backdriving algorithm. The neural network learned the nonlinear mapping from a 2-dimensional cartesian planar hand position (x,y) to a 17-dimensional motor command space (u1, . . ., u17). Learning 20 training trajectories, each composed of 26 sample points [[x,y], [u1, . . ., u17] took only 20 min on a Sun-4 Sparc workstation. After the learning stage, new, untrained test trajectories as well as the original trajectories of the hand were given to the neural network as input. The network calculated the required motor commands for these movements. The resulting movements were close to the desired ones for both the training and test cases.

  17. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is...

  18. 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.

  19. 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.

  20. 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

  1. 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...

  2. 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…

  3. CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.

    Science.gov (United States)

    Zhou, Jiyun; Wang, Hongpeng; Zhao, Zhishan; Xu, Ruifeng; Lu, Qin

    2018-05-08

    Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

  4. Accuracy issues involved in modeling in vivo protein structures using PM7.

    Science.gov (United States)

    Martin, Benjamin P; Brandon, Christopher J; Stewart, James J P; Braun-Sand, Sonja B

    2015-08-01

    Using the semiempirical method PM7, an attempt has been made to quantify the error in prediction of the in vivo structure of proteins relative to X-ray structures. Three important contributory factors are the experimental limitations of X-ray structures, the difference between the crystal and solution environments, and the errors due to PM7. The geometries of 19 proteins from the Protein Data Bank that had small R values, that is, high accuracy structures, were optimized and the resulting drop in heat of formation was calculated. Analysis of the changes showed that about 10% of this decrease in heat of formation was caused by faults in PM7, the balance being attributable to the X-ray structure and the difference between the crystal and solution environments. A previously unknown fault in PM7 was revealed during tests to validate the geometries generated using PM7. Clashscores generated by the Molprobity molecular mechanics structure validation program showed that PM7 was predicting unrealistically close contacts between nonbonding atoms in regions where the local geometry is dominated by very weak noncovalent interactions. The origin of this fault was traced to an underestimation of the core-core repulsion between atoms at distances smaller than the equilibrium distance. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published By Wiley Periodicals, Inc.

  5. 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,…

  6. 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.

  7. Concerning the structure of occupational accidents involving construction workers in the erection of nuclear power plants

    International Nuclear Information System (INIS)

    Nowak, B.; Roebenack, K.D.

    1991-01-01

    An investigation of 561 occupational accidents involving construction workers which took place during the construction of nuclear power plants failed to show any significant deviation in comparison with general construction as regards process classification, classification of accidents according to occupation and situation, and accidents severity. Occupational accidents which are typial for nuclear power plant construction are a rare exception. (orig.) [de

  8. Cortical regions involved in the generation of musical structures during improvisation in pianists.

    Science.gov (United States)

    Bengtsson, Sara L; Csíkszentmihályi, Mihály; Ullén, Fredrik

    2007-05-01

    Studies on simple pseudorandom motor and cognitive tasks have shown that the dorsolateral prefrontal cortex and rostral premotor areas are involved in free response selection. We used functional magnetic resonance imaging to investigate whether these brain regions are also involved in free generation of responses in a more complex creative behavior: musical improvisation. Eleven professional pianists participated in the study. In one condition, Improvise, the pianist improvised on the basis of a visually displayed melody. In the control condition, Reproduce, the participant reproduced his previous improvisation from memory. Participants were able to reproduce their improvisations with a high level of accuracy, and the contrast Improvise versus Reproduce was thus essentially matched in terms of motor output and sensory feedback. However, the Improvise condition required storage in memory of the improvisation. We therefore also included a condition FreeImp, where the pianist improvised but was instructed not to memorize his performance. To locate brain regions involved in musical creation, we investigated the activations in the Improvise-Reproduce contrast that were also present in FreeImp contrasted with a baseline rest condition. Activated brain regions included the right dorsolateral prefrontal cortex, the presupplementary motor area, the rostral portion of the dorsal premotor cortex, and the left posterior part of the superior temporal gyrus. We suggest that these regions are part of a network involved in musical creation, and discuss their possible functional roles.

  9. Impaired neural structure and function contributing to autonomic symptoms in congenital central hypoventilation syndrome.

    Science.gov (United States)

    Harper, Ronald M; Kumar, Rajesh; Macey, Paul M; Harper, Rebecca K; Ogren, Jennifer A

    2015-01-01

    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, or hypoxic exposure.

  10. 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

  11. Effect of repeated contact on adhesion measurements involving polydimethylsiloxane structural material

    International Nuclear Information System (INIS)

    Kroner, E; Arzt, E; Maboudian, R

    2009-01-01

    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.

  12. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  13. Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

    International Nuclear Information System (INIS)

    Kapur, G.S.; Sastry, M.I.S.; Jaiswal, A.K.; Sarpal, A.S.

    2004-01-01

    The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using 1 H and 13 C nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their 1 H NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the 'measured' and 'estimated' RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only 1 H NMR data) also showed high correlation between the 'measured' and 'estimated' RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets

  14. 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.

  15. Effects of Neuromodulation on Excitatory-Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

    Science.gov (United States)

    Rich, Scott; Zochowski, Michal; Booth, Victoria

    2018-01-01

    Acetylcholine (ACh), one of the brain's most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E-I networks), which are ubiquitous in the brain. Utilizing biophysical models of E-I networks, we analyze how the network connectivity structure in terms of synaptic connectivity alters the influence of ACh on the generation of synchronous excitatory bursting. We investigate networks containing all combinations of excitatory and inhibitory cells with high (Type I properties) or low (Type II properties) modulatory tone. To vary network connectivity structure, we focus on the effects of the strengths of inter-connections between excitatory and inhibitory cells (E-I synapses and I-E synapses), and the strengths of intra-connections among excitatory cells (E-E synapses) and among inhibitory cells (I-I synapses). We show that the presence of ACh may or may not affect the generation of network synchrony depending on the network connectivity. Specifically, strong network inter-connectivity induces synchronous excitatory bursting regardless of the cellular propensity for synchronization, which aligns with predictions of the PING model. However, when a network's intra-connectivity dominates its inter-connectivity, the propensity for synchrony of either inhibitory or excitatory cells can determine the generation of network-wide bursting.

  16. Flutter Analysis of RX-420 Balistic Rocket Fin Involving Rigid Body Modes of Rocket Structures

    Directory of Open Access Journals (Sweden)

    Novi Andria

    2013-03-01

    Full Text Available Flutter is a phenomenon that has brought a catastrophic failure to the flight vehicle structure. In this experiment, flutter was analyzed for its symmetric and antisymmetric configuration to understand the effect of rocket rigid modes to the fin flutter characteristic. This research was also expected to find out the safety level of RX-420 structure design. The analysis was performed using half rocket model. Fin structure used in this research was a fin which has semispan 600 mm, thickness 12 mm, chord root 700 mm, chord tip 400 mm, made by Al 6061-T651, double spar configuration with skin thickness of 2 mm. Structural dynamics and flutter stability were analyzed using finite element software implemented on MSC. Nastran. The analysis shows that the antisymmetric flutter mode is more critical than symmetric flutter mode. At sea level altitude, antisymmetric flutter occurs at 6.4 Mach, and symmetric flutter occurs at 10.15 Mach. Compared to maximum speed of RX-420 which is 4.5 Mach at altitude 11 km or equivalent to 2.1 Mach at sea level, it can be concluded that the RX-420 structure design is safe, and flutter will not occur during flight.

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

    International Nuclear Information System (INIS)

    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.; Bedem, Henry van den; Weekes, Dana; Xu, Qingping; Hodgson, Keith O.; Wooley, John; Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wilson, Ian A.

    2010-01-01

    The crystal structures of SPO0140 and Sbal-2486 revealed a two-domain structure that adopts a novel fold. Analysis of the interdomain cleft suggests a nucleotide-based ligand with a genome context indicating signaling as a possible role for this family. 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

  18. Neurological soft signs in psychoses. II: an explorative study of structural involvement amongst drug naive first episode patients

    Directory of Open Access Journals (Sweden)

    Pranjal Sharma

    2016-01-01

    Full Text Available Background: The aims and objective of the study was to find out the different structural involvement in the three study groups, namely brief psychotic disorder, schizophreniform psychosis, and schizophrenia as reflected by the neurological soft signs (NSS. Material and methods: The study was conducted in the Department of Psychiatry, Silchar Medical College and Hospital, Silchar, Cachar, Assam. In this study, we had further classified the soft signs into groups related to their corresponding brain structures as per the aims and objectives. Results: Our study consisted of 30 patients distributed into three case groups, namely brief psychotic disorder having 14 cases, schizophrenia having 12 cases, and only four cases in the schizophreniform group. We have made a novel attempt to establish a functional relationship between the structural involvement and the three groups of disorders under study through the evaluation of NSS at the onset of symptoms, which at times may not be possible to diagnose through currently available radio-imaging techniques. We have definitely found a predominant involvement of the cerebellum in the brief psychotic disorder and schizophrenia groups, and the involvement of parietal lobe in the schizophreniform psychosis group; although the results were not statistically significant. Conclusion: We hope that in future larger studies with more number of patients will shed definite lights in the present study findings.

  19. Common neural structures activated by epidural and transcutaneous lumbar spinal cord stimulation: Elicitation of posterior root-muscle reflexes.

    Directory of Open Access Journals (Sweden)

    Ursula S Hofstoetter

    Full Text Available 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

  20. Impact of resilience and job involvement on turnover intention of new graduate nurses using structural equation modeling.

    Science.gov (United States)

    Yu, Mi; Lee, Haeyoung

    2018-03-06

    Nurses' turnover intention is not just a result of their maladjustment to the field; it is an organizational issue. This study aimed to construct a structural model to verify the effects of new graduate nurses' work environment satisfaction, emotional labor, and burnout on their turnover intention, with consideration of resilience and job involvement, and to test the adequacy of the developed model. A cross-sectional study and a structural equation modelling approach were used. A nationwide survey was conducted of 371 new nurses who were working in hospitals for ≤18 months between July and October, 2014. The final model accounted for 40% of the variance in turnover intention. Emotional labor and burnout had a significant positive direct effect and an indirect effect on nurses' turnover intention. Resilience had a positive direct effect on job involvement. Job involvement had a negative direct effect on turnover intention. Resilience and job involvement mediated the effect of work environment satisfaction, emotional labor, and burnout on turnover intention. It is important to strengthen new graduate nurses' resilience in order to increase their job involvement and to reduce their turnover intention. © 2018 Japan Academy of Nursing Science.

  1. Error and attack tolerance of synchronization in Hindmarsh–Rose neural networks with community structure

    International Nuclear Information System (INIS)

    Li, Chun-Hsien; Yang, Suh-Yuh

    2014-01-01

    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.

  2. Structures excited by heavy ions in 208Pb target. Interpretation involving giant resonances and multiphonon excitations

    International Nuclear Information System (INIS)

    Chomaz, P.

    1984-01-01

    Kinetic energy spectra of heavy fragments from the 36Ar+208Pb reaction at 11 MeV/n and 20 Ne+ 208 Pb at 30 MeV/n have been measured with a time of flight spectrometer. Numerous structures ranging up to 100 MeV excitation energy are observed in the inelastic and few nucleon transfer channels. These structures are shown to be due to an excitation of the 208 Pb target nucleus and not to decay products of excited ejectiles. Positions of low lying structures (E* 208 Pb. The linear response of the target nucleus to the external field created by the projectile is calculated microscopically in the Random Phase Approximation resolved using the Green's function method in coordinate space with a Skyrme interaction. In the independant quasi-boson approximation multiple phonon excitations reproduce the main features of the experimental data and appear as a plausible interpretation of the observed structures. The theoretical calculations and experimental observations suggest that multiphonon excitations play an important role in heavy ion reactions and contribute strongly to the kinetic energy dissipation [fr

  3. 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.

  4. Prediction of phenotypic susceptibility to antiretroviral drugs using physiochemical properties of the primary enzymatic structure combined with artificial neural networks

    DEFF Research Database (Denmark)

    Kjaer, J; Høj, L; Fox, Z

    2008-01-01

    OBJECTIVES: Genotypic interpretation systems extrapolate observed associations in datasets to predict viral susceptibility to antiretroviral drugs (ARVs) for given isolates. We aimed to develop and validate an approach using artificial neural networks (ANNs) that employ descriptors...

  5. Structural networks involved in attention and executive functions in multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Sara Llufriu

    2017-01-01

    Full Text Available Attention and executive deficits are disabling symptoms in multiple sclerosis (MS that have been related to disconnection mechanisms. We aimed to investigate changes in structural connectivity in MS and their association with attention and executive performance applying an improved framework that combines high order probabilistic tractography and anatomical exclusion criteria postprocessing. We compared graph theory metrics of structural networks and fractional anisotropy (FA of white matter (WM connections or edges between 72 MS subjects and 38 healthy volunteers (HV and assessed their correlation with cognition. Patients displayed decreased network transitivity, global efficiency and increased path length compared with HV (p < 0.05, corrected. Also, nodal strength was decreased in 26 of 84 gray matter regions. The distribution of nodes with stronger connections or hubs of the network was similar among groups except for the right pallidum and left insula, which became hubs in patients. MS subjects presented reduced edge FA widespread in the network, while FA was increased in 24 connections (p < 0.05, corrected. Decreased integrity of frontoparietal networks, deep gray nuclei and insula correlated with worse attention and executive performance (r between 0.38 and 0.55, p < 0.05, corrected. Contrarily, higher strength in the right transverse temporal cortex and increased FA of several connections (mainly from cingulate, frontal and occipital cortices were associated with worse functioning (r between −0.40 and −0.47, p < 0.05 corrected. In conclusion, structural brain connectivity is disturbed in MS due to widespread impairment of WM connections and gray matter structures. The increased edge connectivity suggests the presence of reorganization mechanisms at the structural level. Importantly, attention and executive performance relates to frontoparietal networks, deep gray nuclei and insula. These results support the relevance of

  6. Structure, function, and regulation of enzymes involved in amino acid metabolism of bacteria and archaea.

    Science.gov (United States)

    Tomita, Takeo

    2017-11-01

    Amino acids are essential components in all organisms because they are building blocks of proteins. They are also produced industrially and used for various purposes. For example, L-glutamate is used as the component of "umami" taste and lysine has been used as livestock feed. Recently, many kinds of amino acids have attracted attention as biological regulators and are used for a healthy life. Thus, to clarify the mechanism of how amino acids are biosynthesized and how they work as biological regulators will lead to further effective utilization of them. Here, I review the leucine-induced-allosteric activation of glutamate dehydrogenase (GDH) from Thermus thermophilus and the relationship with the allosteric regulation of GDH from mammals. Next, I describe structural insights into the efficient production of L-glutamate by GDH from an excellent L-glutamate producer, Corynebacterium glutamicum. Finally, I review the structural biology of lysine biosynthesis of thermophilic bacterium and archaea.

  7. 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.

  8. The current structure of key actors involved in research on land and soil degradation

    Science.gov (United States)

    Escadafal, Richard; Barbero, Celia; Exbrayat, Williams; Marques, Maria Jose; Ruiz, Manuel; El Haddadi, Anass; Akhtar-Schuster, Mariam

    2013-04-01

    Land and soil conservation topics, the final mandate of the United Convention to Combat desertification in drylands, have been diagnosed as still suffering from a lack of guidance. On the contrary, climate change and biodiversity issues -the other two big subjects of the Rio Conventions- seem to progress and may benefit from the advice of international panels. Arguably the weakness of policy measures and hence the application of scientific knowledge by land users and stakeholders could be the expression of an inadequate research organization and a lack of ability to channel their findings. In order to better understand the size, breadth and depth of the scientific communities involved in providing advice to this convention and to other bodies, this study explores the corpus of international publications dealing with land and/or with soils. A database of several thousands records including a significant part of the literature published so far was performed using the Web of Science and other socio-economic databases such as FRANCIS and CAIRN. We extracted hidden information using bibliometric methods and data mining applied to these scientific publications to map the key actors (laboratories, teams, institutions) involved in research on land and on soils. Several filters were applied to the databases in combination with the word "desertification". The further use of Tetralogie software merges databases, analyses similarities and differences between keywords, disciplines, authors and regions and identifies obvious clusters. Assessing their commonalities and differences, the visualisation of links and gaps between scientists, organisations, policymakers and other stakeholders is possible. The interpretation of the 'clouds' of disciplines, keywords, and techniques will enhance the understanding of interconnections between them; ultimately this will allow diagnosing some of their strengths and weaknesses. This may help explain why land and soil degradation remains a

  9. Sieve element occlusion (SEO) genes encode structural phloem proteins involved in wound sealing of the phloem.

    Science.gov (United States)

    Ernst, Antonia M; Jekat, Stephan B; Zielonka, Sascia; Müller, Boje; Neumann, Ulla; Rüping, Boris; Twyman, Richard M; Krzyzanek, Vladislav; Prüfer, Dirk; Noll, Gundula A

    2012-07-10

    The sieve element occlusion (SEO) gene family originally was delimited to genes encoding structural components of forisomes, which are specialized crystalloid phloem proteins found solely in the Fabaceae. More recently, SEO genes discovered in various non-Fabaceae plants were proposed to encode the common phloem proteins (P-proteins) that plug sieve plates after wounding. We carried out a comprehensive characterization of two tobacco (Nicotiana tabacum) SEO genes (NtSEO). Reporter genes controlled by the NtSEO promoters were expressed specifically in immature sieve elements, and GFP-SEO fusion proteins formed parietal agglomerates in intact sieve elements as well as sieve plate plugs after wounding. NtSEO proteins with and without fluorescent protein tags formed agglomerates similar in structure to native P-protein bodies when transiently coexpressed in Nicotiana benthamiana, and the analysis of these protein complexes by electron microscopy revealed ultrastructural features resembling those of native P-proteins. NtSEO-RNA interference lines were essentially devoid of P-protein structures and lost photoassimilates more rapidly after injury than control plants, thus confirming the role of P-proteins in sieve tube sealing. We therefore provide direct evidence that SEO genes in tobacco encode P-protein subunits that affect translocation. We also found that peptides recently identified in fascicular phloem P-protein plugs from squash (Cucurbita maxima) represent cucurbit members of the SEO family. Our results therefore suggest a common evolutionary origin for P-proteins found in the sieve elements of all dicotyledonous plants and demonstrate the exceptional status of extrafascicular P-proteins in cucurbits.

  10. 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.

  11. The deeper structure of the southern Dead Sea basin derived from neural network analysis of velocity and attenuation tomography

    Science.gov (United States)

    Braeuer, Benjamin; Haberland, Christian; Bauer, Klaus; Weber, Michael

    2014-05-01

    The Dead Sea basin is a pull-apart basin at the Dead Sea transform fault, the boundary between the African and the Arabian plates. Though the DSB has been studied for a long time, the available knowledge - based mainly on surface geology, drilling and seismic reflection surveys - gives only a partial picture of its shallow structure. Therefore, within the framework of the international DESIRE (DEad Sea Integrated REsearch) project, a dense temporary local seismological network was operated in the southern Dead Sea area. Within 18 month of recording 650 events were detected. In addition to an already published tomography study revealing the distribution of P velocities and the Vp/Vs ratios a 2D P-wave attenuation tomography (parameter Qp) was performed. The neural network technique of Self-organizing maps (SOM) is used for the joint interpretation of these three parameters (Vp, Vp/Vs, Qp). The resulting clusters in the petrophysical parameter space are assigned to the main lithological units below the southern part of the Dead Sea basin: (1) The basin sediments characterized by strong attenuation, high vp/vs ratios and low P velocities. (2) The pre-basin sediments characterized by medium to strong attenuation, low Vp/Vs ratios and medium P velocities. (3) The basement characterized by low to moderate attenuation, medium vp/vs ratios and high P velocities. Thus, the asymmetric southern Dead Sea basin is filled with basin sediments down to depth of 7 to 12 km. Below the basin sediments, the pre-basin sediments are extending to a depth between 13 and 18 km.

  12. SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

    Science.gov (United States)

    Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

    2017-01-01

    This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

  13. Task instructions influence the cognitive strategies involved in line bisection judgements: evidence from modulated neural mechanisms revealed by fMRI

    NARCIS (Netherlands)

    Fink, G.R.; Marshall, J.C.; Weiss, P.H.; Toni, I.; Zilles, K.

    2002-01-01

    Manual line bisection and a perceptual variant thereof (the Landmark test) are widely used to assess visuospatial neglect in neurological patients, but little is known about the cognitive strategies involved. In the Landmark test, one could explicitly compare the lengths of the left and right line

  14. Engineering High-Energy Interfacial Structures for High-Performance Oxygen-Involving Electrocatalysis.

    Science.gov (United States)

    Guo, Chunxian; Zheng, Yao; Ran, Jingrun; Xie, Fangxi; Jaroniec, Mietek; Qiao, Shi-Zhang

    2017-07-10

    Engineering high-energy interfacial structures for high-performance electrocatalysis is achieved by chemical coupling of active CoO nanoclusters and high-index facet Mn 3 O 4 nano-octahedrons (hi-Mn 3 O 4 ). A thorough characterization, including synchrotron-based near edge X-ray absorption fine structure, reveals that strong interactions between both components promote the formation of high-energy interfacial Mn-O-Co species and high oxidation state CoO, from which electrons are drawn by Mn III -O present in hi-Mn 3 O 4 . The CoO/hi-Mn 3 O 4 demonstrates an excellent catalytic performance over the conventional metal oxide-based electrocatalysts, which is reflected by 1.2 times higher oxygen evolution reaction (OER) activity than that of Ru/C and a comparable oxygen reduction reaction (ORR) activity to that of Pt/C as well as a better stability than that of Ru/C (95 % vs. 81 % retained OER activity) and Pt/C (92 % vs. 78 % retained ORR activity after 10 h running) in alkaline electrolyte. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. 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.

  16. Structure, function and networks of transcription factors involved in abiotic stress responses

    DEFF Research Database (Denmark)

    Lindemose, Søren; O'Shea, Charlotte; Jensen, Michael Krogh

    2013-01-01

    Transcription factors (TFs) are master regulators of abiotic stress responses in plants. This review focuses on TFs from seven major TF families, known to play functional roles in response to abiotic stresses, including drought, high salinity, high osmolarity, temperature extremes...... and the phytohormone ABA. Although ectopic expression of several TFs has improved abiotic stress tolerance in plants, fine-tuning of TF expression and protein levels remains a challenge to avoid crop yield loss. To further our understanding of TFs in abiotic stress responses, emerging gene regulatory networks based...... on TFs and their direct targets genes are presented. These revealed components shared between ABA-dependent and independent signaling as well as abiotic and biotic stress signaling. Protein structure analysis suggested that TFs hubs of large interactomes have extended regions with protein intrinsic...

  17. 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.

  18. ANT Advanced Neural Tool

    International Nuclear Information System (INIS)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-01-01

    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

  19. Neural codes of seeing architectural styles.

    Science.gov (United States)

    Choo, Heeyoung; Nasar, Jack L; Nikrahei, Bardia; Walther, Dirk B

    2017-01-10

    Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people's visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture.

  20. 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

  1. Pea Border Cell Maturation and Release Involve Complex Cell Wall Structural Dynamics.

    Science.gov (United States)

    Mravec, Jozef; Guo, Xiaoyuan; Hansen, Aleksander Riise; Schückel, Julia; Kračun, Stjepan Krešimir; Mikkelsen, Maria Dalgaard; Mouille, Grégory; Johansen, Ida Elisabeth; Ulvskov, Peter; Domozych, David S; Willats, William George Tycho

    2017-06-01

    The adhesion of plant cells is vital for support and protection of the plant body and is maintained by a variety of molecular associations between cell wall components. In some specialized cases, though, plant cells are programmed to detach, and root cap-derived border cells are examples of this. Border cells (in some species known as border-like cells) provide an expendable barrier between roots and the environment. Their maturation and release is an important but poorly characterized cell separation event. To gain a deeper insight into the complex cellular dynamics underlying this process, we undertook a systematic, detailed analysis of pea ( Pisum sativum ) root tip cell walls. Our study included immunocarbohydrate microarray profiling, monosaccharide composition determination, Fourier-transformed infrared microspectroscopy, quantitative reverse transcription-PCR of cell wall biosynthetic genes, analysis of hydrolytic activities, transmission electron microscopy, 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 findings provide a new level of detail about border cell maturation and enable us to develop a model of the separation process. We propose that loss of adhesion by the dissolution of homogalacturonan in the middle lamellae is augmented by an active biophysical process of cell curvature driven by the polarized distribution of xyloglucan and extensin epitopes. © 2017 American Society of Plant Biologists. All Rights Reserved.

  2. Pea Border Cell Maturation and Release Involve Complex Cell Wall Structural Dynamics1[OPEN

    Science.gov (United States)

    2017-01-01

    The adhesion of plant cells is vital for support and protection of the plant body and is maintained by a variety of molecular associations between cell wall components. In some specialized cases, though, plant cells are programmed to detach, and root cap-derived border cells are examples of this. Border cells (in some species known as border-like cells) provide an expendable barrier between roots and the environment. Their maturation and release is an important but poorly characterized cell separation event. To gain a deeper insight into the complex cellular dynamics underlying this process, we undertook a systematic, detailed analysis of pea (Pisum sativum) root tip cell walls. Our study included immunocarbohydrate microarray profiling, monosaccharide composition determination, Fourier-transformed infrared microspectroscopy, quantitative reverse transcription-PCR of cell wall biosynthetic genes, analysis of hydrolytic activities, transmission electron microscopy, 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 findings provide a new level of detail about border cell maturation and enable us to develop a model of the separation process. We propose that loss of adhesion by the dissolution of homogalacturonan in the middle lamellae is augmented by an active biophysical process of cell curvature driven by the polarized distribution of xyloglucan and extensin epitopes. PMID:28400496

  3. 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

  4. Adenovirus structural protein IIIa is involved in the serotype specificity of viral DNA packaging.

    Science.gov (United States)

    Ma, Hsin-Chieh; Hearing, Patrick

    2011-08-01

    The packaging of the adenovirus (Ad) genome into a capsid displays serotype specificity. This specificity has been attributed to viral packaging proteins, the IVa2 protein and the L1-52/55K protein. We previously found that the Ad17 L1-52/55K protein was not able to complement the growth of an Ad5 L1-52/55K mutant virus, whereas two other Ad17 packaging proteins, IVa2 and L4-22K, could complement the growth of Ad5 viruses with mutations in the respective genes. In this report, we investigated why the Ad17 L1-52/55K protein was not able to complement the Ad5 L1-52/55K mutant virus. We demonstrate that the Ad17 L1-52/55K protein binds to the Ad5 IVa2 protein in vitro and the Ad5 packaging domain in vivo, activities previously associated with packaging function. The Ad17 L1-52/55K protein also associates with empty Ad5 capsids. Interestingly, we find that the Ad17 L1-52/55K protein is able to complement the growth of an Ad5 L1-52/55K mutant virus in conjunction with the Ad17 structural protein IIIa. The same result was found with the L1-52/55K and IIIa proteins of several other Ad serotypes, including Ad3 and Ad4. The Ad17 IIIa protein associates with empty Ad5 capsids. Consistent with the complementation results, we find that the IIIa protein interacts with the L1-52/55K protein in vitro and associates with the viral packaging domain in vivo. These results underscore the complex nature of virus assembly and genome encapsidation and provide a new model for how the viral genome may tether to the empty capsid during the encapsidation process.

  5. [Functional neuro-navigation and intraoperative magnetic resonance imaging for the resection of gliomas involving eloquent language structures].

    Science.gov (United States)

    Chen, Xiao-lei; Xu, Bai-nan; Wang, Fei; Meng, Xiang-hui; Zhang, Jun; Jiang, Jin-li; Yu, Xin-guang; Zhou, Ding-biao

    2011-08-01

    To explore the clinical value of functional neuro-navigation and high-field-strength intraoperative magnetic resonance imaging (iMRI) for the resection of intracerebral gliomas involving eloquent language structures. From April 2009 to April 2010, 48 patients with intracerebral gliomas involving eloquent language structures, were operated with functional neuro-navigation and iMRI. Blood oxygen level dependent functional MRI (BOLD-fMRI) was used to depict both Broca and Wernicke cortex, while diffusion tensor imaging (DTI) based fiber tracking was used to delineate arcuate fasciculus. The reconstructed language structures were integrated into a navigation system, so that intra-operative microscopic-based functional neuro-navigation could be achieved. iMRI was used to update the images for both language structures and residual tumors. All patients were evaluated for language function pre-operatively and post-operatively upon short-term and long-term follow-up. In all patients, functional neuro-navigation and iMRI were successfully achieved. In 38 cases (79.2%), gross total resection was accomplished, while in the rest 10 cases (20.8%), subtotal resection was achieved. Only 1 case (2.1%) developed long-term (more than 3 months) new language function deficits at post-operative follow-up. No peri-operative mortality was recorded. With functional neuro-navigation and iMRI, the eloquent structures for language can be precisely located, while the resection size can be accurately evaluated intra-operatively. This technique is safe and helpful for preservation of language function.

  6. 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

    2013-12-01

    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.

  7. Neural plasticity and its initiating conditions in tinnitus.

    Science.gov (United States)

    Roberts, L E

    2018-03-01

    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.

  8. 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…

  9. The progestin etonogestrel enhances the respiratory response to metabolic acidosis in newborn rats. Evidence for a mechanism involving supramedullary structures.

    Science.gov (United States)

    Loiseau, Camille; Osinski, Diane; Joubert, Fanny; Straus, Christian; Similowski, Thomas; Bodineau, Laurence

    2014-05-01

    Central congenital hypoventilation syndrome is a neuro-respiratory disease characterized by the dysfunction of the CO2/H(+) chemosensitive neurons of the retrotrapezoid nucleus/parafacial respiratory group. A recovery of CO2/H(+) chemosensitivity has been observed in some central congenital hypoventilation syndrome patients coincidental with contraceptive treatment by a potent progestin, desogestrel (Straus et al., 2010). The mechanisms of this progestin effect remain unknown, although structures of medulla oblongata, midbrain or diencephalon are known to be targets for progesterone. In the present study, on ex vivo preparations of central nervous system of newborn rats, we show that acute exposure to etonogestrel (active metabolite of desogestrel) enhanced the increased respiratory frequency induced by metabolic acidosis via a mechanism involving supramedullary structures located in pontine, mesencephalic or diencephalic regions. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  10. Extracellular polysaccharides are involved in the attachment of Azospirillum brasilense and Rhizobium leguminosarum to arbuscular mycorrhizal structures

    Directory of Open Access Journals (Sweden)

    V Bianciotto

    2009-12-01

    Full Text Available Arbuscular mycorrhizal (AM fungi, one of the most important component of the soil microbial community, establish physical interactions with naturally occurring and genetically modified bacterial biofertilizers and biopesticides, commonly referred to as plant growth-promoting rhizobacteria (PGPR. We have used a genetic approach to investigate the bacterial components possibly involved in the attachment of two PGPR (Azospirillum and Rhizobium to AM roots and AM fungal structures. Mutants affected in extracellular polysaccharides (EPS have been tested in in vitro adhesion assays and shown to be strongly impaired in the attachment to both types of surfaces as well as to quartz fibers. Anchoring of rhizobacteria to AM fungal structures may have special ecological and biotechnological significance because it may facilitate colonisation of new rhizospheres by the bacteria, and may be an essential trait for the development of mixed inocula.

  11. Application of neural networks in coastal engineering

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.

    the neural network attractive. A neural network is an information processing system modeled on the structure of the dynamic process. It can solve the complex/nonlinear problems quickly once trained by operating on problems using an interconnected number...

  12. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  13. 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.

  14. 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.

  15. Structure reveals regulatory mechanisms of a MaoC-like hydratase from Phytophthora capsici involved in biosynthesis of polyhydroxyalkanoates (PHAs).

    Science.gov (United States)

    Wang, Huizheng; Zhang, Kai; Zhu, Jie; Song, Weiwei; Zhao, Li; Zhang, Xiuguo

    2013-01-01

    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. 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. The data in our study reveal the regulatory mechanism of an (R)-hydratase, providing information on enzyme engineering to produce low cost PHAs.

  16. 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 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.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.The data in our study reveal the regulatory mechanism of an (R-hydratase, providing information on enzyme engineering to produce low cost PHAs.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. AMES, NESC and ENIQ: European networks in the field of structural integrity involving NDE and inspection effectiveness assessment

    International Nuclear Information System (INIS)

    Crutzen, S.; Hurst, R.; Debarberis, L.; Lemaitre, P.; Eriksen, B.

    1999-01-01

    Three European networks on structural integrity aspects of ageing nuclear components are presently managed by the Institute for Advanced Materials of the Joint Research Centre of the European Commission: AMES (Ageing Materials Evaluation and Studies), ENIQ (European Network for Inspection Qualification) and NESC (Network for Evaluating Steel Components). All three networks involve actions, which aim at the effectiveness and reliability assessment of NDE techniques and of inspection procedures: Either for materials damage detection and characterisation or for defect detection and evaluation. This paper is describing very generally the objectives of the three networks and is then concentrating on the results obtained in ENIQ, which are relevant with ISI and regulatory issues. (orig./DGE)

  2. Primary structure and subcellular localization of two fimbrial subunit-like proteins involved in the biosynthesis of K99 fibrillae.

    Science.gov (United States)

    Roosendaal, E; Jacobs, A A; Rathman, P; Sondermeyer, C; Stegehuis, F; Oudega, B; de Graaf, F K

    1987-09-01

    Analysis of the nucleotide sequence of the distal part of the fan gene cluster encoding the proteins involved in the biosynthesis of the fibrillar adhesin, K99, revealed the presence of two structural genes, fanG and fanH. The amino acid sequence of the gene products (FanG and FanH) showed significant homology to the amino acid sequence of the fibrillar subunit protein (FanC). Introduction of a site-specific frameshift mutation in fanG or fanH resulted in a simultaneous decrease in fibrillae production and adhesive capacity. Analysis of subcellular fractions showed that, in contrast to the K99 fibrillar subunit (FanC), both the FanH and the FanG protein were loosely associated with the outer membrane, possibly on the periplasmic side, but were not components of the fimbriae themselves.

  3. 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.

  4. 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.

    2017-01-01

    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. PMID:28161674

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Using Neural Networks to Predict the Hardness of Aluminum Alloys

    Directory of Open Access Journals (Sweden)

    B. Zahran

    2015-02-01

    Full Text Available Aluminum alloys have gained significant industrial importance being involved in many of the light and heavy industries and especially in aerospace engineering. The mechanical properties of aluminum alloys are defined by a number of principal microstructural features. Conventional mathematical models of these properties are sometimes very complex to be analytically calculated. In this paper, a neural network model is used to predict the correlations between the hardness of aluminum alloys in relation to certain alloying elements. A backpropagation neural network is trained using a thorough dataset. The impact of certain elements is documented and an optimum structure is proposed.

  10. Time-frequency analysis to a particular type of scattering problems involving metallic-polymer tubing structures.

    Science.gov (United States)

    Elhanaoui, Abdelkader; Aassif, Elhoucein; Maze, Gérard; Décultot, Dominique

    2018-01-01

    In this paper, recent studies of backscattered acoustic signals in thinner steel-polymer tubing structures have been presented. Reassigned smoothed pseudo Wigner-Ville (rspWV) analysis has been adopted in order to diminish the cross-term effect, and achieve high resolution spectral. Vibration modes, which are associated to the resonances of circumferential waves, have been determined by using the modal isolation plan representation. At normalized frequencies below 140, an appreciable influence from the polymer coating thickness on the A 0 + and S 0 modes has been noticed. Furthermore, the trajectory of the A 0 - wave has been modified in the normalized frequency band 40-42. Group velocity curves of the A 0 - wave have, then, been graphically illustrated. The findings have shown a particular curvature change at reduced frequency 41 in the case of an immersed two-layer tube in water. Studies of acoustic backscattering involving steel-polymer tubing structures have confirmed the significant coupling of A 0 + and S 0 waves. Besides, the disappearance of the A 0 + resonance trajectory has been observed; which is a very important phenomenon to understand. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. 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.

  12. 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

  13. 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

  14. Recycling signals in the neural crest

    OpenAIRE

    Taneyhill, Lisa A.; Bronner-Fraser, Marianne E.

    2006-01-01

    Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

  15. Recycling signals in the neural crest.

    Science.gov (United States)

    Taneyhill, Lisa A; Bronner-Fraser, Marianne

    2005-01-01

    Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

  16. Neural coding of image structure and contrast polarity of Cartesian, hyperbolic, and polar gratings in the primary and secondary visual cortex of the tree shrew.

    Science.gov (United States)

    Poirot, Jordan; De Luna, Paolo; Rainer, Gregor

    2016-04-01

    We comprehensively characterize spiking and visual evoked potential (VEP) activity in tree shrew V1 and V2 using Cartesian, hyperbolic, and polar gratings. Neural selectivity to structure of Cartesian gratings was higher than other grating classes in both visual areas. From V1 to V2, structure selectivity of spiking activity increased, whereas corresponding VEP values tended to decrease, suggesting that single-neuron coding of Cartesian grating attributes improved while the cortical columnar organization of these neurons became less precise from V1 to V2. We observed that neurons in V2 generally exhibited similar selectivity for polar and Cartesian gratings, suggesting that structure of polar-like stimuli might be encoded as early as in V2. This hypothesis is supported by the preference shift from V1 to V2 toward polar gratings of higher spatial frequency, consistent with the notion that V2 neurons encode visual scene borders and contours. Neural sensitivity to modulations of polarity of hyperbolic gratings was highest among all grating classes and closely related to the visual receptive field (RF) organization of ON- and OFF-dominated subregions. We show that spatial RF reconstructions depend strongly on grating class, suggesting that intracortical contributions to RF structure are strongest for Cartesian and polar gratings. Hyperbolic gratings tend to recruit least cortical elaboration such that the RF maps are similar to those generated by sparse noise, which most closely approximate feedforward inputs. Our findings complement previous literature in primates, rodents, and carnivores and highlight novel aspects of shape representation and coding occurring in mammalian early visual cortex. Copyright © 2016 the American Physiological Society.

  17. Parallel consensual neural networks.

    Science.gov (United States)

    Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

    1997-01-01

    A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

  18. Neural network to diagnose lining condition

    Science.gov (United States)

    Yemelyanov, V. A.; Yemelyanova, N. Y.; Nedelkin, A. A.; Zarudnaya, M. V.

    2018-03-01

    The paper presents data on the problem of diagnosing the lining condition at the iron and steel works. The authors describe the neural network structure and software that are designed and developed to determine the lining burnout zones. The simulation results of the proposed neural networks are presented. The authors note the low learning and classification errors of the proposed neural networks. To realize the proposed neural network, the specialized software has been developed.

  19. 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.

  20. Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

    Science.gov (United States)

    Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

    2015-06-01

    Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

  1. Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

    International Nuclear Information System (INIS)

    Hosseini-Golgoo, S M; Bozorgi, H; Saberkari, A

    2015-01-01

    Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively. (paper)

  2. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  3. 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.

  4. X-ray diffraction study on the structure of concentrated aqueous solutions involving alanine molecules with different optical activities

    International Nuclear Information System (INIS)

    Kameda, Yasuo; Okuyama, Aya; Amo, Yuko; Usuki, Takeshi; Kohara, Shinji

    2007-01-01

    X-ray diffraction measurements on aqueous 2.5 mol% DL-, L-, and D-alanine solutions in D 2 O were carried out at 26±2degC in order to obtain information concerning the difference in the hydrogen-bonded structure between aqueous solutions involving amino acid molecules with different optical activities. The difference function, Δi inter (Q), between intermolecular interference term observed for DL- and L-alanine and between DL- and D-alanine solutions both exhibited a first peak at Q=1.6 A -1 , followed by oscillatory features extending to higher-Q region, implying that there is a difference in the intermolecular structure is present between these solutions. The difference distribution function, Δg inter (r), obtained from the Fourier transform of the Δi inter (Q) between DL- and L-, and between DL- and D-alanine solutions showed an obvious negative peak at r=2.8 A, which was attributed to the nearest neighbor hydrogen-bonded O...O interaction. The least squares fitting analysis of the observed Δi inter (Q) showed that the intermolecular O...O distance and the difference in the coordination number between DL- and L-, and between DL- and D-alanine solutions are 2.76(2) A and -0.18(1), and 2.81(3) A and -0.18(1), respectively. It was concluded that the intermolecular hydrogen-bonded network in aqueous L- and D-alanine solutions is stronger than that in the DL-alanine solution. (author)

  5. 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...

  6. Joint stiffness identification of body structure using neural network. Jointed part composed of 2 beams; Neural network ni yoru shatai kozo no ketsugo gosei dotei. Buzai 2 hon kara naru ketsugobu no baai

    Energy Technology Data Exchange (ETDEWEB)

    Okabe, A; Tomioka, N [Nihon University, Tokyo (Japan)

    1997-10-01

    The method to obtain a joint stiffness value from displacements of jointed part using hierarchical neural networks in case of a jointed part composed of two beams were proposed. First, the sample data of displacements of jointed part vs. joint stiffness are prepared as learned data. Second, the relations between displacements of jointed part and joint stiffness are constructed from these learned data using a hierarchical neural networks. It was found that the value of joint stiffness can be obtained from displacement of jointed part by the trained neural network. 4 refs., 9 figs., 2 tabs.

  7. Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering and recognition

    Science.gov (United States)

    Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

    2018-03-01

    The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will be discussed. We shall consider these neural structures and their spatial-invariant equivalental models (SIEMs) based on proposed equivalent two-dimensional functions of image similarity and the corresponding matrix-matrix (or tensor) procedures using as basic operations of continuous logic and nonlinear processing. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalent weighing of input patterns. We show that these SL_EC_RMNSs have several advantages, such as the self-study and self-identification of features and signs of the similarity of fragments, ability to clustering and recognize of image fragments with best efficiency and strong mutual correlation. The proposed combined with learning-recognition 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 continuous logic and nonlinear processing algorithms and to k-average method or method the winner takes all (WTA). The experimental results confirmed that 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 images of different dimensions (a reference

  8. Construction of a Piezoresistive Neural Sensor Array

    Science.gov (United States)

    Carlson, W. B.; Schulze, W. A.; Pilgrim, P. M.

    1996-01-01

    The construction of a piezoresistive - piezoelectric sensor (or actuator) array is proposed using 'neural' connectivity for signal recognition and possible actuation functions. A closer integration of the sensor and decision functions is necessary in order to achieve intrinsic identification within the sensor. A neural sensor is the next logical step in development of truly 'intelligent' arrays. This proposal will integrate 1-3 polymer piezoresistors and MLC electroceramic devices for applications involving acoustic identification. The 'intelligent' piezoresistor -piezoelectric system incorporates printed resistors, composite resistors, and a feedback for the resetting of resistances. A model of a design is proposed in order to simulate electromechanical resistor interactions. The goal of optimizing a sensor geometry for improving device reliability, training, & signal identification capabilities is the goal of this work. At present, studies predict performance of a 'smart' device with a significant control of 'effective' compliance over a narrow pressure range due to a piezoresistor percolation threshold. An interesting possibility may be to use an array of control elements to shift the threshold function in order to change the level of resistance in a neural sensor array for identification, or, actuation applications. The proposed design employs elements of: (1) conductor loaded polymers for a 'fast' RC time constant response; and (2) multilayer ceramics for actuation or sensing and shifting of resistance in the polymer. Other material possibilities also exist using magnetoresistive layered systems for shifting the resistance. It is proposed to use a neural net configuration to test and to help study the possible changes required in the materials design of these devices. Numerical design models utilize electromechanical elements, in conjunction with structural elements in order to simulate piezoresistively controlled actuators and changes in resistance of sensors

  9. Neural Mechanisms of Foraging

    OpenAIRE

    Kolling, Nils; Behrens, Timothy EJ; Mars, Rogier B; Rushworth, Matthew FS

    2012-01-01

    Behavioural economic studies, involving limited numbers of choices, have provided key insights into neural decision-making mechanisms. By contrast, animals’ foraging choices arise in the context of sequences of encounters with prey/food. On each encounter the animal chooses to engage or whether the environment is sufficiently rich that searching elsewhere is merited. The cost of foraging is also critical. We demonstrate humans can alternate between two modes of choice, comparative decision-ma...

  10. 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.

  11. Structuring an integrated care system: interpreted through the enacted diversity of the actors involved – the case of a French healthcare network

    Directory of Open Access Journals (Sweden)

    Corinne Grenier

    2011-02-01

    Full Text Available Research question: We are looking at the process of structuring an integrated care system as an innovative process that swings back and forth between the diversity of the actors involved, local aspirations and national and regional regulations. We believe that innovation is enriched by the variety of the actors involved, but may also be blocked or disrupted by that diversity. Our research aims to add to other research, which, when questioning these integrated systems, analyses how the actors involved deal with diversity without really questioning it. Case study: The empirical basis of the paper is provided by case study analysis. The studied integrated care system is a French healthcare network that brings together healthcare professionals and various organisations in order to improve the way in which interventions are coordinated and formalised, in order to promote better detection and diagnosis procedures and the implementation of a care protocol. We consider this case as instrumental in developing theoretical proposals for structuring an integrated care system in light of the diversity of the actors involved. Results and discussion: We are proposing a model for structuring an integrated care system in light of the enacted diversity of the actors involved. This model is based on three factors: the diversity enacted by the leaders, three stances for considering the contribution made by diversity in the structuring process and the specific leading role played by those in charge of the structuring process.  Through this process, they determined how the actors involved in the project were differentiated, and on what basis those actors were involved. By mobilizing enacted diversity, the leaders are seeking to channel the emergence of a network in light of their own representation of that network. This model adds to published research on the structuring of integrated care systems.

  12. Structuring an integrated care system: interpreted through the enacted diversity of the actors involved – the case of a French healthcare network

    Directory of Open Access Journals (Sweden)

    Corinne Grenier

    2011-02-01

    Full Text Available Research question: We are looking at the process of structuring an integrated care system as an innovative process that swings back and forth between the diversity of the actors involved, local aspirations and national and regional regulations. We believe that innovation is enriched by the variety of the actors involved, but may also be blocked or disrupted by that diversity. Our research aims to add to other research, which, when questioning these integrated systems, analyses how the actors involved deal with diversity without really questioning it.Case study: The empirical basis of the paper is provided by case study analysis. The studied integrated care system is a French healthcare network that brings together healthcare professionals and various organisations in order to improve the way in which interventions are coordinated and formalised, in order to promote better detection and diagnosis procedures and the implementation of a care protocol. We consider this case as instrumental in developing theoretical proposals for structuring an integrated care system in light of the diversity of the actors involved.Results and discussion: We are proposing a model for structuring an integrated care system in light of the enacted diversity of the actors involved. This model is based on three factors: the diversity enacted by the leaders, three stances for considering the contribution made by diversity in the structuring process and the specific leading role played by those in charge of the structuring process.  Through this process, they determined how the actors involved in the project were differentiated, and on what basis those actors were involved. By mobilizing enacted diversity, the leaders are seeking to channel the emergence of a network in light of their own representation of that network. This model adds to published research on the structuring of integrated care systems.

  13. Neural activation toward erotic stimuli in homosexual and heterosexual males.

    Science.gov (United States)

    Kagerer, Sabine; Klucken, Tim; Wehrum, Sina; Zimmermann, Mark; Schienle, Anne; Walter, Bertram; Vaitl, Dieter; Stark, Rudolf

    2011-11-01

    Studies investigating sexual arousal exist, yet there are diverging findings on the underlying neural mechanisms with regard to sexual orientation. Moreover, sexual arousal effects have often been confounded with general arousal effects. Hence, it is still unclear which structures underlie the sexual arousal response in homosexual and heterosexual men. Neural activity and subjective responses were investigated in order to disentangle sexual from general arousal. Considering sexual orientation, differential and conjoint neural activations were of interest. The functional magnetic resonance imaging (fMRI) study focused on the neural networks involved in the processing of sexual stimuli in 21 male participants (11 homosexual, 10 heterosexual). Both groups viewed pictures with erotic content as well as aversive and neutral stimuli. The erotic pictures were subdivided into three categories (most sexually arousing, least sexually arousing, and rest) based on the individual subjective ratings of each participant. Blood oxygen level-dependent responses measured by fMRI and subjective ratings. A conjunction analysis revealed conjoint neural activation related to sexual arousal in thalamus, hypothalamus, occipital cortex, and nucleus accumbens. Increased insula, amygdala, and anterior cingulate gyrus activation could be linked to general arousal. Group differences emerged neither when viewing the most sexually arousing pictures compared with highly arousing aversive pictures nor compared with neutral pictures. Results suggest that a widespread neural network is activated by highly sexually arousing visual stimuli. A partly distinct network of structures underlies sexual and general arousal effects. The processing of preferred, highly sexually arousing stimuli recruited similar structures in homosexual and heterosexual males. © 2011 International Society for Sexual Medicine.

  14. The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

    Science.gov (United States)

    Pla, Patrick; Monsoro-Burq, Anne H

    2018-05-28

    The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

  15. 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.

  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. A pilot study for distinguishing chromophobe renal cell carcinoma and oncocytoma using second harmonic generation imaging and convolutional neural network analysis of collagen fibrillar structure

    Science.gov (United States)

    Judd, Nicolas; Smith, Jason; Jain, Manu; Mukherjee, Sushmita; Icaza, Michael; Gallagher, Ryan; Szeligowski, Richard; Wu, Binlin

    2018-02-01

    A clear distinction between oncocytoma and chromophobe renal cell carcinoma (chRCC) is critically important for clinical management of patients. But it may often be difficult to distinguish the two entities based on hematoxylin and eosin (H and E) stained sections alone. In this study, second harmonic generation (SHG) signals which are very specific to collagen were used to image collagen fibril structure. We conduct a pilot study to develop a new diagnostic method based on the analysis of collagen associated with kidney tumors using convolutional neural networks (CNNs). CNNs comprise a type of machine learning process well-suited for drawing information out of images. This study examines a CNN model's ability to differentiate between oncocytoma (benign), and chRCC (malignant) kidney tumor images acquired with second harmonic generation (SHG), which is very specific for collagen matrix. To the best of our knowledge, this is the first study that attempts to distinguish the two entities based on their collagen structure. The model developed from this study demonstrated an overall classification accuracy of 68.7% with a specificity of 66.3% and sensitivity of 74.6%. While these results reflect an ability to classify the kidney tumors better than chance, further studies will be carried out to (a) better realize the tumor classification potential of this method with a larger sample size and (b) combining SHG with two-photon excited intrinsic fluorescence signal to achieve better classification.

  18. 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....

  19. 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.

  20. 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. .

  1. 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

  2. Memory Consolidation and Neural Substrate of Reward

    Directory of Open Access Journals (Sweden)

    Redolar-Ripoll, Diego

    2012-08-01

    Full Text Available The aim of this report is to analyze the relationships between reward and learning and memory processes. Different studies have described how information about rewards influences behavior and how the brain uses this reward information to control learning and memory processes. Reward nature seems to be processed in different ways by neurons in different brain structures, ranging from the detection and perception of rewards to the use of information about predicted rewards for the control of goal-directed behavior. The neural substrate underling this processing of reward information is a reliable way of improving learning and memory processes. Evidence from several studies indicates that this neural system can facilitate memory consolidation in a wide variety of learning tasks. From a molecular perspective, certain cardinal features of reward have been described as forms of memory. Studies of human addicts and studies in animal models of addiction show that chronic drug exposure produces stable changes in the brain at the cellular and molecular levels that underlie the long-lasting behavioral plasticity associated with addiction. These molecular and cellular adaptations involved in addiction are also implicated in learning and memory processes. Dopamine seems to be a critical common signal to activate different genetic mechanisms that ultimately remodel synapses and circuits. Despite memory is an active and complex process mediated by different brain areas, the neural substrate of reward is able to improve memory consolidation in a several paradigms. We believe that there are many equivalent traits between reward and learning and memory processes.

  3. Theoretical exploration of the neural bases of behavioural disinhibition, apathy and executive dysfunction in preclinical Alzheimer's disease in people with Down's syndrome: potential involvement of multiple frontal-subcortical neuronal circuits.

    Science.gov (United States)

    Ball, S L; Holland, A J; Watson, P C; Huppert, F A

    2010-04-01

    planning, response inhibition and working memory) and an object memory task, (also thought to place high demands on working memory), while 'apathy' score significantly predicted performance on two different tasks, those measuring spatial reversal and prospective memory (p decline was associated only with performance on a delayed recall task while antidepressant medication use was associated with better performance on a working memory task (p underlying neural circuitry and supports the involvement of multiple frontal-subcortical circuits in the early stages of DAT in DS. However, the prominence of disinhibition in the behavioural profile (which more closely resembles that of disinhibited subtype of DFT than that of AD in the general population) leads us to postulate that the serotonergically mediated orbitofrontal circuit may be disproportionately affected. A speculative theory is developed regarding the biological basis for observed changes and discussion is focused on how this understanding may aid us in the development of treatments directly targeting underlying abnormalities.

  4. 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.

  5. 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.

  6. 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.

  7. 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…

  8. 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

  9. 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.

  10. 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...

  11. 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

  12. Region-Specific Involvement of Actin Rearrangement-Related Synaptic Structure Alterations in Conditioned Taste Aversion Memory

    Science.gov (United States)

    Bi, Ai-Ling; Wang, Yue; Li, Bo-Qin; Wang, Qian-Qian; Ma, Ling; Yu, Hui; Zhao, Ling; Chen, Zhe-Yu

    2010-01-01

    Actin rearrangement plays an essential role in learning and memory; however, the spatial and temporal regulation of actin dynamics in different phases of associative memory has not been fully understood. Here, using the conditioned taste aversion (CTA) paradigm, we investigated the region-specific involvement of actin rearrangement-related…

  13. 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.

  14. Quantitative structure-activity relationship modeling on in vitro endocrine effects and metabolic stability involving 26 selected brominated flame retardants

    NARCIS (Netherlands)

    Harju, M.; Hamers, T.; Kamstra, J.H.; Sonneveld, E.; Boon, J.P.

    2007-01-01

    In this work, quantitative structure-activity relationships (QSARs) were developed to aid human and environmental risk assessment processes for brominated flame retardants (BFRs). Brominated flame retardants, such as the high-production-volume chemicals polybrominated diphenyl ethers (PBDEs),

  15. The conserved structures of the 5' nontranslated region of Citrus tristeza virus are involved in replication and virion assembly

    International Nuclear Information System (INIS)

    Gowda, Siddarame; Satyanarayana, Tatineni; Ayllon, Maria A.; Moreno, Pedro; Flores, Ricardo; Dawson, William O.

    2003-01-01

    The genomic RNA of different isolates of Citrus tristeza virus (CTV) reveals an unusual pattern of sequence diversity: the 3' halves are highly conserved (homology >90%), while the 5' halves show much more dissimilarity, with the 5' nontranslated region (NTR) containing the highest diversity (homology as low as 42%). Yet, positive-sense sequences of the 5' NTR were predicted to fold into nearly identical structures consisting of two stem-loops (SL1 and SL2) separated by a short spacer region. The predicted most stable secondary structures of the negative-sense sequences were more variable. We introduced mutations into the 5' NTR of a CTV replicon to alter the sequence and/or the predicted secondary structures with or without additional compensatory changes designed to restore predicted secondary structures, and examined their effect on replication in transfected protoplasts. The results suggested that the predicted secondary structures of the 5' NTR were more important for replication than the primary structure. Most mutations that were predicted to disrupt the secondary structures fail to replicate, while compensatory mutations were allowed replication to resume. The 5' NTR mutations that were tolerated by the CTV replicon were examined in the full-length virus for effects on replication and production of the multiple subgenomic RNAs. Additionally, the ability of these mutants to produce virions was monitored by electron microscopy and by passaging the progeny nucleocapsids to another batch of protoplasts. Some of the mutants with compensatory sequence alterations predicted to rebuild similar secondary structures allowed replication at near wild-type levels but failed to passage, suggesting that the 5' NTR contains sequences required for both replication and virion assembly

  16. Functional and Structural Characterization of a Receptor-Like Kinase Involved in Germination and Cell Expansion in Arabidopsis

    Science.gov (United States)

    Wu, Zhen; Liang, Shan; Song, Wen; Lin, Guangzhong; Wang, Weiguang; Zhang, Heqiao; Han, Zhifu; Chai, Jijie

    2017-01-01

    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). PMID:29213277

  17. 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

  18. 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...

  19. Direct adaptive control using feedforward neural networks

    OpenAIRE

    Cajueiro, Daniel Oliveira; Hemerly, Elder Moreira

    2003-01-01

    ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the conver...

  20. Involvement of right piriform cortex in olfactory familiarity judgments. : Familiarity judgment in olfaction

    OpenAIRE

    Plailly , Jane; Bensafi , Moustafa; Pachot-Clouard , Mathilde; Delon-Martin , Chantal; Kareken , David ,; Rouby , Catherine; Segebarth , Christoph; Royet , Jean ,

    2005-01-01

    International audience; Previous studies have shown activation of right orbitofrontal cortex during judgments of odor familiarity. In the present study, we sought to extend our knowledge about the neural circuits involved in such a task by exploring the involvement of the right prefrontal areas and limbic/primary olfactory structures. Fourteen right-handed male subjects were tested using fMRI with a single functional run of two olfactory conditions (odor detection and familiarity judgments). ...

  1. 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.

  2. 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.

  3. Structural Studies of RNA Helicases Involved in Eukaryotic Pre-mRNA Splicing, Ribosome Biogenesis, and Translation Initiation

    DEFF Research Database (Denmark)

    He, Yangzi

    and ligates the neighbouring exons to generate mature mRNAs. Prp43 is an RNA helicase of the DEAH/RHA family. In yeast, once mRNAs are released, Prp43 catalyzes the disassembly of spliceosomes. The 18S, 5.8S and 25S rRNAs are transcribed as a single polycistronic transcript—the 35S pre......-rRNA. It is nucleolytically cleaved and chemically modified to generate mature rRNAs, which assemble with ribosomal proteins to form the ribosome. Prp43 is required for the processing of the 18S rRNA. Using X-ray crystallography, I determined a high resolution structure of Prp43 bound to ADP, the first structure of a DEAH....../RHA helicase. It defined the conserved structural features of all DEAH/RHA helicases, and unveiled a novel nucleotide binding site. Additionally a preliminary low resolution structure of a ternary complex comprising Prp43, a non-hydrolyzable ATP analogue, and a single-stranded RNA, was obtained. The ribosome...

  4. 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...

  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. Modulation of α-synuclein fibrillization by ring-fused 2-pyridones: templation and inhibition involve oligomers with different structure.

    Science.gov (United States)

    Horvath, Istvan; Sellstedt, Magnus; Weise, Christoph; Nordvall, Lina-Maria; Krishna Prasad, G; Olofsson, Anders; Larsson, Göran; Almqvist, Fredrik; Wittung-Stafshede, Pernilla

    2013-04-15

    In a recent study we discovered that a ring-fused 2-pyridone compound triggered fibrillization of a key protein in Parkinson's disease, α-synuclein. To reveal how variations in compound structure affect protein aggregation, we now prepared a number of strategic analogs and tested their effects on α-synuclein amyloid fiber formation in vitro. We find that, in contrast to the earlier templating effect, some analogs inhibit α-synuclein fibrillization. For both templating and inhibiting compounds, the key species formed in the reactions are α-synuclein oligomers that contain compound. Despite similar macroscopic appearance, the templating and inhibiting oligomers are distinctly different in secondary structure content. When the inhibitory oligomers are added in seed amounts, they inhibit fresh α-synuclein aggregation reactions. Our study demonstrates that small chemical changes to the same central fragment can result in opposite effects on protein aggregation. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. Sequence and structural analysis of the chitinase insertion domain reveals two conserved motifs involved in chitin-binding.

    Directory of Open Access Journals (Sweden)

    Hai Li

    2010-01-01

    Full Text Available 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.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.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.

  8. 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…

  9. Identification of the Genes Involved in the Biofilm-like Structures on Actinomyces oris K20, a Clinical Isolate from an Apical Lesion

    Science.gov (United States)

    2013-01-01

    bacteria in clinically asymptomatic periapical pathosis. J Endod 1990;16:534–8. 5. Nair PNR. On the causes of persistent apical periodontitis : a review...Identification of the Genes Involved in the Biofilm-like Structures on Actinomyces oris K20, a Clinical Isolate from an Apical Lesion Chiho Mashimo...Actinomyces oris K20. (J Endod 2013;39:44–48) Key Words Actinomyces oris, apical abscess, biofilm, polysac- charide deacetylase, transposon mutagenesis

  10. Documentation and analysis of traumatic injuries in clinical forensic medicine involving structured light three-dimensional surface scanning versus photography.

    Science.gov (United States)

    Shamata, Awatif; Thompson, Tim

    2018-05-10

    Non-contact three-dimensional (3D) surface scanning has been applied in forensic medicine and has been shown to mitigate shortcoming of traditional documentation methods. The aim of this paper is to assess the efficiency of structured light 3D surface scanning in recording traumatic injuries of live cases in clinical forensic medicine. The work was conducted in Medico-Legal Centre in Benghazi, Libya. A structured light 3D surface scanner and ordinary digital camera with close-up lens were used to record the injuries and to have 3D and two-dimensional (2D) documents of the same traumas. Two different types of comparison were performed. Firstly, the 3D wound documents were compared to 2D documents based on subjective visual assessment. Additionally, 3D wound measurements were compared to conventional measurements and this was done to determine whether there was a statistical significant difference between them. For this, Friedman test was used. The study established that the 3D wound documents had extra features over the 2D documents. Moreover; the 3D scanning method was able to overcome the main deficiencies of the digital photography. No statistically significant difference was found between the 3D and conventional wound measurements. The Spearman's correlation established strong, positive correlation between the 3D and conventional measurement methods. Although, the 3D surface scanning of the injuries of the live subjects faced some difficulties, the 3D results were appreciated, the validity of 3D measurements based on the structured light 3D scanning was established. Further work will be achieved in forensic pathology to scan open injuries with depth information. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

  11. In vitro reconstitution of sortase-catalyzed pilus polymerization reveals structural elements involved in pilin cross-linking.

    Science.gov (United States)

    Chang, Chungyu; Amer, Brendan R; Osipiuk, Jerzy; McConnell, Scott A; Huang, I-Hsiu; Hsieh, Van; Fu, Janine; Nguyen, Hong H; Muroski, John; Flores, Erika; Ogorzalek Loo, Rachel R; Loo, Joseph A; Putkey, John A; Joachimiak, Andrzej; Das, Asis; Clubb, Robert T; Ton-That, Hung

    2018-06-12

    Covalently cross-linked pilus polymers displayed on the cell surface of Gram-positive bacteria are assembled by class C sortase enzymes. These pilus-specific transpeptidases located on the bacterial membrane catalyze a two-step protein ligation reaction, first cleaving the LPXTG motif of one pilin protomer to form an acyl-enzyme intermediate and then joining the terminal Thr to the nucleophilic Lys residue residing within the pilin motif of another pilin protomer. To date, the determinants of class C enzymes that uniquely enable them to construct pili remain unknown. Here, informed by high-resolution crystal structures of corynebacterial pilus-specific sortase (SrtA) and utilizing a structural variant of the enzyme (SrtA 2M ), whose catalytic pocket has been unmasked by activating mutations, we successfully reconstituted in vitro polymerization of the cognate major pilin (SpaA). Mass spectrometry, electron microscopy, and biochemical experiments authenticated that SrtA 2M synthesizes pilus fibers with correct Lys-Thr isopeptide bonds linking individual pilins via a thioacyl intermediate. Structural modeling of the SpaA-SrtA-SpaA polymerization intermediate depicts SrtA 2M sandwiched between the N- and C-terminal domains of SpaA harboring the reactive pilin and LPXTG motifs, respectively. Remarkably, the model uncovered a conserved TP(Y/L)XIN(S/T)H signature sequence following the catalytic Cys, in which the alanine substitutions abrogated cross-linking activity but not cleavage of LPXTG. These insights and our evidence that SrtA 2M can terminate pilus polymerization by joining the terminal pilin SpaB to SpaA and catalyze ligation of isolated SpaA domains in vitro provide a facile and versatile platform for protein engineering and bio-conjugation that has major implications for biotechnology.

  12. Characterization of lipoteichoic acid structures from three probiotic Bacillus strains: involvement of D-alanine in their biological activity.

    Science.gov (United States)

    Villéger, Romain; Saad, Naima; Grenier, Karine; Falourd, Xavier; Foucat, Loïc; Urdaci, Maria C; Bressollier, Philippe; Ouk, Tan-Sothea

    2014-10-01

    Probiotics represent a potential strategy to influence the host's immune system thereby modulating immune response. Lipoteichoic Acid (LTA) is a major immune-stimulating component of Gram-positive cell envelopes. This amphiphilic polymer, anchored in the cytoplasmic membrane by means of its glycolipid component, typically consists of a poly (glycerol-phosphate) chain with D-alanine and/or glycosyl substitutions. LTA is known to stimulate macrophages in vitro, leading to secretion of inflammatory mediators such as Nitric Oxide (NO). This study investigates the structure-activity relationship of purified LTA from three probiotic Bacillus strains (Bacillus cereus CH, Bacillus subtilis CU1 and Bacillus clausii O/C). LTAs were extracted from bacterial cultures and purified. Chemical modification by means of hydrolysis at pH 8.5 was performed to remove D-alanine. The molecular structure of native and modified LTAs was determined by (1)H NMR and GC-MS, and their inflammatory potential investigated by measuring NO production by RAW 264.7 macrophages. Structural analysis revealed several differences between the newly characterized LTAs, mainly relating to their D-alanylation rates and poly (glycerol-phosphate) chain length. We observed induction of NO production by LTAs from B. subtilis and B. clausii, whereas weaker NO production was observed with B. cereus. LTA dealanylation abrogated NO production independently of the glycolipid component, suggesting that immunomodulatory potential depends on D-alanine substitutions. D-alanine may control the spatial configuration of LTAs and their recognition by cell receptors. Knowledge of molecular mechanisms behind the immunomodulatory abilities of probiotics is essential to optimize their use.

  13. Structural Injury after Lithium Treatment in Human and Rat Kidney involves Glycogen Synthase Kinase-3β Positive Epithelium

    DEFF Research Database (Denmark)

    Kjærsgaard, Gitte; Madsen, Kirsten; Marcussen, Niels

    2011-01-01

    Lithium is reabsorbed by distal nephron segments in sodium depleted states. It was hypothesized that lithium causes permanent injury to the developing kidney particularly in the sodium-retaining phase around weaning through entry into epithelial cells of the distal nephron and inhibition of glyco....... Lithium causes proliferation, structural injury and increases inactive pGSK-3β abundance in these segments. The data are compatible with epithelial entry of lithium and a causal role for GSK-3β in postnatal developing cortical collecting duct epithelium....

  14. Structural factors involved in the recognition of helix distortions in uv-damaged DNA by model peptides

    Energy Technology Data Exchange (ETDEWEB)

    Lang, H; Zimmer, C [Akademie der Wissenschaften der DDR, Jena. Forschungszentrum fuer Molekularbiologie und Medizin

    1977-02-28

    On the basis of our previous and present results concerning conformational changes of DNA after uv-irradiation some conclusions on the structure of DNA double helix in uv-damaged regions were drawn. From the results it appears that local distortions like denaturation or premelting should be excluded. Furthermore it was shown that the thymine dimerization strongly depends on the adjacent nucleic acid bases. By means of a strong binding effect of the oligopeptide netropsin to DNA irradiated at low uv-doses it is concluded that such local distortions in DNA together with a specific sequence-dependent variation of the conformation could act as recognition sites for endonucleases.

  15. 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.

  16. The neural network approach to parton fitting

    International Nuclear Information System (INIS)

    Rojo, Joan; Latorre, Jose I.; Del Debbio, Luigi; Forte, Stefano; Piccione, Andrea

    2005-01-01

    We introduce the neural network approach to global fits of parton distribution functions. First we review previous work on unbiased parametrizations of deep-inelastic structure functions with faithful estimation of their uncertainties, and then we summarize the current status of neural network parton distribution fits

  17. Polaronic and bipolaronic structures in the adiabatic Hubbard-Holstein model involving 2 electrons and its extensions

    International Nuclear Information System (INIS)

    Proville, L.

    1998-01-01

    This thesis brings its contribution to the bipolaronic theory which might explain the origin of superconductivity at high temperature. A polaron is a quasiparticle made up of a localized electron and a deformation in the crystal structure. 2 electrons in singlet states localized on the same site form a bipolaron. Whenever the Coulomb repulsion between the 2 electrons is too strong bipolaron turns into 2 no bound polarons. We study the existence and the mobility of bipolarons. We describe the electron-phonon interaction by the Holstein term and the Coulomb repulsion by the Hubbard term. 2 assumptions are made: - the local electron-phonon interaction is strong and opposes the Coulomb repulsion between Hubbard type electrons - the system is close to the adiabatic limit. The system is reduced to 2 electrons in order to allow an exact treatment and the investigation of some bipolaronic bound states. At 2-dimensions the existence of bipolarons requires a very strong coupling which forbids any classical mobility. In some cases an important tunneling effect appears and we show that mobile bipolarons exist in a particular parameter range. Near the adiabatic limit we prove that polaronic and bipolaronic structures exist for a great number of electrons. (A.C.)

  18. Anosognosia in mild cognitive impairment: Relationship to activation of cortical midline structures involved in self-appraisal

    Science.gov (United States)

    Ries, Michele L.; Jabbar, Britta M.; Schmitz, Taylor W.; Trivedi, Mehul A.; Gleason, Carey E.; Carlsson, Cynthia M.; Rowley, Howard A.; Asthana, Sanjay; Johnson, Sterling C.

    2009-01-01

    Awareness of cognitive dysfunction shown by individuals with Mild Cognitive Impairment (MCI), a condition conferring risk for Alzheimer’s disease (AD), is variable. Anosognosia, or unawareness of loss of function, is beginning to be recognized as an important clinical symptom of MCI. However, little is known about the brain substrates underlying this symptom. We hypothesized that MCI participants’ activation of cortical midline structures (CMS) during self-appraisal would covary with level of insight into cognitive difficulties (indexed by a discrepancy score between patient and informant ratings of cognitive decline in each MCI participant). To address this hypothesis, we first compared 16 MCI participants and 16 age-matched controls, examining brain regions showing conjoint or differential BOLD response during self-appraisal. Second, we used regression to investigate the relationship between awareness of deficit in MCI and BOLD activity during self-appraisal, controlling for extent of memory impairment. Between-group comparisons indicated that MCI participants show subtly attenuated CMS activity during self-appraisal. Regression analysis revealed a highly-significant relationship between BOLD response during self-appraisal and self-awareness of deficit in MCI. This finding highlights the level of anosognosia in MCI as an important predictor of response to self-appraisal in cortical midline structures, brain regions vulnerable to changes in early AD. PMID:17445294

  19. Structure-function analysis of STRUBBELIG, an Arabidopsis atypical receptor-like kinase involved in tissue morphogenesis.

    Directory of Open Access Journals (Sweden)

    Prasad Vaddepalli

    Full Text Available Tissue morphogenesis in plants requires the coordination of cellular behavior across clonally distinct histogenic layers. The underlying signaling mechanisms are presently being unraveled and are known to include the cell surface leucine-rich repeat receptor-like kinase STRUBBELIG in Arabidopsis. To understand better its mode of action an extensive structure-function analysis of STRUBBELIG was performed. The phenotypes of 20 EMS and T-DNA-induced strubbelig alleles were assessed and homology modeling was applied to rationalize their possible effects on STRUBBELIG protein structure. The analysis was complemented by phenotypic, cell biological, and pharmacological investigations of a strubbelig null allele carrying genomic rescue constructs encoding fusions between various mutated STRUBBELIG proteins and GFP. The results indicate that STRUBBELIG accepts quite some sequence variation, reveal the biological importance for the STRUBBELIG N-capping domain, and reinforce the notion that kinase activity is not essential for its function in vivo. Furthermore, individual protein domains of STRUBBELIG cannot be related to specific STRUBBELIG-dependent biological processes suggesting that process specificity is mediated by factors acting together with or downstream of STRUBBELIG. In addition, the evidence indicates that biogenesis of a functional STRUBBELIG receptor is subject to endoplasmic reticulum-mediated quality control, and that an MG132-sensitive process regulates its stability. Finally, STRUBBELIG and the receptor-like kinase gene ERECTA interact synergistically in the control of internode length. The data provide genetic and molecular insight into how STRUBBELIG regulates intercellular communication in tissue morphogenesis.

  20. 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.

  1. The neural basis of unconditional love.

    Science.gov (United States)

    Beauregard, Mario; Courtemanche, Jérôme; Paquette, Vincent; St-Pierre, Evelyne Landry

    2009-05-15

    Functional neuroimaging studies have shown that romantic love and maternal love are mediated by regions specific to each, as well as overlapping regions in the brain's reward system. Nothing is known yet regarding the neural underpinnings of unconditional love. The main goal of this functional magnetic resonance imaging study was to identify the brain regions supporting this form of love. Participants were scanned during a control condition and an experimental condition. In the control condition, participants were instructed to simply look at a series of pictures depicting individuals with intellectual disabilities. In the experimental condition, participants were instructed to feel unconditional love towards the individuals depicted in a series of similar pictures. Significant loci of activation were found, in the experimental condition compared with the control condition, in the middle insula, superior parietal lobule, right periaqueductal gray, right globus pallidus (medial), right caudate nucleus (dorsal head), left ventral tegmental area and left rostro-dorsal anterior cingulate cortex. These results suggest that unconditional love is mediated by a distinct neural network relative to that mediating other emotions. This network contains cerebral structures known to be involved in romantic love or maternal love. Some of these structures represent key components of the brain's reward system.

  2. Adaptive Graph Convolutional Neural Networks

    OpenAIRE

    Li, Ruoyu; Wang, Sheng; Zhu, Feiyun; Huang, Junzhou

    2018-01-01

    Graph Convolutional Neural Networks (Graph CNNs) are generalizations of classical CNNs to handle graph data such as molecular data, point could and social networks. Current filters in graph CNNs are built for fixed and shared graph structure. However, for most real data, the graph structures varies in both size and connectivity. The paper proposes a generalized and flexible graph CNN taking data of arbitrary graph structure as input. In that way a task-driven adaptive graph is learned for eac...

  3. 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

    2014-01-01

    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. PMID:27030784

  4. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  5. 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.

  6. [Posterior tibial tendon dysfunction: what other structures are involved in the development of acquired adult flat foot?].

    Science.gov (United States)

    Herráiz Hidalgo, L; Carrascoso Arranz, J; Recio Rodríguez, M; Jiménez de la Peña, M; Cano Alonso, R; Álvarez Moreno, E; Martínez de Vega Fernández, V

    2014-01-01

    To evaluate the association of posterior tibial tendon dysfunction and lesions of diverse ankle structures diagnosed at MRI with radiologic signs of flat foot. We retrospectively compared 29 patients that had posterior tibial tendon dysfunction (all 29 studied with MRI and 21 also studied with weight-bearing plain-film X-rays) with a control group of 28 patients randomly selected from among all patients who underwent MRI and weight-bearing plain-film X-rays for other ankle problems. In the MRI studies, we analyzed whether a calcaneal spur, talar beak, plantar fasciitis, calcaneal bone edema, Achilles' tendinopathy, spring ligament injury, tarsal sinus disease, and tarsal coalition were present. In the weight-bearing plain-film X-rays, we analyzed the angle of Costa-Bertani and radiologic signs of flat foot. To analyze the differences between groups, we used Fisher's exact test for the MRI findings and for the presence of flat foot and analysis of variance for the angle of Costa-Bertani. Calcaneal spurs, talar beaks, tarsal sinus disease, and spring ligament injury were significantly more common in the group with posterior tibial tendon dysfunction (P<.05). Radiologic signs of flat foot and anomalous values for the angle of Costa-Bertani were also significantly more common in the group with posterior tibial tendon dysfunction (P<.001). We corroborate the association between posterior tibial tendon dysfunction and lesions to the structures analyzed and radiologic signs of flat foot. Knowledge of this association can be useful in reaching an accurate diagnosis. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

  7. Mutational analysis of two structural genes of the remperate lactococcal bacteriophage TP901-1 involved in tail length determination and baseplate assembly

    DEFF Research Database (Denmark)

    Pedersen, Margit; Østergaard, Solvej; Bresciani, José

    2000-01-01

    Two putative structural genes, orf tmp (tape measure protein) and orf bpp (baseplate protein), of the temperate lactococcal phage TP901-1 were examined by introduction of specific mutations in the prophage strain Lactococcus lactic ssp. cremoris 901-1. The adsorption efficiencies of the mutated...... or duplication of 29% in orf tmp was shown to shorten or lengthen the phage tail by approximately 30%, respectively. The orf tmp is proposed to function as a tape measure protein, TMP, important for assembly of the TP901-1 phage tail and involved in tail length determination. Specific mutations in orf bpp...... produced phages which were unable to adsorb to the indicator strain and electron microscopy revealed particles lacking the baseplate structure. The orf bpp is proposed to encode a highly immunogenic structural baseplate protein, BPP, important for assembly of the baseplate. Finally, an assembly pathway...

  8. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as perception, back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally the application of artificial neural network for Chinese character recognition is also given. (author)

  9. The principles of artificial neural network information processing

    International Nuclear Information System (INIS)

    Dai, Ru-Wei

    1993-01-01

    In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as Perceptron, Back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally, the application of artificial neural network for Chinese Character Recognition is also given. (author)

  10. Soil factors involved in the diversity and structure of soil bacterial communities in commercial organic olive orchards in Southern Spain.

    Science.gov (United States)

    Landa, B B; Montes-Borrego, M; Aranda, S; Soriano, M A; Gómez, J A; Navas-Cortés, J A

    2014-04-01

    Nowadays, there is a tendency in olive production systems to reduce tillage or keep a vegetative cover to reduce soil erosion and degradation. However, there is scarce information on the effects of different soil management systems (SMS) in soil bacterial community composition of olive groves. In this study, we have evaluated the effects of soil type and different SMS implemented to control weeds in the structure and diversity of bacterial communities of 58 soils in the two geographic areas that best represent the organic olive production systems in Spain. Bacterial community composition assessed by frequency and intensity of occurrence of terminal restriction profiles (TRFs) derived from terminal restriction fragment length polymorphism (T-RFLP) analysis of amplified 16S ribosomal deoxyribonucleic acid were strongly correlated with soil type/field site (Eutric/Calcaric) that differed mainly in soil particle size distribution and soil pH, followed by a strong effect of SMS, in that order. Canonical discriminant (CD) analysis of TRFs properly classified all of the olive orchard soils as belonging to their respective soil type or SMS. Furthermore, only a small set of TRFs were enough to clearly and significantly differentiate soil samples according to soil type or SMS. Those specific TRFs could be used as bioindicators to assess the effect of changes in SMS aimed to enhance soil quality in olive production systems. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

  11. Psychopathology of addiction: May a SCL-90-based five dimensions structure be applied irrespectively of the involved drug?

    Science.gov (United States)

    Pani, Pier Paolo; Maremmani, Angelo G I; Trogu, Emanuela; Vigna-Taglianti, Federica; Mathis, Federica; Diecidue, Roberto; Kirchmayer, Ursula; Amato, Laura; Ghibaudi, Joli; Camposeragna, Antonella; Saponaro, Alessio; Davoli, Marina; Faggiano, Fabrizio; Maremmani, Icro

    2016-01-01

    We previously found a five cluster of psychological symptoms in heroin use disorder (HUD) patients: 'worthlessness-being trapped', 'somatic-symptoms', 'sensitivity-psychoticism', 'panic-anxiety', and 'violence-suicide'. We demonstrated that this aggregation is independent of the chosen treatment, of intoxication status and of the presence of psychiatric problems. 2314 Subjects, with alcohol, heroin or cocaine dependence were assigned to one of the five clusters. Differences between patients dependent on alcohol, heroin and cocaine in the frequency of the five clusters and in their severity were analysed. The association between the secondary abuse of alcohol and cocaine and the five clusters was also considered in the subsample of HUD patients. We confirmed a positive association of the 'somatic symptoms' dimension with the condition of heroin versus cocaine dependence and of the 'sensitivity-psychoticism' dimension with the condition of alcohol versus heroin dependence. 'Somatic symptoms' and 'panic anxiety' successfully discriminated between patients as being alcohol, heroin or cocaine dependents. Looking at the subsample of heroin dependents, no significant differences were observed. The available evidence coming from our results, taken as a whole, seems to support the extension of the psychopathological structure previously observed in opioid addicts to the population of alcohol and cocaine dependents.

  12. Monitoring Si growth on Ag(111) with scanning tunneling microscopy reveals that silicene structure involves silver atoms

    International Nuclear Information System (INIS)

    Prévot, G.; Bernard, R.; Cruguel, H.; Borensztein, Y.

    2014-01-01

    Using scanning tunneling microscopy (STM), the elaboration of the so-called silicene layer on Ag(111) is monitored in real time during Si evaporation at different temperatures. It is shown that the growth of silicene is accompanied by the release of about 65% of the surface Ag atoms from the Si covered areas. We observe that Si islands develop on the Ag terraces and Si strips at the Ag step edges, progressively forming ordered (4×4), (√(13)×√(13)) R13.9°, and dotted phases. Meanwhile, displaced Ag atoms group to develop additional bare Ag terraces growing round the Si islands from the pristine Ag step edges. This indicates a strong interaction between Si and Ag atoms, with an important modification of the Ag substrate beneath the surface layer. This observation is in contradiction with the picture of a silicene layer weakly interacting with the unreconstructed Ag substrate, and strongly indicates that the structure of silicene on Ag(111) corresponds either to a Si-Ag surface alloy or to a Si plane covered with Ag atoms

  13. New insights into the structural and functional involvement of the gate loop in AcrB export activity.

    Science.gov (United States)

    Ababou, Abdessamad

    2018-02-01

    AcrB is a major multidrug exporter in Escherichia coli and other Gram-negative bacteria. Its gate loop, located between the proximal and the distal pockets, have been reported to play important role in the export of many antibiotics. This loop location, rigidity and interactions with substrates have led recent reports to suggest that AcrB export mechanism operates in a sequential manner. First the substrate binds the proximal pocket in the access monomer, then it moves to bind the distal pocket in the binding monomer and subsequently it is extruded in the extrusion monomer. Recently, we have demonstrated that the gate loop is not required for the binding of Erythromycin but the integrity of this loop is important for an efficient export of this substrate. However, here we show that the antibiotic susceptibilities of the same AcrB gate loop mutants for Doxorubicin were unaffected, suggesting that this loop is not required for its export, and we demonstrate that this substrate may use principally the tunnel-1, located between transmembranes 8 and 9, more often than previously reported. To further explain our findings, here we address the gate loop mutations effects on AcrB solution energetics (fold, stability, molecular dynamics) and on the in vivo efflux of Erythromycin and Doxorubicin. Finally, we discuss the efflux and the discrepancy between the structural and the functional experiments for Erythromycin in these gate loop mutants. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Translocation and gross deletion breakpoints in human inherited disease and cancer II: Potential involvement of repetitive sequence elements in secondary structure formation between DNA ends.

    Science.gov (United States)

    Chuzhanova, Nadia; Abeysinghe, Shaun S; Krawczak, Michael; Cooper, David N

    2003-09-01

    Translocations and gross deletions are responsible for a significant proportion of both cancer and inherited disease. Although such gene rearrangements are nonuniformly distributed in the human genome, the underlying mutational mechanisms remain unclear. We have studied the potential involvement of various types of repetitive sequence elements in the formation of secondary structure intermediates between the single-stranded DNA ends that recombine during rearrangements. Complexity analysis was used to assess the potential of these ends to form secondary structures, the maximum decrease in complexity consequent to a gross rearrangement being used as an indicator of the type of repeat and the specific DNA ends involved. A total of 175 pairs of deletion/translocation breakpoint junction sequences available from the Gross Rearrangement Breakpoint Database [GRaBD; www.uwcm.ac.uk/uwcm/mg/grabd/grabd.html] were analyzed. Potential secondary structure was noted between the 5' flanking sequence of the first breakpoint and the 3' flanking sequence of the second breakpoint in 49% of rearrangements and between the 5' flanking sequence of the second breakpoint and the 3' flanking sequence of the first breakpoint in 36% of rearrangements. Inverted repeats, inversions of inverted repeats, and symmetric elements were found in association with gross rearrangements at approximately the same frequency. However, inverted repeats and inversions of inverted repeats accounted for the vast majority (83%) of deletions plus small insertions, symmetric elements for one-half of all antigen receptor-mediated translocations, while direct repeats appear only to be involved in mediating simple deletions. These findings extend our understanding of illegitimate recombination by highlighting the importance of secondary structure formation between single-stranded DNA ends at breakpoint junctions. Copyright 2003 Wiley-Liss, Inc.

  15. Estimation of network structure for signal propagations by the analysis of multichannel action potentials in cultured neural networks; Ta channel katsudo den`i kaiseki ni yoru baiyo shinkei kairomonai kofun denpa keiro no suitei

    Energy Technology Data Exchange (ETDEWEB)

    Konno, N.; Fukami, T.; Shiina, T. [University of Tsukuba, Tsukuba (Japan); Jinbo, Y. [Nippon Telegraph and Telephone Corp., Tokyo (Japan)

    1998-07-01

    We have fabricated a 64 embedded microelectrode-array substrate using semiconductor technology to investigate the biological signal processing in brain by using cultured neural networks of fetal rat neocortex in vitro. We analyzed temporal and spatial neural networks patterns cultured on electrode-array substrate and attempted to examine the network structure constituted by neurons and the propagating patterns of electrical activity induced by the electric stimulus. In the experiments, each microelectrode size was 30 {mu}m squared and 150{mu} m spaced. For stimulation, one of the electrodes was selected and current pulses were applied through an isolated circuit. After the network was cultured in about 50 days, responses of neurons to electric stimulus were monitored extracellularly through 64-channel electrode array. Data recorded at each electrode consist of several spike trains generated by different cells. Therefore, these trains were separated by using wavelet transform and template matching for each electrode. We referred the temporal patterns of generated spikes for each electrode to as `spike sequences`. Next, we compared With the spike sequences among multichannel data and visualized the Cultured neural networks structure by identifying the directions of propagations and cell connections. 15 refs., 9 figs.

  16. Neural crest contributions to the lamprey head

    Science.gov (United States)

    McCauley, David W.; Bronner-Fraser, Marianne

    2003-01-01

    The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.

  17. Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

    Science.gov (United States)

    Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

    2014-07-22

    Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.

  18. Enhancing action of LSD on neuronal responsiveness to serotonin in a brain structure involved in obsessive-compulsive disorder.

    Science.gov (United States)

    Zghoul, Tarek; Blier, Pierre

    2003-03-01

    Potent serotonin (5-HT) reuptake inhibitors are the only drugs that consistently exert a therapeutic action in obsessive-compulsive disorder (OCD). Given that some hallucinogens were reported to exert an anti-OCD effect outlasting their psychotomimetic action, possible modifications of neuronal responsiveness to 5-HT by LSD were examined in two rat brain structures: one associated with OCD, the orbitofrontal cortex (OFC), and another linked to depression, the hippocampus. The effects of concurrent microiontophoretic application of LSD and 5-HT were examined on neuronal firing rate in the rat OFC and hippocampus under chloral hydrate anaesthesia. In order to determine whether LSD could also exert a modification of 5-HT neuronal responsiveness upon systemic administration, after a delay when hallucinosis is presumably no longer present, it was given once daily (100 microg/kg i.p.) for 4 d and the experiments were carried out 24 h after the last dose. LSD attenuated the firing activity of OFC neurons, and enhanced the inhibitory effect of 5-HT when concomitantly ejected on the same neurons. In the hippocampus, LSD also decreased firing rate by itself but decreased the inhibitory action of 5-HT. The inhibitory action of 5-HT was significantly greater in the OFC, but smaller in the hippocampus, when examined after subacute systemic administration of LSD. It is postulated that some hallucinogens could have a beneficial action in OCD by enhancing the responsiveness to 5-HT in the OFC, and not necessarily in direct relation to hallucinosis. The latter observation may have theoretical implications for the pharmacotherapy of OCD.

  19. Structural and Molecular Mechanism of CdpR Involved in Quorum-Sensing and Bacterial Virulence in Pseudomonas aeruginosa.

    Directory of Open Access Journals (Sweden)

    Jingru Zhao

    2016-04-01

    Full Text Available Although quorum-sensing (QS systems are important regulators of virulence gene expression in the opportunistic human pathogen Pseudomonas aeruginosa, their detailed regulatory mechanisms have not been fully characterized. Here, we show that deletion of PA2588 resulted in increased production of pyocyanin and biofilm, as well as enhanced pathogenicity in a mouse model. To gain insights into the function of PA2588, we performed a ChIP-seq assay and identified 28 targets of PA2588, including the intergenic region between PA2588 and pqsH, which encodes the key synthase of Pseudomonas quinolone signal (PQS. Though the C-terminal domain was similar to DNA-binding regions of other AraC family members, structural studies revealed that PA2588 has a novel fold at the N-terminal region (NTR, and its C-terminal HTH (helix-turn-helix domain is also unique in DNA recognition. We also demonstrated that the adaptor protein ClpS, an essential regulator of ATP-dependent protease ClpAP, directly interacted with PA2588 before delivering CdpR to ClpAP for degradation. We named PA2588 as CdpR (ClpAP-degradation and pathogenicity Regulator. Moreover, deletion of clpP or clpS/clpA promotes bacterial survival in a mouse model of acute pneumonia infection. Taken together, this study uncovered that CdpR is an important QS regulator, which can interact with the ClpAS-P system to regulate the expression of virulence factors and pathogenicity.

  20. Towards a neural basis of music-evoked emotions.

    Science.gov (United States)

    Koelsch, Stefan

    2010-03-01

    Music is capable of evoking exceptionally strong emotions and of reliably affecting the mood of individuals. Functional neuroimaging and lesion studies show that music-evoked emotions can modulate activity in virtually all limbic and paralimbic brain structures. These structures are crucially involved in the initiation, generation, detection, maintenance, regulation and termination of emotions that have survival value for the individual and the species. Therefore, at least some music-evoked emotions involve the very core of evolutionarily adaptive neuroaffective mechanisms. Because dysfunctions in these structures are related to emotional disorders, a better understanding of music-evoked emotions and their neural correlates can lead to a more systematic and effective use of music in therapy. Copyright 2010 Elsevier Ltd. All rights reserved.

  1. Neural mechanisms of oculomotor abnormalities in the infantile strabismus syndrome.

    Science.gov (United States)

    Walton, Mark M G; Pallus, Adam; Fleuriet, Jérome; Mustari, Michael J; Tarczy-Hornoch, Kristina

    2017-07-01

    Infantile strabismus is characterized by numerous visual and oculomotor abnormalities. Recently nonhuman primate models of infantile strabismus have been established, with characteristics that closely match those observed in human patients. This has made it possible to study the neural basis for visual and oculomotor symptoms in infantile strabismus. In this review, we consider the available evidence for neural abnormalities in structures related to oculomotor pathways ranging from visual cortex to oculomotor nuclei. These studies provide compelling evidence that a disturbance of binocular vision during a sensitive period early in life, whatever the cause, results in a cascade of abnormalities through numerous brain areas involved in visual functions and eye movements. Copyright © 2017 the American Physiological Society.

  2. Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

    Science.gov (United States)

    Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

    2017-04-01

    This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

  3. A systematic review of the neural bases of psychotherapy for anxiety and related disorders.

    Science.gov (United States)

    Brooks, Samantha J; Stein, Dan J

    2015-09-01

    Brain imaging studies over two decades have delineated the neural circuitry of anxiety and related disorders, particularly regions involved in fear processing and in obsessive-compulsive symptoms. The neural circuitry of fear processing involves the amygdala, anterior cingulate, and insular cortex, while cortico-striatal-thalamic circuitry plays a key role in obsessive-compulsive disorder. More recently, neuroimaging studies have examined how psychotherapy for anxiety and related disorders impacts on these neural circuits. Here we conduct a systematic review of the findings of such work, which yielded 19 functional magnetic resonance imaging studies examining the neural bases of cognitive-behavioral therapy (CBT) in 509 patients with anxiety and related disorders. We conclude that, although each of these related disorders is mediated by somewhat different neural circuitry, CBT may act in a similar way to increase prefrontal control of subcortical structures. These findings are consistent with an emphasis in cognitive-affective neuroscience on the potential therapeutic value of enhancing emotional regulation in various psychiatric conditions.

  4. Small leucine rich proteoglycan family regulates multiple signalling pathways in neural development and maintenance.

    Science.gov (United States)

    Dellett, Margaret; Hu, Wanzhou; Papadaki, Vasiliki; Ohnuma, Shin-ichi

    2012-04-01

    The small leucine-rich repeat proteoglycan (SLRPs) family of proteins currently consists of five classes, based on their structural composition and chromosomal location. As biologically active components of the extracellular matrix (ECM), SLRPs were known to bind to various collagens, having a role in regulating fibril assembly, organization and degradation. More recently, as a function of their diverse proteins cores and glycosaminoglycan side chains, SLRPs have been shown to be able to bind various cell surface receptors, growth factors, cytokines and other ECM components resulting in the ability to influence various cellular functions. Their involvement in several signaling pathways such as Wnt, transforming growth factor-β and epidermal growth factor receptor also highlights their role as matricellular proteins. SLRP family members are expressed during neural development and in adult neural tissues, including ocular tissues. This review focuses on describing SLRP family members involvement in neural development with a brief summary of their role in non-neural ocular tissues and in response to neural injury. © 2012 The Authors Development, Growth & Differentiation © 2012 Japanese Society of Developmental Biologists.

  5. Neural networks with discontinuous/impact activations

    CERN Document Server

    Akhmet, Marat

    2014-01-01

    This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided. This book also: Explores questions related to the biological underpinning for models of neural networks\\ Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities Provides all necessary mathematical basics for application to the theory of neural networks Neural Networks with Discontinuous/Impact Activations is an ideal book for researchers and professionals in the field of engineering mathematics that have an interest in app...

  6. Estimation of Conditional Quantile using Neural Networks

    DEFF Research Database (Denmark)

    Kulczycki, P.; Schiøler, Henrik

    1999-01-01

    The problem of estimating conditional quantiles using neural networks is investigated here. A basic structure is developed using the methodology of kernel estimation, and a theory guaranteeing con-sistency on a mild set of assumptions is provided. The constructed structure constitutes a basis...... for the design of a variety of different neural networks, some of which are considered in detail. The task of estimating conditional quantiles is related to Bayes point estimation whereby a broad range of applications within engineering, economics and management can be suggested. Numerical results illustrating...... the capabilities of the elaborated neural network are also given....

  7. Deep Gate Recurrent Neural Network

    Science.gov (United States)

    2016-11-22

    and Fred Cummins. Learning to forget: Continual prediction with lstm . Neural computation, 12(10):2451–2471, 2000. Alex Graves. Generating sequences...DSGU) and Simple Gated Unit (SGU), which are structures for learning long-term dependencies. Compared to traditional Long Short-Term Memory ( LSTM ) and...Gated Recurrent Unit (GRU), both structures require fewer parameters and less computation time in sequence classification tasks. Unlike GRU and LSTM

  8. Antenna analysis using neural networks

    Science.gov (United States)

    Smith, William T.

    1992-01-01

    Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

  9. Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

    Science.gov (United States)

    Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

    2017-02-01

    It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

  10. Neural and psychological underpinnings of gambling disorder

    DEFF Research Database (Denmark)

    Grant, Jon E; Odlaug, Brian L; Chamberlain, Samuel R

    2016-01-01

    Gambling disorder affects 0.4 to 1.6% of adults worldwide, and is highly comorbid with other mental health disorders. This article provides a concise primer on the neural and psychological underpinnings of gambling disorder based on a selective review of the literature. Gambling disorder is assoc......Gambling disorder affects 0.4 to 1.6% of adults worldwide, and is highly comorbid with other mental health disorders. This article provides a concise primer on the neural and psychological underpinnings of gambling disorder based on a selective review of the literature. Gambling disorder...... is associated with dysfunction across multiple cognitive domains which can be considered in terms of impulsivity and compulsivity. Neuroimaging data suggest structural and functional abnormalities of networks involved in reward processing and top-down control. Gambling disorder shows 50-60% heritability...... is required to evaluate whether cognitive dysfunction and personality aspects influence the longitudinal course and treatment outcome for gambling disorder. It is hoped that improved understanding of the biological and psychological components of gambling disorder, and their interactions, may lead to improved...

  11. SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    S. K. M. Abujayyab

    2016-09-01

    Full Text Available Mapping the suitability of landfill sites is a complex field and is involved with multidiscipline. The purpose of this research is to create an ArcGIS spatial data mining toolbox for mapping the suitability of landfill sites at a regional scale using neural networks. The toolbox is constructed from six sub-tools to prepare, train, and process data. The employment of the toolbox is straightforward. The multilayer perceptron (MLP neural networks structure with a backpropagation learning algorithm is used. The dataset is mined from the north states in Malaysia. A total of 14 criteria are utilized to build the training dataset. The toolbox provides a platform for decision makers to implement neural networks for mapping the suitability of landfill sites in the ArcGIS environment. The result shows the ability of the toolbox to produce suitability maps for landfill sites.

  12. Structural and functional characterization of an orphan ATP-binding cassette ATPase involved in manganese utilization and tolerance in Leptospira spp.

    Science.gov (United States)

    Benaroudj, Nadia; Saul, Frederick; Bellalou, Jacques; Miras, Isabelle; Weber, Patrick; Bondet, Vincent; Murray, Gerald L; Adler, Ben; Ristow, Paula; Louvel, Hélène; Haouz, Ahmed; Picardeau, Mathieu

    2013-12-01

    Pathogenic Leptospira species are the etiological agents of the widespread zoonotic disease leptospirosis. Most organisms, including Leptospira, require divalent cations for proper growth, but because of their high reactivity, these metals are toxic at high concentrations. Therefore, bacteria have acquired strategies to maintain metal homeostasis, such as metal import and efflux. By screening Leptospira biflexa transposon mutants for their ability to use Mn(2+), we have identified a gene encoding a putative orphan ATP-binding cassette (ABC) ATPase of unknown function. Inactivation of this gene in both L. biflexa and L. interrogans strains led to mutants unable to grow in medium in which iron was replaced by Mn(2+), suggesting an involvement of this ABC ATPase in divalent cation uptake. A mutation in this ATPase-coding gene increased susceptibility to Mn(2+) toxicity. Recombinant ABC ATPase of the pathogen L. interrogans exhibited Mg(2+)-dependent ATPase activity involving a P-loop motif. The structure of this ATPase was solved from a crystal containing two monomers in the asymmetric unit. Each monomer adopted a canonical two-subdomain organization of the ABC ATPase fold with an α/β subdomain containing the Walker motifs and an α subdomain containing the ABC signature motif (LSSGE). The two monomers were arranged in a head-to-tail orientation, forming a V-shaped particle with all the conserved ABC motifs at the dimer interface, similar to functional ABC ATPases. These results provide the first structural and functional characterization of a leptospiral ABC ATPase.

  13. The structure of the first representative of Pfam family PF09836 reveals a two-domain organization and suggests involvement in transcriptional regulation

    International Nuclear Information System (INIS)

    Das, Debanu; Grishin, Nick V.; Kumar, Abhinav; Carlton, Dennis; Bakolitsa, Constantina; Miller, Mitchell D.; Abdubek, Polat; Astakhova, Tamara; Axelrod, Herbert L.; Burra, Prasad; Chen, Connie; Chiu, Hsiu-Ju; Chiu, Michelle; Clayton, Thomas; Deller, Marc C.; Duan, Lian; Ellrott, Kyle; Ernst, Dustin; Farr, Carol L.; Feuerhelm, Julie; Grzechnik, Anna; Grzechnik, Slawomir K.; Grant, Joanna C.; Han, Gye Won; 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; Nopakun, Amanda; Okach, Linda; Oommachen, Silvya; Paulsen, Jessica; Puckett, Christina; Reyes, Ron; Rife, Christopher L.; Sefcovic, Natasha; Tien, Henry J.; Trame, Christine B.; Bedem, Henry van den; Weekes, Dana; Wooten, Tiffany; Xu, Qingping; Hodgson, Keith O.; Wooley, John; Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wilson, Ian A.

    2009-01-01

    The crystal structure of the NGO1945 gene product from N. gonorrhoeae (UniProt Q5F5IO) reveals that the N-terminal domain assigned as a domain of unknown function (DUF2063) is likely to bind DNA and that the protein may be involved in transcriptional regulation. Proteins with the DUF2063 domain constitute a new Pfam family, PF09836. The crystal structure of a member of this family, NGO1945 from Neisseria gonorrhoeae, has been determined and reveals that the N-terminal DUF2063 domain is likely to be a DNA-binding domain. In conjunction with the rest of the protein, NGO1945 is likely to be involved in transcriptional regulation, which is consistent with genomic neighborhood analysis. Of the 216 currently known proteins that contain a DUF2063 domain, the most significant sequence homologs of NGO1945 (∼40–99% sequence identity) are from various Neisseria and Haemophilus species. As these are important human pathogens, NGO1945 represents an interesting candidate for further exploration via biochemical studies and possible therapeutic intervention

  14. Neurophysiology and neural engineering: a review.

    Science.gov (United States)

    Prochazka, Arthur

    2017-08-01

    Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

  15. Body-specific motor imagery of hand actions: neural evidence from right- and left-handers

    Directory of Open Access Journals (Sweden)

    Roel M Willems

    2009-11-01

    Full Text Available If motor imagery uses neural structures involved in action execution, then the neural correlates of imagining an action should differ between individuals who tend to execute the action differently. Here we report fMRI data showing that motor imagery is influenced by the way people habitually perform motor actions with their particular bodies; that is, motor imagery is ‘body-specific’ (Casasanto, 2009. During mental imagery for complex hand actions, activation of cortical areas involved in motor planning and execution was left-lateralized in right-handers but right-lateralized in left-handers. We conclude that motor imagery involves the generation of an action plan that is grounded in the participant’s motor habits, not just an abstract representation at the level of the action’s goal. People with different patterns of motor experience form correspondingly different neurocognitive representations of imagined actions.

  16. Optics in neural computation

    Science.gov (United States)

    Levene, Michael John

    In all attempts to emulate the considerable powers of the brain, one is struck by both its immense size, parallelism, and complexity. While the fields of neural networks, artificial intelligence, and neuromorphic engineering have all attempted oversimplifications on the considerable complexity, all three can benefit from the inherent scalability and parallelism of optics. This thesis looks at specific aspects of three modes in which optics, and particularly volume holography, can play a part in neural computation. First, holography serves as the basis of highly-parallel correlators, which are the foundation of optical neural networks. The huge input capability of optical neural networks make them most useful for image processing and image recognition and tracking. These tasks benefit from the shift invariance of optical correlators. In this thesis, I analyze the capacity of correlators, and then present several techniques for controlling the amount of shift invariance. Of particular interest is the Fresnel correlator, in which the hologram is displaced from the Fourier plane. In this case, the amount of shift invariance is limited not just by the thickness of the hologram, but by the distance of the hologram from the Fourier plane. Second, volume holography can provide the huge storage capacity and high speed, parallel read-out necessary to support large artificial intelligence systems. However, previous methods for storing data in volume holograms have relied on awkward beam-steering or on as-yet non- existent cheap, wide-bandwidth, tunable laser sources. This thesis presents a new technique, shift multiplexing, which is capable of very high densities, but which has the advantage of a very simple implementation. In shift multiplexing, the reference wave consists of a focused spot a few millimeters in front of the hologram. Multiplexing is achieved by simply translating the hologram a few tens of microns or less. This thesis describes the theory for how shift

  17. Collagen type XI alpha1 may be involved in the structural plasticity of the vertebral column in Atlantic salmon (Salmo salar L.).

    Science.gov (United States)

    Wargelius, A; Fjelldal, P G; Nordgarden, U; Grini, A; Krossøy, C; Grotmol, S; Totland, G K; Hansen, T

    2010-04-01

    Atlantic salmon (Salmo salar L.) vertebral bone displays plasticity in structure, osteoid secretion and mineralization in response to photoperiod. Other properties of the vertebral bone, such as mineral content and mechanical strength, are also associated with common malformations in farmed Atlantic salmon. The biological mechanisms that underlie these changes in bone physiology are unknown, and in order to elucidate which factors might be involved in this process, microarray assays were performed on vertebral bone of Atlantic salmon reared under natural or continuous light. Eight genes were upregulated in response to continuous light treatment, whereas only one of them was upregulated in a duplicate experiment. The transcriptionally regulated gene was predicted to code for collagen type XI alpha1, a protein known to be involved in controlling the diameter of fibrillar collagens in mammals. Furthermore, the gene was highly expressed in the vertebrae, where spatial expression was found in trabecular and compact bone osteoblasts and in the chordoblasts of the notochordal sheath. When we measured the expression level of the gene in the tissue compartments of the vertebrae, the collagen turned out to be 150 and 25 times more highly expressed in the notochord and compact bone respectively, relative to the expression in the trabecular bone. Gene expression was induced in response to continuous light, and reduced in compressed vertebrae. The downregulation in compressed vertebrae was due to reduced expression in the compact bone, while expression in the trabecular bone and the notochord was unaffected. These data support the hypothesis that this gene codes for a presumptive collagen type XI alpha1, which may be involved in the regulatory pathway leading to structural adaptation of the vertebral architecture.

  18. Neural Plasticity Associated with Hippocampal PKA-CREB and NMDA Signaling Is Involved in the Antidepressant Effect of Repeated Low Dose of Yueju Pill on Chronic Mouse Model of Learned Helplessness

    Directory of Open Access Journals (Sweden)

    Zhilu Zou

    2017-01-01

    Full Text Available Yueju pill is a traditional Chinese medicine formulated to treat syndromes of mood disorders. Here, we investigated the therapeutic effect of repeated low dose of Yueju in the animal model mimicking clinical long-term depression condition and the role of neural plasticity associated with PKA- (protein kinase A- CREB (cAMP response element binding protein and NMDA (N-methyl-D-aspartate signaling. We showed that a single low dose of Yueju demonstrated antidepressant effects in tests of tail suspension, forced swim, and novelty-suppressed feeding. A chronic learned helplessness (LH protocol resulted in a long-term depressive-like condition. Repeated administration of Yueju following chronic LH remarkably alleviated all of depressive-like symptoms measured, whereas conventional antidepressant fluoxetine only showed a minor improvement. In the hippocampus, Yueju and fluoxetine both normalized brain-derived neurotrophic factor (BDNF and PKA level. Only Yueju, not fluoxetine, rescued the deficits in CREB signaling. The chronic LH upregulated the expression of NMDA receptor subunits NR1, NR2A, and NR2B, which were all attenuated by Yueju. Furthermore, intracerebraventricular administration of NMDA blunted the antidepressant effect of Yueju. These findings supported the antidepressant efficacy of repeated routine low dose of Yueju in a long-term depression model and the critical role of CREB and NMDA signaling.

  19. Neural Plasticity Associated with Hippocampal PKA-CREB and NMDA Signaling Is Involved in the Antidepressant Effect of Repeated Low Dose of Yueju Pill on Chronic Mouse Model of Learned Helplessness.

    Science.gov (United States)

    Zou, Zhilu; Chen, Yin; Shen, Qinqin; Guo, Xiaoyan; Zhang, Yuxuan; Chen, Gang

    2017-01-01

    Yueju pill is a traditional Chinese medicine formulated to treat syndromes of mood disorders. Here, we investigated the therapeutic effect of repeated low dose of Yueju in the animal model mimicking clinical long-term depression condition and the role of neural plasticity associated with PKA- (protein kinase A-) CREB (cAMP response element binding protein) and NMDA (N-methyl-D-aspartate) signaling. We showed that a single low dose of Yueju demonstrated antidepressant effects in tests of tail suspension, forced swim, and novelty-suppressed feeding. A chronic learned helplessness (LH) protocol resulted in a long-term depressive-like condition. Repeated administration of Yueju following chronic LH remarkably alleviated all of depressive-like symptoms measured, whereas conventional antidepressant fluoxetine only showed a minor improvement. In the hippocampus, Yueju and fluoxetine both normalized brain-derived neurotrophic factor (BDNF) and PKA level. Only Yueju, not fluoxetine, rescued the deficits in CREB signaling. The chronic LH upregulated the expression of NMDA receptor subunits NR1, NR2A, and NR2B, which were all attenuated by Yueju. Furthermore, intracerebraventricular administration of NMDA blunted the antidepressant effect of Yueju. These findings supported the antidepressant efficacy of repeated routine low dose of Yueju in a long-term depression model and the critical role of CREB and NMDA signaling.

  20. Neural networks, D0, and the SSC

    International Nuclear Information System (INIS)

    Barter, C.; Cutts, D.; Hoftun, J.S.; Partridge, R.A.; Sornborger, A.T.; Johnson, C.T.; Zeller, R.T.

    1989-01-01

    We outline several exploratory studies involving neural network simulations applied to pattern recognition in high energy physics. We describe the D0 data acquisition system and a natual means by which algorithms derived from neural networks techniques may be incorporated into recently developed hardware associated with the D0 MicroVAX farm nodes. Such applications to the event filtering needed by SSC detectors look interesting. 10 refs., 11 figs

  1. Dynamic decomposition of spatiotemporal neural signals.

    Directory of Open Access Journals (Sweden)

    Luca Ambrogioni

    2017-05-01

    Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.

  2. Neural Darwinism and consciousness.

    Science.gov (United States)

    Seth, Anil K; Baars, Bernard J

    2005-03-01

    Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.

  3. Distinct pathways of neural coupling for different basic emotions.

    Science.gov (United States)

    Tettamanti, Marco; Rognoni, Elena; Cafiero, Riccardo; Costa, Tommaso; Galati, Dario; Perani, Daniela

    2012-01-16

    Emotions are complex events recruiting distributed cortical and subcortical cerebral structures, where the functional integration dynamics within the involved neural circuits in relation to the nature of the different emotions are still unknown. Using fMRI, we measured the neural responses elicited by films representing basic emotions (fear, disgust, sadness, happiness). The amygdala and the associative cortex were conjointly activated by all basic emotions. Furthermore, distinct arrays of cortical and subcortical brain regions were additionally activated by each emotion, with the exception of sadness. Such findings informed the definition of three effective connectivity models, testing for the functional integration of visual cortex and amygdala, as regions processing all emotions, with domain-specific regions, namely: i) for fear, the frontoparietal system involved in preparing adaptive motor responses; ii) for disgust, the somatosensory system, reflecting protective responses against contaminating stimuli; iii) for happiness: medial prefrontal and temporoparietal cortices involved in understanding joyful interactions. Consistently with these domain-specific models, the results of the effective connectivity analysis indicate that the amygdala is involved in distinct functional integration effects with cortical networks processing sensorimotor, somatosensory, or cognitive aspects of basic emotions. The resulting effective connectivity networks may serve to regulate motor and cognitive behavior based on the quality of the induced emotional experience. Copyright © 2011. Published by Elsevier Inc.

  4. Neural Tube Defects

    Science.gov (United States)

    Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

  5. Non-structural proteins P17 and P33 are involved in the assembly of the internal membrane-containing virus PRD1

    Energy Technology Data Exchange (ETDEWEB)

    Karttunen, Jenni; Mäntynen, Sari [Centre of Excellence in Biological Interactions, Department of Biological and Environmental Science and Nanoscience Center, University of Jyväskylä, P.O. Box 35, 40014 Jyväskylä (Finland); Ihalainen, Teemu O. [Stem Cells in Neurological Applications Group, BioMediTech, University of Tampere, Tampere (Finland); Bamford, Jaana K.H. [Centre of Excellence in Biological Interactions, Department of Biological and Environmental Science and Nanoscience Center, University of Jyväskylä, P.O. Box 35, 40014 Jyväskylä (Finland); Oksanen, Hanna M., E-mail: hanna.oksanen@helsinki.fi [Institute of Biotechnology and Department of Biosciences, University of Helsinki, Biocenter 2, P.O. Box 56 (Viikinkaari 5), FIN-00014 Helsinki (Finland)

    2015-08-15

    Bacteriophage PRD1, which has been studied intensively at the structural and functional levels, still has some gene products with unknown functions and certain aspects of the PRD1 assembly process have remained unsolved. In this study, we demonstrate that the phage-encoded non-structural proteins P17 and P33, either individually or together, complement the defect in a temperature-sensitive GroES mutant of Escherichia coli for host growth and PRD1 propagation. Confocal microscopy of fluorescent fusion proteins revealed co-localisation between P33 and P17 as well as between P33 and the host chaperonin GroEL. A fluorescence recovery after photobleaching assay demonstrated that the diffusion of the P33 fluorescent fusion protein was substantially slower in E. coli than theoretically calculated, presumably resulting from intermolecular interactions. Our results indicate that P33 and P17 function in procapsid assembly, possibly in association with the host chaperonin complex GroEL/GroES. - Highlights: • Two non-structural proteins of PRD1 are involved in the virus assembly. • P17 and P33 complement the defect in GroES of Escherichia coli. • P33 co-localises with GroEL and P17 in the bacterium. • Slow motion of P33 in the bacterium suggests association with cellular components.

  6. Structural vascular disease in Africans: performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: the SABPA study

    OpenAIRE

    Botha, J.; De Ridder, J.H.; Potgieter, J.C.; Steyn, H.S.; Malan, L.

    2013-01-01

    A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fa...

  7. Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music

    Science.gov (United States)

    Liu, Chao; Brattico, Elvira; Abu-jamous, Basel; Pereira, Carlos S.; Jacobsen, Thomas; Nandi, Asoke K.

    2017-01-01

    People can experience different emotions when listening to music. A growing number of studies have investigated the brain structures and neural connectivities associated with perceived emotions. However, very little is known about the effect of an explicit act of judgment on the neural processing of emotionally-valenced music. In this study, we adopted the novel consensus clustering paradigm, called binarisation of consensus partition matrices (Bi-CoPaM), to study whether and how the conscious aesthetic evaluation of the music would modulate brain connectivity networks related to emotion and reward processing. Participants listened to music under three conditions – one involving a non-evaluative judgment, one involving an explicit evaluative aesthetic judgment, and one involving no judgment at all (passive listening only). During non-evaluative attentive listening we obtained auditory-limbic connectivity whereas when participants were asked to decide explicitly whether they liked or disliked the music excerpt, only two clusters of intercommunicating brain regions were found: one including areas related to auditory processing and action observation, and the other comprising higher-order structures involved with visual processing. Results indicate that explicit evaluative judgment has an impact on the neural auditory-limbic connectivity during affective processing of music. PMID:29311874

  8. Parental involvement

    Directory of Open Access Journals (Sweden)

    Ezra S Simon

    2005-01-01

    Full Text Available Parent-Teacher Associations and other community groups can play a significant role in helping to establish and run refugee schools; their involvement can also help refugee adults adjust to their changed circumstances.

  9. Applications of neural network prediction of conformational states for small peptides from spectra and of fold classes

    DEFF Research Database (Denmark)

    Bohr, Henrik; Røgen, Peter; Jalkanen, Karl J.

    2001-01-01

    but already at this stage they could be compared with reasonable agreements to experiments. The neural networks are shown to be good in distinguishing the different conformers of the small alanine peptides. especially when in the gas phase. Also the task of predicting protein fold-classes, defined from line...... to construct vibrational spectra for each of the conformational states with low energy. From the spectra, neural networks could be trained to distinguish between the various states and thus be able to generate a larger set of relevant structures and their relation to secondary structures of the peptides....... The calculations were done both with solvent atoms (up to ten water molecules) and without, and hence the neural networks could be used to monitor the influence of the solvent on hydrogen bond formation. The calculations at this stage only involved very short peptide fragments of a few alanine amino acids...

  10. Neural tissue-spheres

    DEFF Research Database (Denmark)

    Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

    2007-01-01

    By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

  11. Crystal structure of heterodimeric hexaprenyl diphosphate synthase from Micrococcus luteus B-P 26 reveals that the small subunit is directly involved in the product chain length regulation.

    Science.gov (United States)

    Sasaki, Daisuke; Fujihashi, Masahiro; Okuyama, Naomi; Kobayashi, Yukiko; Noike, Motoyoshi; Koyama, Tanetoshi; Miki, Kunio

    2011-02-04

    Hexaprenyl diphosphate synthase from Micrococcus luteus B-P 26 (Ml-HexPPs) is a heterooligomeric type trans-prenyltransferase catalyzing consecutive head-to-tail condensations of three molecules of isopentenyl diphosphates (C(5)) on a farnesyl diphosphate (FPP; C(15)) to form an (all-E) hexaprenyl diphosphate (HexPP; C(30)). Ml-HexPPs is known to function as a heterodimer of two different subunits, small and large subunits called HexA and HexB, respectively. Compared with homooligomeric trans-prenyltransferases, the molecular mechanism of heterooligomeric trans-prenyltransferases is not yet clearly understood, particularly with respect to the role of the small subunits lacking the catalytic motifs conserved in most known trans-prenyltransferases. We have determined the crystal structure of Ml-HexPPs both in the substrate-free form and in complex with 7,11-dimethyl-2,6,10-dodecatrien-1-yl diphosphate ammonium salt (3-DesMe-FPP), an analog of FPP. The structure of HexB is composed of mostly antiparallel α-helices joined by connecting loops. Two aspartate-rich motifs (designated the first and second aspartate-rich motifs) and the other characteristic motifs in HexB are located around the diphosphate part of 3-DesMe-FPP. Despite the very low amino acid sequence identity and the distinct polypeptide chain lengths between HexA and HexB, the structure of HexA is quite similar to that of HexB. The aliphatic tail of 3-DesMe-FPP is accommodated in a large hydrophobic cleft starting from HexB and penetrating to the inside of HexA. These structural features suggest that HexB catalyzes the condensation reactions and that HexA is directly involved in the product chain length control in cooperation with HexB.

  12. The structure of classical swine fever virus N(pro: a novel cysteine Autoprotease and zinc-binding protein involved in subversion of type I interferon induction.

    Directory of Open Access Journals (Sweden)

    Keerthi Gottipati

    Full Text Available Pestiviruses express their genome as a single polypeptide that is subsequently cleaved into individual proteins by host- and virus-encoded proteases. The pestivirus N-terminal protease (N(pro is a cysteine autoprotease that cleaves between its own C-terminus and the N-terminus of the core protein. Due to its unique sequence and catalytic site, it forms its own cysteine protease family C53. After self-cleavage, N(pro is no longer active as a protease. The released N(pro suppresses the induction of the host's type-I interferon-α/β (IFN-α/β response. N(pro binds interferon regulatory factor-3 (IRF3, the key transcriptional activator of IFN-α/β genes, and promotes degradation of IRF3 by the proteasome, thus preventing induction of the IFN-α/β response to pestivirus infection. Here we report the crystal structures of pestivirus N(pro. N(pro is structurally distinct from other known cysteine proteases and has a novel "clam shell" fold consisting of a protease domain and a zinc-binding domain. The unique fold of N(pro allows auto-catalysis at its C-terminus and subsequently conceals the cleavage site in the active site of the protease. Although many viruses interfere with type I IFN induction by targeting the IRF3 pathway, little information is available regarding structure or mechanism of action of viral proteins that interact with IRF3. The distribution of amino acids on the surface of N(pro involved in targeting IRF3 for proteasomal degradation provides insight into the nature of N(pro's interaction with IRF3. The structures thus establish the mechanism of auto-catalysis and subsequent auto-inhibition of trans-activity of N(pro, and its role in subversion of host immune response.

  13. The eighth TNM classification system for lung cancer: A consideration based on the degree of pleural invasion and involved neighboring structures.

    Science.gov (United States)

    Sakakura, Noriaki; Mizuno, Tetsuya; Kuroda, Hiroaki; Arimura, Takaaki; Yatabe, Yasushi; Yoshimura, Kenichi; Sakao, Yukinori

    2018-04-01

    The eighth tumor-node-metastasis (TNM) classification system for lung cancer has been used since January 2017 and must be applied to an individual institution's database. We analyzed pathological stage data of 2756 patients who underwent resection of non-small-cell lung cancer, particularly in terms of the degree of visceral pleural invasion and involved neighboring structures. Few patients had stage IIA disease (103, 4%); stratification between stages IB and IIA was insufficient (p = 0.129). When T2a tumors were divided into PL1 and PL2 subgroups based on the degree of pleural invasion, there was a significant prognostic difference between the subgroups (p consideration. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Prediction of nodal involvement in primary rectal carcinoma without invasion to pelvic structures: accuracy of preoperative CT, MR, and DWIBS assessments relative to histopathologic findings.

    Directory of Open Access Journals (Sweden)

    Jun Zhou

    Full Text Available OBJECTIVE: To investigate the accuracy of preoperative computed tomography (CT, magnetic resonance (MR imaging and diffusion-weighted imaging with background body signal suppression (DWIBS in the prediction of nodal involvement in primary rectal carcinoma patients in the absence of tumor invasion into pelvic structures. METHODS AND MATERIALS: Fifty-two subjects with primary rectal cancer were preoperatively assessed by CT and MRI at 1.5 T with a phased-array coil. Preoperative lymph node staging with imaging modalities (CT, MRI, and DWIBS were compared with the final histological findings. RESULTS: The accuracy of CT, MRI, and DWIBS were 57.7%, 63.5%, and 40.4%. The accuracy of DWIBS with higher sensitivity and negative predictive value for evaluating primary rectal cancer patients was lower than that of CT and MRI. Nodal staging agreement between imaging and pathology was fairly strong for CT and MRI (Kappa value = 0.331 and 0.348, P<0.01 but was relatively weaker for DWIBS (Kappa value = 0.174, P<0.05. The accuracy was 57.7% and 59.6%, respectively, for CT and MRI when the lymph node border information was used as the criteria, and was 57.7% and 61.5%, respectively, for enhanced CT and MRI when the lymph node enhancement pattern was used as the criteria. CONCLUSION: MRI is more accurate than CT in predicting nodal involvement in primary rectal carcinoma patients in the absence of tumor invasion into pelvic structures. DWIBS has a great diagnostic value in differentiating small malignant from benign lymph nodes.

  15. Olfactory systems and neural circuits that modulate predator odor fear

    Directory of Open Access Journals (Sweden)

    Lorey K. Takahashi

    2014-03-01

    Full Text Available When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS and accessory olfactory systems (AOS detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray, paraventricular nucleus of the hypothalamus, and the medial amygdala appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal stress hormone secretion. The medial amygdala also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus appear prominently involve in predator odor fear behavior. The basolateral amygdala, medial hypothalamic nuclei, and medial prefrontal cortex are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator odors activate

  16. Olfactory systems and neural circuits that modulate predator odor fear

    Science.gov (United States)

    Takahashi, Lorey K.

    2014-01-01

    When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS) and accessory olfactory systems (AOS) detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray (DPAG), paraventricular nucleus (PVN) of the hypothalamus, and the medial amygdala (MeA) appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal (HPA) stress hormone secretion. The MeA also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus (VHC) appear prominently involved in predator odor fear behavior. The basolateral amygdala (BLA), medial hypothalamic nuclei, and medial prefrontal cortex (mPFC) are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator

  17. Neural network recognition of mammographic lesions

    International Nuclear Information System (INIS)

    Oldham, W.J.B.; Downes, P.T.; Hunter, V.

    1987-01-01

    A method for recognition of mammographic lesions through the use of neural networks is presented. Neural networks have exhibited the ability to learn the shape andinternal structure of patterns. Digitized mammograms containing circumscribed and stelate lesions were used to train a feedfoward synchronous neural network that self-organizes to stable attractor states. Encoding of data for submission to the network was accomplished by performing a fractal analysis of the digitized image. This results in scale invariant representation of the lesions. Results are discussed

  18. Molecular evolution of a peptide GPCR ligand driven by artificial neural networks.

    Directory of Open Access Journals (Sweden)

    Sebastian Bandholtz

    Full Text Available Peptide ligands of G protein-coupled receptors constitute valuable natural lead structures for the development of highly selective drugs and high-affinity tools to probe ligand-receptor interaction. Currently, pharmacological and metabolic modification of natural peptides involves either an iterative trial-and-error process based on structure-activity relationships or screening of peptide libraries that contain many structural variants of the native molecule. Here, we present a novel neural network architecture for the improvement of metabolic stability without loss of bioactivity. In this approach the peptide sequence determines the topology of the neural network and each cell corresponds one-to-one to a single amino acid of the peptide chain. Using a training set, the learning algorithm calculated weights for each cell. The resulting network calculated the fitness function in a genetic algorithm to explore the virtual space of all possible peptides. The network training was based on gradient descent techniques which rely on the efficient calculation of the gradient by back-propagation. After three consecutive cycles of sequence design by the neural network, peptide synthesis and bioassay this new approach yielded a ligand with 70fold higher metabolic stability compared to the wild type peptide without loss of the subnanomolar activity in the biological assay. Combining specialized neural networks with an exploration of the combinatorial amino acid sequence space by genetic algorithms represents a novel rational strategy for peptide design and optimization.

  19. Neural electrical activity and neural network growth.

    Science.gov (United States)

    Gafarov, F M

    2018-05-01

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. Human cytosolic glutathione-S-transferases: quantitative analysis of expression, comparative analysis of structures and inhibition strategies of isozymes involved in drug resistance.

    Science.gov (United States)

    Mohana, Krishnamoorthy; Achary, Anant

    2017-08-01

    Glutathione-S-transferase (GST) inhibition is a strategy to overcome drug resistance. Several isoforms of human GSTs are present and they are expressed in almost all the organs. Specific expression levels of GSTs in various organs are collected from the human transcriptome data and analysis of the organ-specific expression of GST isoforms is carried out. The variations in the level of expressions of GST isoforms are statistically significant. The GST expression differs in diseased conditions as reported by many investigators and some of the isoforms of GSTs are disease markers or drug targets. Structure analysis of various isoforms is carried out and literature mining has been performed to identify the differences in the active sites of the GSTs. The xenobiotic binding H site is classified into H1, H2, and H3 and the differences in the amino acid composition, the hydrophobicity and other structural features of H site of GSTs are discussed. The existing inhibition strategies are compared. The advent of rational drug design, mechanism-based inhibition strategies, availability of high-throughput screening, target specific, and selective inhibition of GST isoforms involved in drug resistance could be achieved for the reversal of drug resistance and aid in the treatment of diseases.

  1. Vascular pattern of the dentate gyrus is regulated by neural progenitors.

    Science.gov (United States)

    Pombero, Ana; Garcia-Lopez, Raquel; Estirado, Alicia; Martinez, Salvador

    2018-05-01

    Neurogenesis is a vital process that begins during early embryonic development and continues until adulthood, though in the latter case, it is restricted to the subventricular zone and the subgranular zone of the dentate gyrus (DG). In particular, the DG's neurogenic properties are structurally and functionally unique, which may be related to its singular vascular pattern. Neurogenesis and angiogenesis share molecular signals and act synergistically, supporting the concept of a neurogenic niche as a functional unit between neural precursors cells and their environment, in which the blood vessels play an important role. Whereas it is well known that vascular development controls neural proliferation in the embryonary and in the adult brain, by releasing neurotrophic factors; the potential influence of neural cells on vascular components during angiogenesis is largely unknown. We have demonstrated that the reduction of neural progenitors leads to a significant impairment of vascular development. Since VEGF is a potential regulator in the neurogenesis-angiogenesis crosstalk, we were interested in assessing the possible role of this molecule in the hippocampal neurovascular development. Our results showed that VEGF is the molecule involved in the regulation of vascular development by neural progenitor cells in the DG.

  2. Methodology of Neural Design: Applications in Microwave Engineering

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2006-06-01

    Full Text Available 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 formulated objective function. The objective function is minimized using different versions of genetic algorithms, and their mutual combinations. The verified methodology of the automated creation of accurate neural models of microwave structures, and their association with global optimization routines are the most important original features of the paper.

  3. Advanced models of neural networks nonlinear dynamics and stochasticity in biological neurons

    CERN Document Server

    Rigatos, Gerasimos G

    2015-01-01

    This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.

  4. Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

    Science.gov (United States)

    Panzeri, Stefano; Harvey, Christopher D; Piasini, Eugenio; Latham, Peter E; Fellin, Tommaso

    2017-02-08

    The two basic processes underlying perceptual decisions-how neural responses encode stimuli, and how they inform behavioral choices-have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes," have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. A novel method combining cellular neural networks and the coupled nonlinear oscillators' paradigm involving a related bifurcation analysis for robust image contrast enhancement in dynamically changing difficult visual environments

    International Nuclear Information System (INIS)

    Chedjou, Jean Chamberlain; Kyamakya, Kyandoghere

    2010-01-01

    It is well known that a machine vision-based analysis of a dynamic scene, for example in the context of advanced driver assistance systems (ADAS), does require real-time processing capabilities. Therefore, the system used must be capable of performing both robust and ultrafast analyses. Machine vision in ADAS must fulfil the above requirements when dealing with a dynamically changing visual context (i.e. driving in darkness or in a foggy environment, etc). Among the various challenges related to the analysis of a dynamic scene, this paper focuses on contrast enhancement, which is a well-known basic operation to improve the visual quality of an image (dynamic or static) suffering from poor illumination. The key objective is to develop a systematic and fundamental concept for image contrast enhancement that should be robust despite a dynamic environment and that should fulfil the real-time constraints by ensuring an ultrafast analysis. It is demonstrated that the new approach developed in this paper is capable of fulfilling the expected requirements. The proposed approach combines the good features of the 'coupled oscillators'-based signal processing paradigm with the good features of the 'cellular neural network (CNN)'-based one. The first paradigm in this combination is the 'master system' and consists of a set of coupled nonlinear ordinary differential equations (ODEs) that are (a) the so-called 'van der Pol oscillator' and (b) the so-called 'Duffing oscillator'. It is then implemented or realized on top of a 'slave system' platform consisting of a CNN-processors platform. An offline bifurcation analysis is used to find out, a priori, the windows of parameter settings in which the coupled oscillator system exhibits the best and most appropriate behaviours of interest for an optimal resulting image processing quality. In the frame of the extensive bifurcation analysis carried out, analytical formulae have been derived, which are capable of determining the various

  6. Intelligent neural network diagnostic system

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2010-01-01

    Recently, artificial neural network (ANN) has made a significant mark in the domain of diagnostic applications. Neural networks are used to implement complex non-linear mappings (functions) using simple elementary units interrelated through connections with adaptive weights. The performance of the ANN is mainly depending on their topology structure and weights. Some systems have been developed using genetic algorithm (GA) to optimize the topology of the ANN. But, they suffer from some limitations. They are : (1) The computation time requires for training the ANN several time reaching for the average weight required, (2) Slowness of GA for optimization process and (3) Fitness noise appeared in the optimization of ANN. This research suggests new issues to overcome these limitations for finding optimal neural network architectures to learn particular problems. This proposed methodology is used to develop a diagnostic neural network system. It has been applied for a 600 MW turbo-generator as a case of real complex systems. The proposed system has proved its significant performance compared to two common methods used in the diagnostic applications.

  7. Prediction of metal corrosion using feed-forward neural networks

    International Nuclear Information System (INIS)

    Mahjani, M.G.; Jalili, S.; Jafarian, M.; Jaberi, A.

    2004-01-01

    The reliable prediction of corrosion behavior for the effective control of corrosion is a fundamental requirement. Since real world corrosion never seems to involve quite the same conditions that have previously been tested, using corrosion literature does not provide the necessary answers. In order to provide a methodology for predicting corrosion in real and complex situations, artificial neural networks can be utilized. Feed-forward artificial neural network (FFANN) is an information-processing paradigm inspired by the way the densely interconnected, parallel structure of the human brain process information.The aim of the present work is to predict corrosion behavior in critical conditions, such as industrial applications, based on some laboratory experimental data. Electrochemical behavior of stainless steel in different conditions were studied, using polarization technique and Tafel curves. Back-propagation neural networks models were developed to predict the corrosion behavior. The trained networks result in predicted value in good comparison to the experimental data. They have generally been claimed to be successful in modeling the corrosion behavior. The results are presented in two tables. Table 1 gives corrosion behavior of stainless-steel as a function of pH and CuSO 4 concentration and table 2 gives corrosion behavior of stainless - steel as a function of electrode surface area and CuSO 4 concentration. (authors)

  8. Neural correlates underlying musical semantic memory.

    Science.gov (United States)

    Groussard, M; Viader, F; Landeau, B; Desgranges, B; Eustache, F; Platel, H

    2009-07-01

    Numerous functional imaging studies have examined the neural basis of semantic memory mainly using verbal and visuospatial materials. Musical material also allows an original way to explore semantic memory processes. We used PET imaging to determine the neural substrates that underlie musical semantic memory using different tasks and stimuli. The results of three PET studies revealed a greater involvement of the anterior part of the temporal lobe. Concerning clinical observations and our neuroimaging data, the musical lexicon (and most widely musical semantic memory) appears to be sustained by a temporo-prefrontal cerebral network involving right and left cerebral regions.

  9. Adaptive competitive learning neural networks

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abas

    2013-11-01

    Full Text Available In this paper, the adaptive competitive learning (ACL neural network algorithm is proposed. This neural network not only groups similar input feature vectors together but also determines the appropriate number of groups of these vectors. This algorithm uses a new proposed criterion referred to as the ACL criterion. This criterion evaluates different clustering structures produced by the ACL neural network for an input data set. Then, it selects the best clustering structure and the corresponding network architecture for this data set. The selected structure is composed of the minimum number of clusters that are compact and balanced in their sizes. The selected network architecture is efficient, in terms of its complexity, as it contains the minimum number of neurons. Synaptic weight vectors of these neurons represent well-separated, compact and balanced clusters in the input data set. The performance of the ACL algorithm is evaluated and compared with the performance of a recently proposed algorithm in the literature in clustering an input data set and determining its number of clusters. Results show that the ACL algorithm is more accurate and robust in both determining the number of clusters and allocating input feature vectors into these clusters than the other algorithm especially with data sets that are sparsely distributed.

  10. PANP is a novel O-glycosylated PILR{alpha} ligand expressed in neural tissues

    Energy Technology Data Exchange (ETDEWEB)

    Kogure, Amane [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); Shiratori, Ikuo [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Wang, Jing [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); Lanier, Lewis L. [Department of Microbiology and Immunology and the Cancer Research Institute, University of California San Francisco, San Francisco, CA 94143 (United States); Arase, Hisashi, E-mail: arase@biken.osaka-u.ac.jp [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); JST CREST, Saitama 332-0012 (Japan)

    2011-02-18

    Research highlights: {yields} A Novel molecule, PANP, was identified to be a PILR{alpha} ligand. {yields} Sialylated O-glycan structures on PANP were required for PILR{alpha} recognition. {yields} Transcription of PANP was mainly observed in neural tissues. {yields} PANP seems to be involved in immune regulation as a ligand for PILR{alpha}. -- Abstract: PILR{alpha} is an immune inhibitory receptor possessing an immunoreceptor tyrosine-based inhibitory motif (ITIM) in its cytoplasmic domain enabling it to deliver inhibitory signals. Binding of PILR{alpha} to its ligand CD99 is involved in immune regulation; however, whether there are other PILR{alpha} ligands in addition to CD99 is not known. Here, we report that a novel molecule, PILR-associating neural protein (PANP), acts as an additional ligand for PILR{alpha}. Transcription of PANP was mainly observed in neural tissues. PILR{alpha}-Ig fusion protein bound cells transfected with PANP and the transfectants stimulated PILR{alpha} reporter cells. Specific O-glycan structures on PANP were found to be required for PILR recognition of this ligand. These results suggest that PANP is involved in immune regulation as a ligand of the PILR{alpha}.

  11. Involvement of 5-HT(2) serotonergic receptors of the nucleus raphe magnus and nucleus reticularis gigantocellularis/paragigantocellularis complex neural networks in the antinociceptive phenomenon that follows the post-ictal immobility syndrome.

    Science.gov (United States)

    de Oliveira, Rithiele Cristina; de Oliveira, Ricardo; Ferreira, Célio Marcos Dos Reis; Coimbra, Norberto Cysne

    2006-09-01

    The post-ictal immobility syndrome is followed by a significant increase in the nociceptive thresholds in animals and men. In this interesting post-ictal behavioral response, endogenous opioid peptides-mediated mechanisms, as well as cholinergic-mediated antinociceptive processes, have been suggested. However, considering that many serotonergic descending pathways have been implicated in antinociceptive reactions, the aim of the present work is to investigate the involvement of 5-HT(2)-serotonergic receptor subfamily in the post-ictal antinociception. The analgesia was measured by the tail-flick test in seven or eight Wistar rats per group. Convulsions were followed by statistically significant increase in the tail-flick latencies (TFL), at least for 120 min of the post-ictal period. Male Wistar rats were submitted to stereotaxic surgery for introduction of a guide-cannula in the rhombencephalon, aiming either the nucleus raphe magnus (NRM) or the gigantocellularis complex. In independent groups of animals, these nuclei were neurochemically lesioned with a unilateral microinjection of ibotenic acid (1.0 microg/0.2 microL). The neuronal damage of either the NRM or nucleus reticularis gigantocellularis/paragigantocellularis complex decreased the post-ictal analgesia. Also, in other independent groups, central administration of ritanserin (5.0 microg/0.2 microL) or physiological saline into each of the reticular formation nuclei studied caused a statistically significant decrease in the TFL of seizing animals, as compared to controls, in all post-ictal periods studied. These results indicate that serotonin input-connected neurons of the pontine and medullarly reticular nuclei may be involved in the post-ictal analgesia.

  12. Crystal structure of the toxin Msmeg_6760, the structural homolog of Mycobacterium tuberculosis Rv2035, a novel type II toxin involved in the hypoxic response

    Energy Technology Data Exchange (ETDEWEB)

    Bajaj, R. Alexandra; Arbing, Mark A.; Shin, Annie; Cascio, Duilio; Miallau, Linda (UCLA)

    2016-11-19

    The structure of Msmeg_6760, a protein of unknown function, has been determined. Biochemical and bioinformatics analyses determined that Msmeg_6760 interacts with a protein encoded in the same operon, Msmeg_6762, and predicted that the operon is a toxin–antitoxin (TA) system. Structural comparison of Msmeg_6760 with proteins of known function suggests that Msmeg_6760 binds a hydrophobic ligand in a buried cavity lined by large hydrophobic residues. Access to this cavity could be controlled by a gate–latch mechanism. The function of the Msmeg_6760 toxin is unknown, but structure-based predictions revealed that Msmeg_6760 and Msmeg_6762 are homologous to Rv2034 and Rv2035, a predicted novel TA system involved inMycobacterium tuberculosislatency during macrophage infection. The Msmeg_6760 toxin fold has not been previously described for bacterial toxins and its unique structural features suggest that toxin activation is likely to be mediated by a novel mechanism.

  13. Grand Research Plan for Neural Circuits of Emotion and Memory--current status of neural circuit studies in China.

    Science.gov (United States)

    Zhu, Yuan-Gui; Cao, He-Qi; Dong, Er-Dan

    2013-02-01

    During recent years, major advances have been made in neuroscience, i.e., asynchronous release, three-dimensional structural data sets, saliency maps, magnesium in brain research, and new functional roles of long non-coding RNAs. Especially, the development of optogenetic technology provides access to important information about relevant neural circuits by allowing the activation of specific neurons in awake mammals and directly observing the resulting behavior. The Grand Research Plan for Neural Circuits of Emotion and Memory was launched by the National Natural Science Foundation of China. It takes emotion and memory as its main objects, making the best use of cutting-edge technologies from medical science, life science and information science. In this paper, we outline the current status of neural circuit studies in China and the technologies and methodologies being applied, as well as studies related to the impairments of emotion and memory. In this phase, we are making efforts to repair the current deficiencies by making adjustments, mainly involving four aspects of core scientific issues to investigate these circuits at multiple levels. Five research directions have been taken to solve important scientific problems while the Grand Research Plan is implemented. Future research into this area will be multimodal, incorporating a range of methods and sciences into each project. Addressing these issues will ensure a bright future, major discoveries, and a higher level of treatment for all affected by debilitating brain illnesses.

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

    NARCIS (Netherlands)

    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

  15. Artificial neural networks application for horizontal and vertical forecasting radionuclides transport

    International Nuclear Information System (INIS)

    Khil'ko, O.S.; Kovalenko, V.I.; Kundas, S.P.

    2010-01-01

    Artificial neural networks approach for horizontal and vertical radionuclide transport forecasting was proposed. Runoff factors analysis was considered. Additional artificial neural network structures for physical-chemical properties recognition were used. (authors)

  16. Identification of flap structure-specific endonuclease 1 as a factor involved in long-term memory formation of aversive learning.

    Science.gov (United States)

    Saavedra-Rodríguez, Lorena; Vázquez, Adrinel; Ortiz-Zuazaga, Humberto G; Chorna, Nataliya E; González, Fernando A; Andrés, Lissette; Rodríguez, Karen; Ramírez, Fernando; Rodríguez, Alan; Peña de Ortiz, Sandra

    2009-05-06

    We previously proposed that DNA recombination/repair processes play a role in memory formation. Here, we examined the possible role of the fen-1 gene, encoding a flap structure-specific endonuclease, in memory consolidation of conditioned taste aversion (CTA). Quantitative real-time PCR showed that amygdalar fen-1 mRNA induction was associated to the central processing of the illness experience related to CTA and to CTA itself, but not to the central processing resulting from the presentation of a novel flavor. CTA also increased expression of the Fen-1 protein in the amygdala, but not the insular cortex. In addition, double immunofluorescence analyses showed that amygdalar Fen-1 expression is mostly localized within neurons. Importantly, functional studies demonstrated that amygdalar antisense knockdown of fen-1 expression impaired consolidation, but not short-term memory, of CTA. Overall, these studies define the fen-1 endonuclease as a new DNA recombination/repair factor involved in the formation of long-term memories.

  17. Modular representation of layered neural networks.

    Science.gov (United States)

    Watanabe, Chihiro; Hiramatsu, Kaoru; Kashino, Kunio

    2018-01-01

    Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its internal representation has many nonlinear and complex parameters embedded in hierarchical layers. Therefore, it becomes important to establish a new methodology by which layered neural networks can be understood. In this paper, we propose a new method for extracting a global and simplified structure from a layered neural network. Based on network analysis, the proposed method detects communities or clusters of units with similar connection patterns. We show its effectiveness by applying it to three use cases. (1) Network decomposition: it can decompose a trained neural network into multiple small independent networks thus dividing the problem and reducing the computation time. (2) Training assessment: the appropriateness of a trained result with a given hyperparameter or randomly chosen initial parameters can be evaluated by using a modularity index. And (3) data analysis: in practical data it reveals the community structure in the input, hidden, and output layers, which serves as a clue for discovering knowledge from a trained neural network. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. The Laplacian spectrum of neural networks

    Science.gov (United States)

    de Lange, Siemon C.; de Reus, Marcel A.; van den Heuvel, Martijn P.

    2014-01-01

    The brain is a complex network of neural interactions, both at the microscopic and macroscopic level. Graph theory is well suited to examine the global network architecture of these neural networks. Many popular graph metrics, however, encode average properties of individual network elements. Complementing these “conventional” graph metrics, the eigenvalue spectrum of the normalized Laplacian describes a network's structure directly at a systems level, without referring to individual nodes or connections. In this paper, the Laplacian spectra of the macroscopic anatomical neuronal networks of the macaque and cat, and the microscopic network of the Caenorhabditis elegans were examined. Consistent with conventional graph metrics, analysis of the Laplacian spectra revealed an integrative community structure in neural brain networks. Extending previous findings of overlap of network attributes across species, similarity of the Laplacian spectra across the cat, macaque and C. elegans neural networks suggests a certain level of consistency in the overall architecture of the anatomical neural networks of these species. Our results further suggest a specific network class for neural networks, distinct from conceptual small-world and scale-free models as well as several empirical networks. PMID:24454286

  19. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

  20. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  1. Uso de incrustaciones de resina compuesta tipo onlay en molares estructuralmente comprometidos Use of onlay-type composite resin inlays in structurally involved molars

    Directory of Open Access Journals (Sweden)

    Alberto Carlos Cruz González

    2012-03-01

    contraction at large sections of material polymerized outside the dental cavity. The objective of this article was to show the use of the composite with indirect technique how an alternative to easy handle and significant clinical results with the structural involvement of molars. The article reports two cases of composite resin inlay onlay in two permanent molars structurally affected, one endodontically treated. The collection of models is performed by the arch alginate impression of the teeth selected, making silicone light casting the prepared tooth and the rest in type III dental stone to obtain a die of work on drawing up the inlay in incremental technique. The cementation process oral cavity is carried out with dual cure resin cement. To control at six months for signs of a leak or marginal jet we used air-dried syringe, explorer and periapical X-Ray. The clinical examination and radiographic analysis revealed a good performance of the restorations in the absence of mismatch or marginal pigmentation. In conclusions the use of the composite inlays in molars with structural involvement with indirect technique is an alternative to easy handle and significant clinical results.

  2. Optimal neural computations require analog processors

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).

  3. Artificial neural networks a practical course

    CERN Document Server

    da Silva, Ivan Nunes; Andrade Flauzino, Rogerio; Liboni, Luisa Helena Bartocci; dos Reis Alves, Silas Franco

    2017-01-01

    This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.

  4. Dlx proteins position the neural plate border and determine adjacent cell fates.

    Science.gov (United States)

    Woda, Juliana M; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

    2003-01-01

    The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates.

  5. Effects of selective serotonin reuptake inhibition on neural activity related to risky decisions and monetary rewards in healthy males

    DEFF Research Database (Denmark)

    Macoveanu, Julian; Fisher, Patrick M; Haahr, Mette E

    2014-01-01

    the involvement of the normally functioning 5HT-system in decision-making under risk and processing of monetary rewards. The data suggest that prolonged SSRI treatment might reduce emotional engagement by reducing the impact of risk during decision-making or the impact of reward during outcome evaluation....... to placebo, the SSRI intervention did not alter individual risk-choice preferences, but modified neural activity during decision-making and reward processing: During the choice phase, SSRI reduced the neural response to increasing risk in lateral orbitofrontal cortex, a key structure for value-based decision-making...... functional MRI (fMRI) to investigate how a three-week fluoxetine intervention influences neural activity related to risk taking and reward processing. Employing a double-blinded parallel-group design, 29 healthy young males were randomly assigned to receive 3 weeks of a daily dose of 40 mg fluoxetine...

  6. Role of SDF1/CXCR4 Interaction in Experimental Hemiplegic Models with Neural Cell Transplantation

    Directory of Open Access Journals (Sweden)

    Noboru Suzuki

    2012-02-01

    Full Text Available Much attention has been focused on neural cell transplantation because of its promising clinical applications. We have reported that embryonic stem (ES cell derived neural stem/progenitor cell transplantation significantly improved motor functions in a hemiplegic mouse model. It is important to understand the molecular mechanisms governing neural regeneration of the damaged motor cortex after the transplantation. Recent investigations disclosed that chemokines participated in the regulation of migration and maturation of neural cell grafts. In this review, we summarize the involvement of inflammatory chemokines including stromal cell derived factor 1 (SDF1 in neural regeneration after ES cell derived neural stem/progenitor cell transplantation in mouse stroke models.

  7. Recent Advances in Neural Recording Microsystems

    Directory of Open Access Journals (Sweden)

    Benoit Gosselin

    2011-04-01

    Full Text Available The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

  8. Neural Networks: Implementations and Applications

    OpenAIRE

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  9. Computational modeling of neural plasticity for self-organization of neural networks.

    Science.gov (United States)

    Chrol-Cannon, Joseph; Jin, Yaochu

    2014-11-01

    Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  10. Neural activity in the prelimbic and infralimbic cortices of freely moving rats during social interaction: Effect of isolation rearing

    Science.gov (United States)

    Minami, Chihiro; Shimizu, Tomoko

    2017-01-01

    Sociability promotes a sound daily life for individuals. Reduced sociability is a central symptom of various neuropsychiatric disorders, and yet the neural mechanisms underlying reduced sociability remain unclear. The prelimbic cortex (PL) and infralimbic cortex (IL) have been suggested to play an important role in the neural mechanisms underlying sociability because isolation rearing in rats results in impairment of social behavior and struct