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Sample records for overlapping network module

  1. Network module detection: Affinity search technique with the multi-node topological overlap measure.

    Li, Ai; Horvath, Steve

    2009-07-20

    Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

  2. Semantic integration to identify overlapping functional modules in protein interaction networks

    Ramanathan Murali

    2007-07-01

    Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

  3. Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

    István A Kovács

    Full Text Available BACKGROUND: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1 determine persvasively overlapping modules with high resolution; (2 uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3 allow the determination of key network nodes and (4 help to predict network dynamics. CONCLUSIONS/SIGNIFICANCE: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

  4. Directed network modules

    Palla, Gergely; Farkas, Illes J; Pollner, Peter; Derenyi, Imre; Vicsek, Tamas

    2007-01-01

    A search technique locating network modules, i.e. internally densely connected groups of nodes in directed networks is introduced by extending the clique percolation method originally proposed for undirected networks. After giving a suitable definition for directed modules we investigate their percolation transition in the Erdos-Renyi graph both analytically and numerically. We also analyse four real-world directed networks, including Google's own web-pages, an email network, a word association graph and the transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The obtained directed modules are validated by additional information available for the nodes. We find that directed modules of real-world graphs inherently overlap and the investigated networks can be classified into two major groups in terms of the overlaps between the modules. Accordingly, in the word-association network and Google's web-pages, overlaps are likely to contain in-hubs, whereas the modules in the email and transcriptional regulatory network tend to overlap via out-hubs

  5. Finding overlapping communities in multilayer networks.

    Liu, Weiyi; Suzumura, Toyotaro; Ji, Hongyu; Hu, Guangmin

    2018-01-01

    Finding communities in multilayer networks is a vital step in understanding the structure and dynamics of these layers, where each layer represents a particular type of relationship between nodes in the natural world. However, most community discovery methods for multilayer networks may ignore the interplay between layers or the unique topological structure in a layer. Moreover, most of them can only detect non-overlapping communities. In this paper, we propose a new community discovery method for multilayer networks, which leverages the interplay between layers and the unique topology in a layer to reveal overlapping communities. Through a comprehensive analysis of edge behaviors within and across layers, we first calculate the similarities for edges from the same layer and the cross layers. Then, by leveraging these similarities, we can construct a dendrogram for the multilayer networks that takes both the unique topological structure and the important interplay into consideration. Finally, by introducing a new community density metric for multilayer networks, we can cut the dendrogram to get the overlapping communities for these layers. By applying our method on both synthetic and real-world datasets, we demonstrate that our method has an accurate performance in discovering overlapping communities in multilayer networks.

  6. Weighted network modules

    Farkas, Illes; Abel, Daniel; Palla, Gergely; Vicsek, Tamas

    2007-01-01

    The inclusion of link weights into the analysis of network properties allows a deeper insight into the (often overlapping) modular structure of real-world webs. We introduce a clustering algorithm clique percolation method with weights (CPMw) for weighted networks based on the concept of percolating k-cliques with high enough intensity. The algorithm allows overlaps between the modules. First, we give detailed analytical and numerical results about the critical point of weighted k-clique percolation on (weighted) Erdos-Renyi graphs. Then, for a scientist collaboration web and a stock correlation graph we compute three-link weight correlations and with the CPMw the weighted modules. After reshuffling link weights in both networks and computing the same quantities for the randomized control graphs as well, we show that groups of three or more strong links prefer to cluster together in both original graphs

  7. Epidemics in partially overlapped multiplex networks.

    Camila Buono

    Full Text Available Many real networks exhibit a layered structure in which links in each layer reflect the function of nodes on different environments. These multiple types of links are usually represented by a multiplex network in which each layer has a different topology. In real-world networks, however, not all nodes are present on every layer. To generate a more realistic scenario, we use a generalized multiplex network and assume that only a fraction [Formula: see text] of the nodes are shared by the layers. We develop a theoretical framework for a branching process to describe the spread of an epidemic on these partially overlapped multiplex networks. This allows us to obtain the fraction of infected individuals as a function of the effective probability that the disease will be transmitted [Formula: see text]. We also theoretically determine the dependence of the epidemic threshold on the fraction [Formula: see text] of shared nodes in a system composed of two layers. We find that in the limit of [Formula: see text] the threshold is dominated by the layer with the smaller isolated threshold. Although a system of two completely isolated networks is nearly indistinguishable from a system of two networks that share just a few nodes, we find that the presence of these few shared nodes causes the epidemic threshold of the isolated network with the lower propagating capacity to change discontinuously and to acquire the threshold of the other network.

  8. Epidemic spreading on complex networks with overlapping and non-overlapping community structure

    Shang, Jiaxing; Liu, Lianchen; Li, Xin; Xie, Feng; Wu, Cheng

    2015-02-01

    Many real-world networks exhibit community structure where vertices belong to one or more communities. Recent studies show that community structure plays an import role in epidemic spreading. In this paper, we investigate how the extent of overlap among communities affects epidemics. In order to experiment on the characteristic of overlapping communities, we propose a rewiring algorithm that can change the community structure from overlapping to non-overlapping while maintaining the degree distribution of the network. We simulate the Susceptible-Infected-Susceptible (SIS) epidemic process on synthetic scale-free networks and real-world networks by applying our rewiring algorithm. Experiments show that epidemics spread faster on networks with higher level of overlapping communities. Furthermore, overlapping communities' effect interacts with the average degree's effect. Our work further illustrates the important role of overlapping communities in the process of epidemic spreading.

  9. Detecting the overlapping and hierarchical community structure in complex networks

    Lancichinetti, Andrea; Fortunato, Santo; Kertesz, Janos

    2009-01-01

    Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other. Uncovering this community structure is one of the most important problems in the field of complex networks. Networks often show a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities. Here, we present the first algorithm that finds both overlapping communities and the hierarchical structure. The method is based on the local optimization of a fitness function. Community structure is revealed by peaks in the fitness histogram. The resolution can be tuned by a parameter enabling different hierarchical levels of organization to be investigated. Tests on real and artificial networks give excellent results.

  10. Link overlap, viability, and mutual percolation in multiplex networks

    Min, Byungjoon; Lee, Sangchul; Lee, Kyu-Min; Goh, K.-I.

    2015-01-01

    Many real-world complex systems are best modeled by multiplex networks. The multiplexity has proved to have broad impact on the system’s structure and function. Most theoretical studies on multiplex networks to date, however, have largely ignored the effect of the link overlap across layers despite strong empirical evidences for its significance. In this article, we investigate the effect of the link overlap in the viability of multiplex networks, both analytically and numerically. After a short recap of the original multiplex viability study, the distinctive role of overlapping links in viability and mutual connectivity is emphasized and exploited for setting up a proper analytic framework. A rich phase diagram for viability is obtained and greatly diversified patterns of hysteretic behavior in viability are observed in the presence of link overlap. Mutual percolation with link overlap is revisited as a limit of multiplex viability problem, and the controversy between existing results is clarified. The distinctive role of overlapping links is further demonstrated by the different responses of networks under random removals of overlapping and non-overlapping links, respectively, as well as under several link-removal strategies. Our results show that the link overlap facilitates the viability and mutual percolation; at the same time, the presence of link overlap poses a challenge in analytical approaches to the problem

  11. Overlapping community detection in weighted networks via a Bayesian approach

    Chen, Yi; Wang, Xiaolong; Xiang, Xin; Tang, Buzhou; Chen, Qingcai; Fan, Shixi; Bu, Junzhao

    2017-02-01

    Complex networks as a powerful way to represent complex systems have been widely studied during the past several years. One of the most important tasks of complex network analysis is to detect communities embedded in networks. In the real world, weighted networks are very common and may contain overlapping communities where a node is allowed to belong to multiple communities. In this paper, we propose a novel Bayesian approach, called the Bayesian mixture network (BMN) model, to detect overlapping communities in weighted networks. The advantages of our method are (i) providing soft-partition solutions in weighted networks; (ii) providing soft memberships, which quantify 'how strongly' a node belongs to a community. Experiments on a large number of real and synthetic networks show that our model has the ability in detecting overlapping communities in weighted networks and is competitive with other state-of-the-art models at shedding light on community partition.

  12. Overlapping community detection in networks with positive and negative links

    Chen, Y; Wang, X L; Yuan, B; Tang, B Z

    2014-01-01

    Complex networks considering both positive and negative links have gained considerable attention during the past several years. Community detection is one of the main challenges for complex network analysis. Most of the existing algorithms for community detection in a signed network aim at providing a hard-partition of the network where any node should belong to a community or not. However, they cannot detect overlapping communities where a node is allowed to belong to multiple communities. The overlapping communities widely exist in many real-world networks. In this paper, we propose a signed probabilistic mixture (SPM) model for overlapping community detection in signed networks. Compared with the existing models, the advantages of our methodology are (i) providing soft-partition solutions for signed networks; (ii) providing soft memberships of nodes. Experiments on a number of signed networks show that our SPM model: (i) can identify assortative structures or disassortative structures as the same as other state-of-the-art models; (ii) can detect overlapping communities; (iii) outperforms other state-of-the-art models at shedding light on the community detection in synthetic signed networks. (paper)

  13. Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

    Zhao Yi

    2010-12-01

    Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

  14. Overlapping coalition formation games in wireless communication networks

    Wang, Tianyu; Saad, Walid; Han, Zhu

    2017-01-01

    This brief introduces overlapping coalition formation games (OCF games), a novel mathematical framework from cooperative game theory that can be used to model, design and analyze cooperative scenarios in future wireless communication networks. The concepts of OCF games are explained, and several algorithmic aspects are studied. In addition, several major application scenarios are discussed. These applications are drawn from a variety of fields that include radio resource allocation in dense wireless networks, cooperative spectrum sensing for cognitive radio networks, and resource management for crowd sourcing. For each application, the use of OCF games is discussed in detail in order to show how this framework can be used to solve relevant wireless networking problems. Overlapping Coalition Formation Games in Wireless Communication Networks provides researchers, students and practitioners with a concise overview of existing works in this emerging area, exploring the relevant fundamental theories, key techniqu...

  15. Architecture and dynamics of overlapped RNA regulatory networks.

    Lapointe, Christopher P; Preston, Melanie A; Wilinski, Daniel; Saunders, Harriet A J; Campbell, Zachary T; Wickens, Marvin

    2017-11-01

    A single protein can bind and regulate many mRNAs. Multiple proteins with similar specificities often bind and control overlapping sets of mRNAs. Yet little is known about the architecture or dynamics of overlapped networks. We focused on three proteins with similar structures and related RNA-binding specificities-Puf3p, Puf4p, and Puf5p of S. cerevisiae Using RNA Tagging, we identified a "super-network" comprised of four subnetworks: Puf3p, Puf4p, and Puf5p subnetworks, and one controlled by both Puf4p and Puf5p. The architecture of individual subnetworks, and thus the super-network, is determined by competition among particular PUF proteins to bind mRNAs, their affinities for binding elements, and the abundances of the proteins. The super-network responds dramatically: The remaining network can either expand or contract. These strikingly opposite outcomes are determined by an interplay between the relative abundance of the RNAs and proteins, and their affinities for one another. The diverse interplay between overlapping RNA-protein networks provides versatile opportunities for regulation and evolution. © 2017 Lapointe et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  16. A model for evolution of overlapping community networks

    Karan, Rituraj; Biswal, Bibhu

    2017-05-01

    A model is proposed for the evolution of network topology in social networks with overlapping community structure. Starting from an initial community structure that is defined in terms of group affiliations, the model postulates that the subsequent growth and loss of connections is similar to the Hebbian learning and unlearning in the brain and is governed by two dominant factors: the strength and frequency of interaction between the members, and the degree of overlap between different communities. The temporal evolution from an initial community structure to the current network topology can be described based on these two parameters. It is possible to quantify the growth occurred so far and predict the final stationary state to which the network is likely to evolve. Applications in epidemiology or the spread of email virus in a computer network as well as finding specific target nodes to control it are envisaged. While facing the challenge of collecting and analyzing large-scale time-resolved data on social groups and communities one faces the most basic questions: how do communities evolve in time? This work aims to address this issue by developing a mathematical model for the evolution of community networks and studying it through computer simulation.

  17. Statistically validated network of portfolio overlaps and systemic risk.

    Gualdi, Stanislao; Cimini, Giulio; Primicerio, Kevin; Di Clemente, Riccardo; Challet, Damien

    2016-12-21

    Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007-2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains).

  18. Intensity-modulated radiation therapy: overlapping co-axial modulated fields

    Metcalfe, P; Tangboonduangjit, P; White, P

    2004-01-01

    The Varian multi-leaf collimator has a 14.5 cm leaf extension limit from each carriage. This means the target volumes in the head and neck region are sometimes too wide for standard width-modulated fields to provide adequate dose coverage. A solution is to set up asymmetric co-axial overlapping fields. This protects the MLC carriage while in return the MLC provides modulated dose blending in the field overlap region. Planar dose maps for coincident fields from the Pinnacle radiotherapy treatment planning system are compared with planar dose maps reconstructed from radiographic film and electronic portal images. The film and portal images show small leaf-jaw matchlines at each field overlap border. Linear profiles taken across each image show that the observed leaf-jaw matchlines from the accelerator images are not accounted for by the treatment planning system. Dose difference between film reconstructed electronic portal images and planning system are about 2.5 cGy in a modulated field at d max . While the magnitude of the dose differences are small improved round end leaf modelling combined with a finer dose calculation grid may minimize the discrepancy between calculated and delivered dose

  19. Partially Overlapping Ownership and Contagion in Financial Networks

    Micah Pollak

    2017-01-01

    Full Text Available Using historical banking data for the United States from the years 2000 to 2015 we characterize the probability and extent of a financial contagion using a calibrated network model of heterogeneous interbank exposures. Both the probability and the average extent of a contagion begin to rise in 2007 prior to the US financial crisis. Including a common asset in the model increases both the probability and extent of contagion, especially during the years of the financial crisis. Based on rising institutional ownership in the banking industry, we introduce a partially overlapping ownership asset that devalues endogenously. The addition of this asset increases the extent of a financial contagion. Our results show that trends in capital buffers and the distribution and type of assets have a significant effect on the predictions of financial network contagion models and that the rising trend in ownership of banks by banks amplifies shocks to the financial system.

  20. Partially Overlapping Brain Networks for Singing and Cello Playing

    Melanie Segado

    2018-05-01

    Full Text Available This research uses an MR-Compatible cello to compare functional brain activation during singing and cello playing within the same individuals to determine the extent to which arbitrary auditory-motor associations, like those required to play the cello, co-opt functional brain networks that evolved for singing. Musical instrument playing and singing both require highly specific associations between sounds and movements. Because these are both used to produce musical sounds, it is often assumed in the literature that their neural underpinnings are highly similar. However, singing is an evolutionarily old human trait, and the auditory-motor associations used for singing are also used for speech and non-speech vocalizations. This sets it apart from the arbitrary auditory-motor associations required to play musical instruments. The pitch range of the cello is similar to that of the human voice, but cello playing is completely independent of the vocal apparatus, and can therefore be used to dissociate the auditory-vocal network from that of the auditory-motor network. While in the MR-Scanner, 11 expert cellists listened to and subsequently produced individual tones either by singing or cello playing. All participants were able to sing and play the target tones in tune (<50C deviation from target. We found that brain activity during cello playing directly overlaps with brain activity during singing in many areas within the auditory-vocal network. These include primary motor, dorsal pre-motor, and supplementary motor cortices (M1, dPMC, SMA,the primary and periprimary auditory cortices within the superior temporal gyrus (STG including Heschl's gyrus, anterior insula (aINS, anterior cingulate cortex (ACC, and intraparietal sulcus (IPS, and Cerebellum but, notably, exclude the periaqueductal gray (PAG and basal ganglia (Putamen. Second, we found that activity within the overlapping areas is positively correlated with, and therefore likely contributing to

  1. Partially Overlapping Brain Networks for Singing and Cello Playing.

    Segado, Melanie; Hollinger, Avrum; Thibodeau, Joseph; Penhune, Virginia; Zatorre, Robert J

    2018-01-01

    This research uses an MR-Compatible cello to compare functional brain activation during singing and cello playing within the same individuals to determine the extent to which arbitrary auditory-motor associations, like those required to play the cello, co-opt functional brain networks that evolved for singing. Musical instrument playing and singing both require highly specific associations between sounds and movements. Because these are both used to produce musical sounds, it is often assumed in the literature that their neural underpinnings are highly similar. However, singing is an evolutionarily old human trait, and the auditory-motor associations used for singing are also used for speech and non-speech vocalizations. This sets it apart from the arbitrary auditory-motor associations required to play musical instruments. The pitch range of the cello is similar to that of the human voice, but cello playing is completely independent of the vocal apparatus, and can therefore be used to dissociate the auditory-vocal network from that of the auditory-motor network. While in the MR-Scanner, 11 expert cellists listened to and subsequently produced individual tones either by singing or cello playing. All participants were able to sing and play the target tones in tune (singing in many areas within the auditory-vocal network. These include primary motor, dorsal pre-motor, and supplementary motor cortices (M1, dPMC, SMA),the primary and periprimary auditory cortices within the superior temporal gyrus (STG) including Heschl's gyrus, anterior insula (aINS), anterior cingulate cortex (ACC), and intraparietal sulcus (IPS), and Cerebellum but, notably, exclude the periaqueductal gray (PAG) and basal ganglia (Putamen). Second, we found that activity within the overlapping areas is positively correlated with, and therefore likely contributing to, both singing and playing in tune determined with performance measures. Third, we found that activity in auditory areas is functionally

  2. The overlapping community structure of structural brain network in young healthy individuals.

    Kai Wu

    2011-05-01

    Full Text Available Community structure is a universal and significant feature of many complex networks in biology, society, and economics. Community structure has also been revealed in human brain structural and functional networks in previous studies. However, communities overlap and share many edges and nodes. Uncovering the overlapping community structure of complex networks remains largely unknown in human brain networks. Here, using regional gray matter volume, we investigated the structural brain network among 90 brain regions (according to a predefined anatomical atlas in 462 young, healthy individuals. Overlapped nodes between communities were defined by assuming that nodes (brain regions can belong to more than one community. We demonstrated that 90 brain regions were organized into 5 overlapping communities associated with several well-known brain systems, such as the auditory/language, visuospatial, emotion, decision-making, social, control of action, memory/learning, and visual systems. The overlapped nodes were mostly involved in an inferior-posterior pattern and were primarily related to auditory and visual perception. The overlapped nodes were mainly attributed to brain regions with higher node degrees and nodal efficiency and played a pivotal role in the flow of information through the structural brain network. Our results revealed fuzzy boundaries between communities by identifying overlapped nodes and provided new insights into the understanding of the relationship between the structure and function of the human brain. This study provides the first report of the overlapping community structure of the structural network of the human brain.

  3. Rhythmic Components in Extracranial Brain Signals Reveal Multifaceted Task Modulation of Overlapping Neuronal Activity.

    Roemer van der Meij

    Full Text Available Oscillatory neuronal activity is implicated in many cognitive functions, and its phase coupling between sensors may reflect networks of communicating neuronal populations. Oscillatory activity is often studied using extracranial recordings and compared between experimental conditions. This is challenging, because there is overlap between sensor-level activity generated by different sources, and this can obscure differential experimental modulations of these sources. Additionally, in extracranial data, sensor-level phase coupling not only reflects communicating populations, but can also be generated by a current dipole, whose sensor-level phase coupling does not reflect source-level interactions. We present a novel method, which is capable of separating and characterizing sources on the basis of their phase coupling patterns as a function of space, frequency and time (trials. Importantly, this method depends on a plausible model of a neurobiological rhythm. We present this model and an accompanying analysis pipeline. Next, we demonstrate our approach, using magnetoencephalographic (MEG recordings during a cued tactile detection task as a case study. We show that the extracted components have overlapping spatial maps and frequency content, which are difficult to resolve using conventional pairwise measures. Because our decomposition also provides trial loadings, components can be readily contrasted between experimental conditions. Strikingly, we observed heterogeneity in alpha and beta sources with respect to whether their activity was suppressed or enhanced as a function of attention and performance, and this happened both in task relevant and irrelevant regions. This heterogeneity contrasts with the common view that alpha and beta amplitude over sensory areas are always negatively related to attention and performance.

  4. Efficient inference of overlapping communities in complex networks

    Fruergaard, Bjarne Ørum; Herlau, Tue

    2014-01-01

    We discuss two views on extending existing methods for complex network modeling which we dub the communities first and the networks first view, respectively. Inspired by the networks first view that we attribute to White, Boorman, and Breiger (1976)[1], we formulate the multiple-networks stochastic...

  5. Research on Some Bus Transport Networks with Random Overlapping Clique Structure

    Yang Xuhua; Sun Youxian; Wang Bo; Wang Wanliang

    2008-01-01

    On the basis of investigating the statistical data of bus transport networks of three big cities in China, we propose that each bus route is a clique (maximal complete subgraph) and a bus transport network (BTN) consists of a lot of cliques, which intensively connect and overlap with each other. We study the network properties, which include the degree distribution, multiple edges' overlapping time distribution, distribution of the overlap size between any two overlapping cliques, distribution of the number of cliques that a node belongs to. Naturally, the cliques also constitute a network, with the overlapping nodes being their multiple links. We also research its network properties such as degree distribution, clustering, average path length, and so on. We propose that a BTN has the properties of random clique increment and random overlapping clique, at the same time, a BTN is a small-world network with highly clique-clustered and highly clique-overlapped. Finally, we introduce a BTN evolution model, whose simulation results agree well with the statistical laws that emerge in real BTNs

  6. Phase modulated 2D HSQC-TOCSY for unambiguous assignment of overlapping spin systems

    Singh, Amrinder; Dubey, Abhinav; Adiga, Satish K.; Atreya, Hanudatta S.

    2018-01-01

    We present a new method that allows one to unambiguously resolve overlapping spin systems often encountered in biomolecular systems such as peptides and proteins or in samples containing a mixture of different molecules such as in metabolomics. We address this problem using the recently proposed phase modulation approach. By evolving the 1H chemical shifts in a conventional two dimensional (2D) HSQC-TOCSY experiment for a fixed delay period, the phase/intensity of set of cross peaks belonging to one spin system are modulated differentially relative to those of its overlapping counterpart, resulting in their discrimination and recognition. The method thus accelerates the process of identification and resonance assignment of individual compounds in complex mixtures. This approach facilitated the assignment of molecules in the embryo culture medium used in human assisted reproductive technology.

  7. An Overlapping Communities Detection Algorithm via Maxing Modularity in Opportunistic Networks

    Gao Zhi-Peng

    2016-01-01

    Full Text Available Community detection in opportunistic networks has been a significant and hot issue, which is used to understand characteristics of networks through analyzing structure of it. Community is used to represent a group of nodes in a network where nodes inside the community have more internal connections than external connections. However, most of the existing community detection algorithms focus on binary networks or disjoint community detection. In this paper, we propose a novel algorithm via maxing modularity of communities (MMCto find overlapping community structure in opportunistic networks. It utilizes contact history of nodes to calculate the relation intensity between nodes. It finds nodes with high relation intensity as the initial community and extend the community with nodes of higher belong degree. The algorithm achieves a rapid and efficient overlapping community detection method by maxing the modularity of community continuously. The experiments prove that MMC is effective for uncovering overlapping communities and it achieves better performance than COPRA and Conductance.

  8. Detecting overlapping community structure of networks based on vertex–vertex correlations

    Zarei, Mina; Izadi, Dena; Samani, Keivan Aghababaei

    2009-01-01

    Using the NMF (non-negative matrix factorization) method, the structure of overlapping communities in complex networks is investigated. For the feature matrix of the NMF method we introduce a vertex–vertex correlation matrix. The method is applied to some computer-generated and real-world networks. Simulations show that this feature matrix gives more reasonable results

  9. Eigenspaces of networks reveal the overlapping and hierarchical community structure more precisely

    Ma, Xiaoke; Gao, Lin; Yong, Xuerong

    2010-01-01

    Identifying community structure is fundamental for revealing the structure–functionality relationship in complex networks, and spectral algorithms have been shown to be powerful for this purpose. In a traditional spectral algorithm, each vertex of a network is embedded into a spectral space by making use of the eigenvectors of the adjacency matrix or Laplacian matrix of the graph. In this paper, a novel spectral approach for revealing the overlapping and hierarchical community structure of complex networks is proposed by not only using the eigenvalues and eigenvectors but also the properties of eigenspaces of the networks involved. This gives us a better characterization of community. We first show that the communicability between a pair of vertices can be rewritten in term of eigenspaces of a network. An agglomerative clustering algorithm is then presented to discover the hierarchical communities using the communicability matrix. Finally, these overlapping vertices are discovered with the corresponding eigenspaces, based on the fact that the vertices more densely connected amongst one another are more likely to be linked through short cycles. Compared with the traditional spectral algorithms, our algorithm can identify both the overlapping and hierarchical community without increasing the time complexity O(n 3 ), where n is the size of the network. Furthermore, our algorithm can also distinguish the overlapping vertices from bridges. The method is tested by applying it to some computer-generated and real-world networks. The experimental results indicate that our algorithm can reveal community structure more precisely than the traditional spectral approaches

  10. A Markov random walk under constraint for discovering overlapping communities in complex networks

    Jin, Di; Yang, Bo; Liu, Dayou; He, Dongxiao; Liu, Jie; Baquero, Carlos

    2011-01-01

    The detection of overlapping communities in complex networks has motivated recent research in relevant fields. Aiming to address this problem, we propose a Markov-dynamics-based algorithm, called UEOC, which means 'unfold and extract overlapping communities'. In UEOC, when identifying each natural community that overlaps, a Markov random walk method combined with a constraint strategy, which is based on the corresponding annealed network (degree conserving random network), is performed to unfold the community. Then, a cutoff criterion with the aid of a local community function, called conductance, which can be thought of as the ratio between the number of edges inside the community and those leaving it, is presented to extract this emerged community from the entire network. The UEOC algorithm depends on only one parameter whose value can be easily set, and it requires no prior knowledge of the hidden community structures. The proposed UEOC has been evaluated both on synthetic benchmarks and on some real-world networks, and has been compared with a set of competing algorithms. The experimental result has shown that UEOC is highly effective and efficient for discovering overlapping communities

  11. Exploring overlapping functional units with various structure in protein interaction networks.

    Xiao-Fei Zhang

    Full Text Available Revealing functional units in protein-protein interaction (PPI networks are important for understanding cellular functional organization. Current algorithms for identifying functional units mainly focus on cohesive protein complexes which have more internal interactions than external interactions. Most of these approaches do not handle overlaps among complexes since they usually allow a protein to belong to only one complex. Moreover, recent studies have shown that other non-cohesive structural functional units beyond complexes also exist in PPI networks. Thus previous algorithms that just focus on non-overlapping cohesive complexes are not able to present the biological reality fully. Here, we develop a new regularized sparse random graph model (RSRGM to explore overlapping and various structural functional units in PPI networks. RSRGM is principally dominated by two model parameters. One is used to define the functional units as groups of proteins that have similar patterns of connections to others, which allows RSRGM to detect non-cohesive structural functional units. The other one is used to represent the degree of proteins belonging to the units, which supports a protein belonging to more than one revealed unit. We also propose a regularizer to control the smoothness between the estimators of these two parameters. Experimental results on four S. cerevisiae PPI networks show that the performance of RSRGM on detecting cohesive complexes and overlapping complexes is superior to that of previous competing algorithms. Moreover, RSRGM has the ability to discover biological significant functional units besides complexes.

  12. Relative camera localisation in non-overlapping camera networks using multiple trajectories

    John, V.; Englebienne, G.; Kröse, B.J.A.

    2012-01-01

    In this article we present an automatic camera calibration algorithm using multiple trajectories in a multiple camera network with non-overlapping field-of-views (FOV). Visible trajectories within a camera FOV are assumed to be measured with respect to the camera local co-ordinate system.

  13. Functional Module Analysis for Gene Coexpression Networks with Network Integration.

    Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

  14. A game theoretic algorithm to detect overlapping community structure in networks

    Zhou, Xu; Zhao, Xiaohui; Liu, Yanheng; Sun, Geng

    2018-04-01

    Community detection can be used as an important technique for product and personalized service recommendation. A game theory based approach to detect overlapping community structure is introduced in this paper. The process of the community formation is converted into a game, when all agents (nodes) cannot improve their own utility, the game process will be terminated. The utility function is composed of a gain and a loss function and we present a new gain function in this paper. In addition, different from choosing action randomly among join, quit and switch for each agent to get new label, two new strategies for each agent to update its label are designed during the game, and the strategies are also evaluated and compared for each agent in order to find its best result. The overlapping community structure is naturally presented when the stop criterion is satisfied. The experimental results demonstrate that the proposed algorithm outperforms other similar algorithms for detecting overlapping communities in networks.

  15. A cooperative game framework for detecting overlapping communities in social networks

    Jonnalagadda, Annapurna; Kuppusamy, Lakshmanan

    2018-02-01

    Community detection in social networks is a challenging and complex task, which received much attention from researchers of multiple domains in recent years. The evolution of communities in social networks happens merely due to the self-interest of the nodes. The interesting feature of community structure in social networks is the multi membership of the nodes resulting in overlapping communities. Assuming the nodes of the social network as self-interested players, the dynamics of community formation can be captured in the form of a game. In this paper, we propose a greedy algorithm, namely, Weighted Graph Community Game (WGCG), in order to model the interactions among the self-interested nodes of the social network. The proposed algorithm employs the Shapley value mechanism to discover the inherent communities of the underlying social network. The experimental evaluation on the real-world and synthetic benchmark networks demonstrates that the performance of the proposed algorithm is superior to the state-of-the-art overlapping community detection algorithms.

  16. Network neighborhood analysis with the multi-node topological overlap measure.

    Li, Ai; Horvath, Steve

    2007-01-15

    The goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial 'seed' set of genes. Neighborhood analysis methods for network data are important in systems biology. If individual network connections are susceptible to noise, it can be advantageous to define neighborhoods on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures. The pairwise topological overlap measure is generalized to multiple network nodes and subsequently used in a recursive neighborhood construction method. A local permutation scheme is used to determine the neighborhood size. Using four network applications and a simulated example, we provide empirical evidence that the resulting neighborhoods are biologically meaningful, e.g. we use neighborhood analysis to identify brain cancer related genes. An executable Windows program and tutorial for multi-node topological overlap measure (MTOM) based analysis can be downloaded from the webpage (http://www.genetics.ucla.edu/labs/horvath/MTOM/).

  17. Is my network module preserved and reproducible?

    Peter Langfelder

    2011-01-01

    Full Text Available In many applications, one is interested in determining which of the properties of a network module change across conditions. For example, to validate the existence of a module, it is desirable to show that it is reproducible (or preserved in an independent test network. Here we study several types of network preservation statistics that do not require a module assignment in the test network. We distinguish network preservation statistics by the type of the underlying network. Some preservation statistics are defined for a general network (defined by an adjacency matrix while others are only defined for a correlation network (constructed on the basis of pairwise correlations between numeric variables. Our applications show that the correlation structure facilitates the definition of particularly powerful module preservation statistics. We illustrate that evaluating module preservation is in general different from evaluating cluster preservation. We find that it is advantageous to aggregate multiple preservation statistics into summary preservation statistics. We illustrate the use of these methods in six gene co-expression network applications including 1 preservation of cholesterol biosynthesis pathway in mouse tissues, 2 comparison of human and chimpanzee brain networks, 3 preservation of selected KEGG pathways between human and chimpanzee brain networks, 4 sex differences in human cortical networks, 5 sex differences in mouse liver networks. While we find no evidence for sex specific modules in human cortical networks, we find that several human cortical modules are less preserved in chimpanzees. In particular, apoptosis genes are differentially co-expressed between humans and chimpanzees. Our simulation studies and applications show that module preservation statistics are useful for studying differences between the modular structure of networks. Data, R software and accompanying tutorials can be downloaded from the following webpage: http

  18. In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap

    AlAmmouri, Ahmad

    2015-12-06

    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization in cellular networks. However, the explicit impact of spatial interference, imposed by FD communications, on uplink and downlink transmissions has been overlooked in the literature. This paper presents an extensive study of the explicit effect of FD communications on the uplink and downlink performances. For the sake of rigorous analysis, we develop a tractable framework based on stochastic geometry toolset. The developed model accounts for uplink truncated channel inversion power control in FD cellular networks. The study shows that FD communications improve the downlink throughput at the expense of significant degradation in the uplink throughput. Therefore, we propose a novel fine-grained duplexing scheme, denoted as α-duplex scheme, which allows a partial overlap between uplink and downlink frequency bands. To this end, we show that the amount of the overlap can be optimized via adjusting α to achieve a certain design objective.

  19. In-Band Full-Duplex Communications for Cellular Networks with Partial Uplink/Downlink Overlap

    Alammouri, Ahmad; Elsawy, Hesham; Amin, Osama; Alouini, Mohamed-Slim

    2015-01-01

    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization in cellular networks. However, the explicit impact of spatial interference, imposed by FD communications, on uplink and downlink transmissions has been overlooked in the literature. This paper presents an extensive study of the explicit effect of FD communications on the uplink and downlink performances. For the sake of rigorous analysis, we develop a tractable framework based on stochastic geometry toolset. The developed model accounts for uplink truncated channel inversion power control in FD cellular networks. The study shows that FD communications improve the downlink throughput at the expense of significant degradation in the uplink throughput. Therefore, we propose a novel fine-grained duplexing scheme, denoted as α-duplex scheme, which allows a partial overlap between uplink and downlink frequency bands. To this end, we show that the amount of the overlap can be optimized via adjusting α to achieve a certain design objective.

  20. Data on overlapping brain disorders and emerging drug targets in human Dopamine Receptors Interaction Network

    Avijit Podder

    2017-06-01

    Full Text Available Intercommunication of Dopamine Receptors (DRs with their associate protein partners is crucial to maintain regular brain function in human. Majority of the brain disorders arise due to malfunctioning of such communication process. Hence, contributions of genetic factors, as well as phenotypic indications for various neurological and psychiatric disorders are often attributed as sharing in nature. In our earlier research article entitled “Human Dopamine Receptors Interaction Network (DRIN: a systems biology perspective on topology, stability and functionality of the network” (Podder et al., 2014 [1], we had depicted a holistic interaction map of human Dopamine Receptors. Given emphasis on the topological parameters, we had characterized the functionality along with the vulnerable properties of the network. In support of this, we hereby provide an additional data highlighting the genetic overlapping of various brain disorders in the network. The data indicates the sharing nature of disease genes for various neurological and psychiatric disorders in dopamine receptors connecting protein-protein interactions network. The data also indicates toward an alternative approach to prioritize proteins for overlapping brain disorders as valuable drug targets in the network.

  1. Dense module enumeration in biological networks

    Tsuda, Koji; Georgii, Elisabeth

    2009-12-01

    Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.

  2. Dense module enumeration in biological networks

    Tsuda, Koji; Georgii, Elisabeth

    2009-01-01

    Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.

  3. Estimates of segregation and overlap of functional connectivity networks in the human cerebral cortex.

    Yeo, B T Thomas; Krienen, Fenna M; Chee, Michael W L; Buckner, Randy L

    2014-03-01

    The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. © 2013.

  4. Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure

    Yang Xuhua; Sun Bao; Wang Bo; Sun Youxian

    2010-01-01

    Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper. (general)

  5. Word and face processing engage overlapping distributed networks: Evidence from RSVP and EEG investigations.

    Robinson, Amanda K; Plaut, David C; Behrmann, Marlene

    2017-07-01

    Words and faces have vastly different visual properties, but increasing evidence suggests that word and face processing engage overlapping distributed networks. For instance, fMRI studies have shown overlapping activity for face and word processing in the fusiform gyrus despite well-characterized lateralization of these objects to the left and right hemispheres, respectively. To investigate whether face and word perception influences perception of the other stimulus class and elucidate the mechanisms underlying such interactions, we presented images using rapid serial visual presentations. Across 3 experiments, participants discriminated 2 face, word, and glasses targets (T1 and T2) embedded in a stream of images. As expected, T2 discrimination was impaired when it followed T1 by 200 to 300 ms relative to longer intertarget lags, the so-called attentional blink. Interestingly, T2 discrimination accuracy was significantly reduced at short intertarget lags when a face was followed by a word (face-word) compared with glasses-word and word-word combinations, indicating that face processing interfered with word perception. The reverse effect was not observed; that is, word-face performance was no different than the other object combinations. EEG results indicated the left N170 to T1 was correlated with the word decrement for face-word trials, but not for other object combinations. Taken together, the results suggest face processing interferes with word processing, providing evidence for overlapping neural mechanisms of these 2 object types. Furthermore, asymmetrical face-word interference points to greater overlap of face and word representations in the left than the right hemisphere. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  6. Interference Management in Full-Duplex Cellular Networks with Partial Spectrum Overlap

    Randrianantenaina, Itsikiantsoa

    2017-03-31

    Full-duplex (FD) communication is promoted to double the spectral efficiency when compared to the halfduplex (HD) counterpart. In the context of cellular networks, however, FD communication exacerbates the aggregate uplink and downlink interference, which diminishes the foreseen FD gains. This paper considers a flexible duplex system, denoted by -duplex (-D) system, wherein a fine-grained bandwidth control for each uplink/downlink channel pair in each base station (BS) is allowed, which also leads to partial spectrum overlap between the uplink and downlink channels. The paper addresses the resulting interference management problem by maximizing a network-wide rate-based utility function subject to uplink/downlink power constraints, so as to determine userto- BS association, user-to-channel scheduling, the UL and DL transmit powers, and the fraction of spectrum overlap between UL and DL for every user, under the assumption that the number of available channels and users are equal. The paper solves such a non-convex mixed-integer optimization problem in an iterative way by decoupling the problem into several subproblems. Particularly, the user-to-BS association problem is solved using a matching algorithm that is a generalization of the stable marriage problem. The scheduling problem is solved by iterative Hungarian algorithm. The power and spectrum overlap problem is solved by successive convex approximation. The proposed iterative strategy guarantees an efficient one-toone user to BS and channel assignment. It further provides optimized flexible duplexing and power allocation schemes for all transceivers. Simulations results show appreciable gains when comparing the proposed solution to different schemes from the literature.

  7. Interference Management in Full-Duplex Cellular Networks with Partial Spectrum Overlap

    Randrianantenaina, Itsikiantsoa; Dahrouj, Hayssam; Elsawy, Hesham; Alouini, Mohamed-Slim

    2017-01-01

    Full-duplex (FD) communication is promoted to double the spectral efficiency when compared to the halfduplex (HD) counterpart. In the context of cellular networks, however, FD communication exacerbates the aggregate uplink and downlink interference, which diminishes the foreseen FD gains. This paper considers a flexible duplex system, denoted by -duplex (-D) system, wherein a fine-grained bandwidth control for each uplink/downlink channel pair in each base station (BS) is allowed, which also leads to partial spectrum overlap between the uplink and downlink channels. The paper addresses the resulting interference management problem by maximizing a network-wide rate-based utility function subject to uplink/downlink power constraints, so as to determine userto- BS association, user-to-channel scheduling, the UL and DL transmit powers, and the fraction of spectrum overlap between UL and DL for every user, under the assumption that the number of available channels and users are equal. The paper solves such a non-convex mixed-integer optimization problem in an iterative way by decoupling the problem into several subproblems. Particularly, the user-to-BS association problem is solved using a matching algorithm that is a generalization of the stable marriage problem. The scheduling problem is solved by iterative Hungarian algorithm. The power and spectrum overlap problem is solved by successive convex approximation. The proposed iterative strategy guarantees an efficient one-toone user to BS and channel assignment. It further provides optimized flexible duplexing and power allocation schemes for all transceivers. Simulations results show appreciable gains when comparing the proposed solution to different schemes from the literature.

  8. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

    Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S.; Shen, Xilin; Constable, R. Todd; Li, Chiang-Shan R.; Chun, Marvin M.

    2016-01-01

    Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained attention task, and a low-attention network, comprising connections negatively correlated with performance. Validating the networks as generalizable biomarkers of attention, models based on network strength at rest predicted attention-deficit/hyperactivity disorder (ADHD) symptoms in an independent group of individuals (Rosenberg et al., 2016). To investigate whether these networks play a causal role in attention, here we examined their strength in healthy adults given methylphenidate (Ritalin), a common ADHD treatment, compared with unmedicated controls. As predicted, individuals given methylphenidate showed patterns of connectivity associated with better sustained attention: higher high-attention and lower low-attention network strength than controls. There was significant overlap between the high-attention network and a network with greater strength in the methylphenidate group, and between the low-attention network and a network with greater strength in the control group. Network strength also predicted behavior on a stop-signal task, such that participants with higher go response rates showed higher high-attention and lower low-attention network strength. These results suggest that methylphenidate acts by modulating functional brain networks related to sustained attention, and that changing whole-brain connectivity patterns may help improve attention. SIGNIFICANCE STATEMENT Recent work identified a promising neuromarker of sustained attention based on whole

  9. Caffeine Modulates Attention Network Function

    Brunye, Tad T.; Mahoney, Caroline R.; Lieberman, Harris R.; Taylor, Holly A.

    2010-01-01

    The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a flanker task designed to test Posner's three visual attention network functions: alerting, orienting, and executive control [Posner, M. I. (2004). "Cognitive neuroscience of attention". New York, NY: Guilford Press]. In a placebo-controlled, double-blind…

  10. 2D materials in electro-optic modulation: energy efficiency, electrostatics, mode overlap, material transfer and integration

    Ma, Zhizhen; Hemnani, Rohit; Bartels, Ludwig; Agarwal, Ritesh; Sorger, Volker J.

    2018-02-01

    Here we discuss the physics of electro-optic modulators deploying 2D materials. We include a scaling laws analysis and show how energy-efficiency and speed change for three underlying cavity systems as a function of critical device length scaling. A key result is that the energy-per-bit of the modulator is proportional to the volume of the device, thus making the case for submicron-scale modulators possible deploying a plasmonic optical mode. We then show how Graphene's Pauli-blocking modulation mechanism is sensitive to the device operation temperature, whereby a reduction of the temperature enables a 10× reduction in modulator energy efficiency. Furthermore, we show how the high-index tunability of graphene is able to compensate for the small optical overlap factor of 2D-based material modulators, which is unlike classical silicon-based dispersion devices. Lastly, we demonstrate a novel method towards a 2D material printer suitable for cross-contamination free and on-demand printing. The latter paves the way to integrate 2D materials seamlessly into taped-out photonic chips.

  11. Overlapping binding site for the endogenous agonist, small-molecule agonists, and ago-allosteric modulators on the ghrelin receptor

    Holst, Birgitte; Frimurer, Thomas M; Mokrosinski, Jacek

    2008-01-01

    A library of robust ghrelin receptor mutants with single substitutions at 22 positions in the main ligand-binding pocket was employed to map binding sites for six different agonists: two peptides (the 28-amino-acid octanoylated endogenous ligand ghrelin and the hexapeptide growth hormone......, and PheVI:23 on the opposing face of transmembrane domain (TM) VI. Each of the agonists was also affected selectively by specific mutations. The mutational map of the ability of L-692,429 and GHRP-6 to act as allosteric modulators by increasing ghrelin's maximal efficacy overlapped with the common....... It is concluded that although each of the ligands in addition exploits other parts of the receptor, a large, common binding site for both small-molecule agonists--including ago-allosteric modulators--and the endogenous agonist is found on the opposing faces of TM-III and -VI of the ghrelin receptor....

  12. A network approach to the comorbidity between posttraumatic stress disorder and major depressive disorder: The role of overlapping symptoms.

    Afzali, Mohammad H; Sunderland, Matthew; Teesson, Maree; Carragher, Natacha; Mills, Katherine; Slade, Tim

    2017-01-15

    The role of symptom overlap between major depressive disorder and posttraumatic stress disorder in comorbidity between two disorders is unclear. The current study applied network analysis to map the structure of symptom associations between these disorders. Data comes from a sample of 909 Australian adults with a lifetime history of trauma and depressive symptoms. Data analysis consisted of the construction of two comorbidity networks of PTSD/MDD with and without overlapping symptoms, identification of the bridging symptoms, and computation of the centrality measures. The prominent bridging role of four overlapping symptoms (i.e., sleep problems, irritability, concentration problems, and loss of interest) and five non-overlapping symptoms (i.e., feeling sad, feelings of guilt, psychomotor retardation, foreshortened future, and experiencing flashbacks) is highlighted. The current study uses DSM-IV criteria for PTSD and does not take into consideration significant changes made to PTSD criteria in DSM-5. Moreover, due to cross-sectional nature of the data, network estimates do not provide information on whether a symptom actively triggers other symptoms or whether a symptom mostly is triggered by other symptoms. The results support the role of dysphoria-related symptoms in PTSD/MDD comorbidity. Moreover, Identification of central symptoms and bridge symptoms will provide useful targets for interventions that seek to intervene early in the development of comorbidity. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

    Franke, R.

    2016-11-01

    In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

  14. Notational usage modulates attention networks in binumerates

    Atesh eKoul

    2014-05-01

    Full Text Available Multicultural environments require learning multiple number notations wherein some are encountered more frequently than others. This leads to differences in exposure and consequently differences in usage between notations. We find that differential notational usage imposes a significant neurocognitive load on number processing. Despite simultaneous acquisition, forty-two adult binumerate populations, familiar with two positional writing systems namely Hindu Nagari digits and Hindu Arabic digits, reported significantly lower preference and usage for Nagari as compared to Arabic. Twenty-four participants showed significantly increased reaction times and reduced accuracy while performing magnitude comparison tasks in Nagari with respect to Arabic. Functional magnetic resonance imaging revealed that processing Nagari elicited significantly greater activity in number processing and attention networks. A direct subtraction of networks for Nagari and Arabic notations revealed a neural circuit comprising of bilateral intra-parietal sulcus, inferior and mid frontal gyri, fusiform gyrus and the anterior cingulate cortex (FDR p<0.005. Additionally, whole brain correlation analysis showed that activity in the left inferior parietal region was modulated by task performance in Nagari. We attribute the increased activation in Ng to increased task difficulty due to infrequent exposure and usage. Our results reiterate the role of the left intra-parietal sulcus in modulating performance in numeric tasks and highlight that of the attention network for monitoring symbolic notation mode in binumerates.

  15. The Limbic-Prefrontal Network Modulated by Electroacupuncture at CV4 and CV12

    Jiliang Fang

    2012-01-01

    Full Text Available fMRI studies showed that acupuncture could induce hemodynamic changes in brain networks. Many of these studies focused on whether specific acupoints could activate specific brain regions and were often limited to manual acupuncture at acupoints on the limbs. In this fMRI study, we investigated acupuncture's modulation effects on brain functional networks by electroacupuncture (EA at acupoints on the midline of abdomen. Acupoints Guanyuan (CV4 and Zhongwan (CV12 were stimulated in 21 healthy volunteers. The needling sensations, brain activation, and functional connectivity were studied. We found that the limbic-prefrontal functional network was deactivated by EA at CV4 and CV12. More importantly, the local functional connectivity was significantly changed during EA stimulation, and the change persisted during the period after the stimulation. Although minor differences existed, both acupoints similarly modulated the limbic-prefrontal functional network, which is overlapped with the functional circuits associated with emotional and cognitive regulation.

  16. Modulation for emergent networks: serotonin and dopamine.

    Weng, Juyang; Paslaski, Stephen; Daly, James; VanDam, Courtland; Brown, Jacob

    2013-05-01

    In autonomous learning, value-sensitive experiences can improve the efficiency of learning. A learning network needs be motivated so that the limited computational resources and the limited lifetime are devoted to events that are of high value for the agent to compete in its environment. The neuromodulatory system of the brain is mainly responsible for developing such a motivation system. Although reinforcement learning has been extensively studied, many existing models are symbolic whose internal nodes or modules have preset meanings. Neural networks have been used to automatically generate internal emergent representations. However, modeling an emergent motivational system for neural networks is still a great challenge. By emergent, we mean that the internal representations emerge autonomously through interactions with the external environments. This work proposes a generic emergent modulatory system for emergent networks, which includes two subsystems - the serotonin system and the dopamine system. The former signals a large class of stimuli that are intrinsically aversive (e.g., stress or pain). The latter signals a large class of stimuli that are intrinsically appetitive (e.g., pleasure or sweet). We experimented with this motivational system for two settings. The first is a visual recognition setting to investigate how such a system can learn through interactions with a teacher, who does not directly give answers, but only punishments and rewards. The second is a setting for wandering in the presence of a friend and a foe. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. A predictive model to guide management of the overlap region between target volume and organs at risk in prostate cancer volumetric modulated arc therapy

    Mattes, Malcolm D.; Lee, Jennifer C.; Einaiem, Sara; Guirguis, Adel; Ikoro, N. C.; Ashamalla Hani [Dept. of Radiation Oncology, New York Methodist Hospital, Brooklyn (United States)

    2013-12-15

    The goal of this study is to determine whether the magnitude of overlap between planning target volume (PTV) and rectum (Rectum{sub overlap}) or PTV and bladder (Bladder{sub overlap}) in prostate cancer volumetric-modulated arc therapy (VMAT) is predictive of the dose-volume relationships achieved after optimization, and to identify predictive equations and cutoff values using these overlap volumes beyond which the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) dose-volume constraints are unlikely to be met. Fifty-seven patients with prostate cancer underwent VMAT planning using identical optimization conditions and normalization. The PTV (for the 50.4 Gy primary plan and 30.6 Gy boost plan) included 5 to 10 mm margins around the prostate and seminal vesicles. Pearson correlations, linear regression analyses, and receiver operating characteristic (ROC) curves were used to correlate the percentage overlap with dose-volume parameters. The percentage Rectum{sub overlap} and Bladder{sub overlap} correlated with sparing of that organ but minimally impacted other dose-volume parameters, predicted the primary plan rectum V{sub 45} and bladder V{sub 50} with R{sup 2} = 0.78 and R{sup 2} = 0.83, respectively, and predicted the boost plan rectum V{sub 30} and bladder V{sub 30} with R{sup 2} = 0.53 and R{sup 2} = 0.81, respectively. The optimal cutoff value of boost Rectumoverlap to predict rectum V75 >15% was 3.5% (sensitivity 100%, specificity 94%, p < 0.01), and the optimal cutoff value of boost Bladder{sub overlap} to predict bladder V{sub 80} >10% was 5.0% (sensitivity 83%, specificity 100%, p < 0.01). The degree of overlap between PTV and bladder or rectum can be used to accurately guide physicians on the use of interventions to limit the extent of the overlap region prior to optimization.

  18. A predictive model to guide management of the overlap region between target volume and organs at risk in prostate cancer volumetric modulated arc therapy

    Mattes, Malcolm D.; Lee, Jennifer C.; Einaiem, Sara; Guirguis, Adel; Ikoro, N. C.; Ashamalla Hani

    2013-01-01

    The goal of this study is to determine whether the magnitude of overlap between planning target volume (PTV) and rectum (Rectum overlap ) or PTV and bladder (Bladder overlap ) in prostate cancer volumetric-modulated arc therapy (VMAT) is predictive of the dose-volume relationships achieved after optimization, and to identify predictive equations and cutoff values using these overlap volumes beyond which the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) dose-volume constraints are unlikely to be met. Fifty-seven patients with prostate cancer underwent VMAT planning using identical optimization conditions and normalization. The PTV (for the 50.4 Gy primary plan and 30.6 Gy boost plan) included 5 to 10 mm margins around the prostate and seminal vesicles. Pearson correlations, linear regression analyses, and receiver operating characteristic (ROC) curves were used to correlate the percentage overlap with dose-volume parameters. The percentage Rectum overlap and Bladder overlap correlated with sparing of that organ but minimally impacted other dose-volume parameters, predicted the primary plan rectum V 45 and bladder V 50 with R 2 = 0.78 and R 2 = 0.83, respectively, and predicted the boost plan rectum V 30 and bladder V 30 with R 2 = 0.53 and R 2 = 0.81, respectively. The optimal cutoff value of boost Rectumoverlap to predict rectum V75 >15% was 3.5% (sensitivity 100%, specificity 94%, p overlap to predict bladder V 80 >10% was 5.0% (sensitivity 83%, specificity 100%, p < 0.01). The degree of overlap between PTV and bladder or rectum can be used to accurately guide physicians on the use of interventions to limit the extent of the overlap region prior to optimization.

  19. Friending, IMing, and hanging out face-to-face: overlap in adolescents' online and offline social networks.

    Reich, Stephanie M; Subrahmanyam, Kaveri; Espinoza, Guadalupe

    2012-03-01

    Many new and important developmental issues are encountered during adolescence, which is also a time when Internet use becomes increasingly popular. Studies have shown that adolescents are using these online spaces to address developmental issues, especially needs for intimacy and connection to others. Online communication with its potential for interacting with unknown others, may put teens at increased risk. Two hundred and fifty-one high school students completed an in-person survey, and 126 of these completed an additional online questionnaire about how and why they use the Internet, their activities on social networking sites (e.g., Facebook, MySpace) and their reasons for participation, and how they perceive these online spaces to impact their friendships. To examine the extent of overlap between online and offline friends, participants were asked to list the names of their top interaction partners offline and online (Facebook and instant messaging). Results reveal that adolescents mainly use social networking sites to connect with others, in particular with people known from offline contexts. While adolescents report little monitoring by their parents, there was no evidence that teens are putting themselves at risk by interacting with unknown others. Instead, adolescents seem to use the Internet, especially social networking sites, to connect with known others. While the study found moderate overlap between teens' closest online and offline friends, the patterns suggest that adolescents use online contexts to strengthen offline relationships. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  20. SPARK: Sparsity-based analysis of reliable k-hubness and overlapping network structure in brain functional connectivity.

    Lee, Kangjoo; Lina, Jean-Marc; Gotman, Jean; Grova, Christophe

    2016-07-01

    Functional hubs are defined as the specific brain regions with dense connections to other regions in a functional brain network. Among them, connector hubs are of great interests, as they are assumed to promote global and hierarchical communications between functionally specialized networks. Damage to connector hubs may have a more crucial effect on the system than does damage to other hubs. Hubs in graph theory are often identified from a correlation matrix, and classified as connector hubs when the hubs are more connected to regions in other networks than within the networks to which they belong. However, the identification of hubs from functional data is more complex than that from structural data, notably because of the inherent problem of multicollinearity between temporal dynamics within a functional network. In this context, we developed and validated a method to reliably identify connectors and corresponding overlapping network structure from resting-state fMRI. This new method is actually handling the multicollinearity issue, since it does not rely on counting the number of connections from a thresholded correlation matrix. The novelty of the proposed method is that besides counting the number of networks involved in each voxel, it allows us to identify which networks are actually involved in each voxel, using a data-driven sparse general linear model in order to identify brain regions involved in more than one network. Moreover, we added a bootstrap resampling strategy to assess statistically the reproducibility of our results at the single subject level. The unified framework is called SPARK, i.e. SParsity-based Analysis of Reliable k-hubness, where k-hubness denotes the number of networks overlapping in each voxel. The accuracy and robustness of SPARK were evaluated using two dimensional box simulations and realistic simulations that examined detection of artificial hubs generated on real data. Then, test/retest reliability of the method was assessed

  1. Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

    Ettore Mosca

    2017-09-01

    Full Text Available Autism spectrum disorder (ASD is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called “disease modules.” In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

  2. Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

    Cai, Congbo; Wang, Chao; Zeng, Yiqing; Cai, Shuhui; Liang, Dong; Wu, Yawen; Chen, Zhong; Ding, Xinghao; Zhong, Jianhui

    2018-04-24

    An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T 2 mapping from single-shot overlapping-echo detachment (OLED) planar imaging. The training dataset was obtained from simulations that were carried out on SPROM (Simulation with PRoduct Operator Matrix) software developed by our group. The relationship between the original OLED image containing two echo signals and the corresponding T 2 mapping was learned by ResNet training. After the ResNet was trained, it was applied to reconstruct the T 2 mapping from simulation and in vivo human brain data. Although the ResNet was trained entirely on simulated data, the trained network was generalized well to real human brain data. The results from simulation and in vivo human brain experiments show that the proposed method significantly outperforms the echo-detachment-based method. Reliable T 2 mapping with higher accuracy is achieved within 30 ms after the network has been trained, while the echo-detachment-based OLED reconstruction method took approximately 2 min. The proposed method will facilitate real-time dynamic and quantitative MR imaging via OLED sequence, and deep convolutional neural network has the potential to reconstruct maps from complex MRI sequences efficiently. © 2018 International Society for Magnetic Resonance in Medicine.

  3. Bayesian latent feature modeling for modeling bipartite networks with overlapping groups

    Jørgensen, Philip H.; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2016-01-01

    Bi-partite networks are commonly modelled using latent class or latent feature models. Whereas the existing latent class models admit marginalization of parameters specifying the strength of interaction between groups, existing latent feature models do not admit analytical marginalization...... by the notion of community structure such that the edge density within groups is higher than between groups. Our model further assumes that entities can have different propensities of generating links in one of the modes. The proposed framework is contrasted on both synthetic and real bi-partite networks...... feature representations in bipartite networks provides a new framework for accounting for structure in bi-partite networks using binary latent feature representations providing interpretable representations that well characterize structure as quantified by link prediction....

  4. FMFinder: A Functional Module Detector for PPI Networks

    M. Modi

    2017-10-01

    Full Text Available Bioinformatics is an integrated area of data mining, statistics and computational biology. Protein-Protein Interaction (PPI network is the most important biological process in living beings. In this network a protein module interacts with another module and so on, forming a large network of proteins. The same set of proteins which takes part in the organic courses of biological actions is detected through the Function Module Detection method. Clustering process when applied in PPI networks is made of proteins which are part of a larger communication network. As a result of this, we can define the limits for module detection as well as clarify the construction of a PPI network. For understating the bio-mechanism of various living beings, a detailed study of FMFinder detection by clustering process is called for.

  5. People identification for domestic non-overlapping RGB-D camera networks

    Takac, B.; Rauterberg, G.W.M.; Català, A.; Chen, W.

    2015-01-01

    The ability to identify the specific person in a home camera network is very relevant for healthcare applications where humans need to be observed daily in their living environment. The appearance based people identification in a domestic environment has many similarities with the problem of

  6. Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection.

    DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

    2015-06-01

    Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Identify Dynamic Network Modules with Temporal and Spatial Constraints

    Jin, R; McCallen, S; Liu, C; Almaas, E; Zhou, X J

    2007-09-24

    Despite the rapid accumulation of systems-level biological data, understanding the dynamic nature of cellular activity remains a difficult task. The reason is that most biological data are static, or only correspond to snapshots of cellular activity. In this study, we explicitly attempt to detangle the temporal complexity of biological networks by using compilations of time-series gene expression profiling data.We define a dynamic network module to be a set of proteins satisfying two conditions: (1) they form a connected component in the protein-protein interaction (PPI) network; and (2) their expression profiles form certain structures in the temporal domain. We develop the first efficient mining algorithm to discover dynamic modules in a temporal network, as well as frequently occurring dynamic modules across many temporal networks. Using yeast as a model system, we demonstrate that the majority of the identified dynamic modules are functionally homogeneous. Additionally, many of them provide insight into the sequential ordering of molecular events in cellular systems. We further demonstrate that identifying frequent dynamic network modules can significantly increase the signal to noise separation, despite the fact that most dynamic network modules are highly condition-specific. Finally, we note that the applicability of our algorithm is not limited to the study of PPI systems, instead it is generally applicable to the combination of any type of network and time-series data.

  8. Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks

    Garrido, Jesús A.; Luque, Niceto R.; Tolu, Silvia

    2016-01-01

    The majority of operations carried out by the brain require learning complex signal patterns for future recognition, retrieval and reuse. Although learning is thought to depend on multiple forms of long-term synaptic plasticity, the way this latter contributes to pattern recognition is still poorly...... and at the inhibitory interneuron-interneuron synapses, the interneurons rapidly learned complex input patterns. Interestingly, induction of plasticity required that the network be entrained into theta-frequency band oscillations, setting the internal phase-reference required to drive STDP. Inhibitory plasticity...... effectively distributed multiple patterns among available interneurons, thus allowing the simultaneous detection of multiple overlapping patterns. The addition of plasticity in intrinsic excitability made the system more robust allowing self-adjustment and rescaling in response to a broad range of input...

  9. Dog and human inflammatory bowel disease rely on overlapping yet distinct dysbiosis networks.

    Vázquez-Baeza, Yoshiki; Hyde, Embriette R; Suchodolski, Jan S; Knight, Rob

    2016-10-03

    Inflammatory bowel disease (IBD) is an autoimmune condition that is difficult to diagnose, and animal models of this disease have questionable human relevance 1 . Here, we show that the dysbiosis network underlying IBD in dogs differs from that in humans, with some bacteria such as Fusobacterium switching roles between the two species (as Bacteroides fragilis switches roles between humans and mice) 2 . For example, a dysbiosis index trained on humans fails when applied to dogs, but a dog-specific dysbiosis index achieves high correlations with the overall dog microbial community diversity patterns. In addition, a random forest classifier trained on dog-specific samples achieves high discriminatory power, even when using stool samples rather than the mucosal biopsies required for high discriminatory power in humans 2 . These relationships were not detected in previously published dog IBD data sets due to their limited sample size and statistical power 3 . Taken together, these results reveal the need to train host-specific dysbiosis networks and point the way towards a generalized understanding of IBD across different mammalian models.

  10. Identification of unstable network modules reveals disease modules associated with the progression of Alzheimer's disease.

    Masataka Kikuchi

    Full Text Available Alzheimer's disease (AD, the most common cause of dementia, is associated with aging, and it leads to neuron death. Deposits of amyloid β and aberrantly phosphorylated tau protein are known as pathological hallmarks of AD, but the underlying mechanisms have not yet been revealed. A high-throughput gene expression analysis previously showed that differentially expressed genes accompanying the progression of AD were more down-regulated than up-regulated in the later stages of AD. This suggested that the molecular networks and their constituent modules collapsed along with AD progression. In this study, by using gene expression profiles and protein interaction networks (PINs, we identified the PINs expressed in three brain regions: the entorhinal cortex (EC, hippocampus (HIP and superior frontal gyrus (SFG. Dividing the expressed PINs into modules, we examined the stability of the modules with AD progression and with normal aging. We found that in the AD modules, the constituent proteins, interactions and cellular functions were not maintained between consecutive stages through all brain regions. Interestingly, the modules were collapsed with AD progression, specifically in the EC region. By identifying the modules that were affected by AD pathology, we found the transcriptional regulation-associated modules that interact with the proteasome-associated module via UCHL5 hub protein, which is a deubiquitinating enzyme. Considering PINs as a system made of network modules, we found that the modules relevant to the transcriptional regulation are disrupted in the EC region, which affects the ubiquitin-proteasome system.

  11. Silicon nanowire networks for multi-stage thermoelectric modules

    Norris, Kate J.; Garrett, Matthew P.; Zhang, Junce; Coleman, Elane; Tompa, Gary S.; Kobayashi, Nobuhiko P.

    2015-01-01

    Highlights: • Fabricated flexible single, double, and quadruple stacked Si thermoelectric modules. • Measured an enhanced power production of 27%, showing vertical stacking is scalable. • Vertically scalable thermoelectric module design of semiconducting nanowires. • Design can utilize either p or n-type semiconductors, both types are not required. • ΔT increases with thickness therefore power/area can increase as modules are stacked. - Abstract: We present the fabrication and characterization of single, double, and quadruple stacked flexible silicon nanowire network based thermoelectric modules. From double to quadruple stacked modules, power production increased 27%, demonstrating that stacking multiple nanowire thermoelectric devices in series is a scalable method to generate power by supplying larger temperature gradient. We present a vertically scalable multi-stage thermoelectric module design using semiconducting nanowires, eliminating the need for both n-type and p-type semiconductors for modules

  12. A method for identifying hierarchical sub-networks / modules and weighting network links based on their similarity in sub-network / module affiliation

    WenJun Zhang

    2016-06-01

    Full Text Available Some networks, including biological networks, consist of hierarchical sub-networks / modules. Based on my previous study, in present study a method for both identifying hierarchical sub-networks / modules and weighting network links is proposed. It is based on the cluster analysis in which between-node similarity in sets of adjacency nodes is used. Two matrices, linkWeightMat and linkClusterIDs, are achieved by using the algorithm. Two links with both the same weight in linkWeightMat and the same cluster ID in linkClusterIDs belong to the same sub-network / module. Two links with the same weight in linkWeightMat but different cluster IDs in linkClusterIDs belong to two sub-networks / modules at the same hirarchical level. However, a link with an unique cluster ID in linkClusterIDs does not belong to any sub-networks / modules. A sub-network / module of the greater weight is the more connected sub-network / modules. Matlab codes of the algorithm are presented.

  13. Functional modules by relating protein interaction networks and gene expression.

    Tornow, Sabine; Mewes, H W

    2003-11-01

    Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

  14. Overlap functions

    Bustince, H.; Fernández, J.; Mesiar, Radko; Montero, J.; Orduna, R.

    2010-01-01

    Roč. 72, 3-4 (2010), s. 1488-1499 ISSN 0362-546X R&D Projects: GA ČR GA402/08/0618 Institutional research plan: CEZ:AV0Z10750506 Keywords : t-norm * Migrative property * Homogeneity property * Overlap function Subject RIV: BA - General Mathematics Impact factor: 1.279, year: 2010 http://library.utia.cas.cz/separaty/2009/E/mesiar-overlap functions.pdf

  15. Overlap between the neural correlates of cued recall and source memory: evidence for a generic recollection network?

    Hayama, Hiroki R; Vilberg, Kaia L; Rugg, Michael D

    2012-05-01

    Recall of a studied item and retrieval of its encoding context (source memory) both depend on recollection of qualitative information about the study episode. This study investigated whether recall and source memory engage overlapping neural regions. Participants (n = 18) studied a series of words, which were presented either to the left or right of fixation. fMRI data were collected during a subsequent test phase in which three-letter word-stems were presented, two thirds of which could be completed by a study item. Instructions were to use each stem as a cue to recall a studied word and, when recall was successful, to indicate the word's study location. When recall failed, the stem was to be completed with the first word to come to mind. Relative to stems for which recall failed, word-stems eliciting successful recall were associated with enhanced activity in a variety of cortical regions, including bilateral parietal, posterior midline, and parahippocampal cortex. Activity in these regions was enhanced when recall was accompanied by successful rather than unsuccessful source retrieval. It is proposed that the regions form part of a "recollection network" in which activity is graded according to the amount of information retrieved about a study episode.

  16. Multi-equilibrium property of metabolic networks: SSI module

    Chen Luonan

    2011-06-01

    Full Text Available Abstract Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

  17. Network monitoring module of BES III system environment

    Song Liwen; Zhao Jingwei; Zhang Bingyun

    2002-01-01

    In order to meet the needs of the complicated network architecture of BES III (Beijing Spectrometer III) and make sure normal online running in the future, it is necessary to develop a multi-platforms Network Monitoring Tool which can help system administrator monitor and manage BES III network. The author provides a module that can monitor not only the traffic of switch-router's ports but also the performance status of key devices in the network environment, meanwhile it can also give warning to manager and submit the related reports. the great sense, the theory basis, the implementing method and the graph in formation of this tool will be discussed

  18. Mixed Th2 and non-Th2 inflammatory pattern in the asthma–COPD overlap: a network approach

    Pérez de Llano L

    2018-02-01

    the nature of inflammation in patients with ACO. Objectives: We aimed at investigating the role and interaction of common markers of systemic inflammation (IL-6, IL-8, and tumor necrosis factor-α, Th2-related markers (periostin, IL-5, and IL-13, and IL-17 in asthma, COPD, and ACO. Methods: This is a cross-sectional study of patients aged ≥40 years with a post-bronchodilator forced expiratory volume in the first second/forced vital capacity <0.70 recruited from outpatient clinics in tertiary hospitals with a clinical diagnosis of asthma, COPD, or ACO. ACO was defined by a history of smoking >10 pack-years in a patient with a previous diagnosis of asthma or by the presence of eosinophilia in a patient with a previous diagnosis of COPD. Clinical, functional, and inflammatory parameters were compared between categories using discriminant and network analysis. Results: In total, 109 ACO, 89 COPD, and 94 asthma patients were included. Serum levels (median [interquartile range] of IL-5 were higher in asthma patients than in COPD patients (2.09 [0.61–3.57] vs 1.11 [0.12–2.42] pg/mL, respectively; p=0.03, and IL-8 levels (median [interquartile range] were higher in COPD patients than in asthma patients (9.45 [6.61–13.12] vs 7.03 [4.69–10.44] pg/mL, respectively; p<0.001. Their values in ACO were intermediate between those in asthma and in COPD. Principal component and network analysis showed a mixed inflammatory pattern in ACO in between asthma and COPD. IL-13 was the most connected node in the network, with different weights among the three conditions. Conclusion: Asthma and COPD are two different inflammatory conditions that may overlap in some patients, leading to a mixed inflammatory pattern. IL-13 could be central to the regulation of inflammation in these conditions. Keywords: asthma mechanisms, COPD mechanisms, inflammatory cytokines, overlap, network analysis, IL-13

  19. Network-dependent modulation of brain activity during sleep.

    Watanabe, Takamitsu; Kan, Shigeyuki; Koike, Takahiko; Misaki, Masaya; Konishi, Seiki; Miyauchi, Satoru; Miyahsita, Yasushi; Masuda, Naoki

    2014-09-01

    Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Altered brain network modules induce helplessness in major depressive disorder.

    Peng, Daihui; Shi, Feng; Shen, Ting; Peng, Ziwen; Zhang, Chen; Liu, Xiaohua; Qiu, Meihui; Liu, Jun; Jiang, Kaida; Fang, Yiru; Shen, Dinggang

    2014-10-01

    The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD. Resting-state functional magnetic resonance imaging data were acquired from 16 first episode, medication-naïve MDD patients and 16 healthy control subjects. The global FC network was constructed using 90 brain regions. The global topological patterns, e.g., small-worldness and modularity, and their relationships with depressive characteristics were investigated. Furthermore, the participant coefficient and module degree of MDD patients were measured to reflect the regional roles in module network, and the impairment of FC was examined by network based statistic. Small-world property was not altered in MDD. However, MDD patients exhibited 5 atypically reorganized modules compared to the controls. A positive relationship was also found among MDD patients between the intra-module I and helplessness factor evaluated via the Hamilton Depression Scale. Specifically, eight regions exhibited the abnormal participant coefficient or module degree, e.g., left superior orbital frontal cortex and right amygdala. The decreased FC was identified among the sub-network of 24 brain regions, e.g., frontal cortex, supplementary motor area, amygdala, thalamus, and hippocampus. The limited size of MDD samples precluded meaningful study of distinct clinical characteristics in relation to aberrant FC. The results revealed altered patterns of brain module network at the global level in MDD patients, which might contribute to the feelings of helplessness. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Modulation of neuronal network activity with ghrelin

    Stoyanova, Irina; Rutten, Wim; le Feber, Jakob

    2012-01-01

    Ghrelin is a neuropeptide regulating multiple physiological processes, including high brain functions such as learning and memory formation. However, the effect of ghrelin on network activity patterns and developments has not been studied yet. Therefore, we used dissociated cortical neurons plated

  2. Modulation aware cluster size optimisation in wireless sensor networks

    Sriram Naik, M.; Kumar, Vinay

    2017-07-01

    Wireless sensor networks (WSNs) play a great role because of their numerous advantages to the mankind. The main challenge with WSNs is the energy efficiency. In this paper, we have focused on the energy minimisation with the help of cluster size optimisation along with consideration of modulation effect when the nodes are not able to communicate using baseband communication technique. Cluster size optimisations is important technique to improve the performance of WSNs. It provides improvement in energy efficiency, network scalability, network lifetime and latency. We have proposed analytical expression for cluster size optimisation using traditional sensing model of nodes for square sensing field with consideration of modulation effects. Energy minimisation can be achieved by changing the modulation schemes such as BPSK, 16-QAM, QPSK, 64-QAM, etc., so we are considering the effect of different modulation techniques in the cluster formation. The nodes in the sensing fields are random and uniformly deployed. It is also observed that placement of base station at centre of scenario enables very less number of modulation schemes to work in energy efficient manner but when base station placed at the corner of the sensing field, it enable large number of modulation schemes to work in energy efficient manner.

  3. Default network modulation and large-scale network interactivity in healthy young and old adults.

    Spreng, R Nathan; Schacter, Daniel L

    2012-11-01

    We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands.

  4. Module detection in complex networks using integer optimisation

    Tsoka Sophia

    2010-11-01

    Full Text Available Abstract Background The detection of modules or community structure is widely used to reveal the underlying properties of complex networks in biology, as well as physical and social sciences. Since the adoption of modularity as a measure of network topological properties, several methodologies for the discovery of community structure based on modularity maximisation have been developed. However, satisfactory partitions of large graphs with modest computational resources are particularly challenging due to the NP-hard nature of the related optimisation problem. Furthermore, it has been suggested that optimising the modularity metric can reach a resolution limit whereby the algorithm fails to detect smaller communities than a specific size in large networks. Results We present a novel solution approach to identify community structure in large complex networks and address resolution limitations in module detection. The proposed algorithm employs modularity to express network community structure and it is based on mixed integer optimisation models. The solution procedure is extended through an iterative procedure to diminish effects that tend to agglomerate smaller modules (resolution limitations. Conclusions A comprehensive comparative analysis of methodologies for module detection based on modularity maximisation shows that our approach outperforms previously reported methods. Furthermore, in contrast to previous reports, we propose a strategy to handle resolution limitations in modularity maximisation. Overall, we illustrate ways to improve existing methodologies for community structure identification so as to increase its efficiency and applicability.

  5. Optical vector network analyzer based on double-sideband modulation.

    Jun, Wen; Wang, Ling; Yang, Chengwu; Li, Ming; Zhu, Ning Hua; Guo, Jinjin; Xiong, Liangming; Li, Wei

    2017-11-01

    We report an optical vector network analyzer (OVNA) based on double-sideband (DSB) modulation using a dual-parallel Mach-Zehnder modulator. The device under test (DUT) is measured twice with different modulation schemes. By post-processing the measurement results, the response of the DUT can be obtained accurately. Since DSB modulation is used in our approach, the measurement range is doubled compared with conventional single-sideband (SSB) modulation-based OVNA. Moreover, the measurement accuracy is improved by eliminating the even-order sidebands. The key advantage of the proposed scheme is that the measurement of a DUT with bandpass response can also be simply realized, which is a big challenge for the SSB-based OVNA. The proposed method is theoretically and experimentally demonstrated.

  6. Remote synchronization reveals network symmetries and functional modules.

    Nicosia, Vincenzo; Valencia, Miguel; Chavez, Mario; Díaz-Guilera, Albert; Latora, Vito

    2013-04-26

    We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmetry are fully synchronized, despite their distance on the graph. We provide analytical arguments to explain this result, and we show how the frustration parameter affects the distribution of phases. An application to brain networks suggests that anatomical symmetry plays a role in neural synchronization by determining correlated functional modules across distant locations.

  7. Asymmetric Modulation Gains in Network Coded Relay Networks

    Roetter, Daniel Enrique Lucani; Fitzek, Frank

    2015-01-01

    Wireless relays have usually been considered in two ways. On the one hand, a physical layer approach focused on per-packet reliability and involving the relay on each packet transmission. On the other, recent approaches have relied on the judicious activation of the relay at the network level to ...

  8. Bilingual Contexts Modulate the Inhibitory Control Network

    Jing Yang

    2018-03-01

    Full Text Available The present functional magnetic resonance imaging (fMRI study investigated influences of language contexts on inhibitory control and the underlying neural processes. Thirty Cantonese–Mandarin–English trilingual speakers, who were highly proficient in Cantonese (L1 and Mandarin (L2, and moderately proficient in English (L3, performed a picture-naming task in three dual-language contexts (L1-L2, L2-L3, and L1-L3. After each of the three naming tasks, participants performed a flanker task, measuring contextual effects on the inhibitory control system. Behavioral results showed a typical flanker effect in the L2-L3 and L1-L3 condition, but not in the L1-L2 condition, which indicates contextual facilitation on inhibitory control performance by the L1-L2 context. Whole brain analysis of the fMRI data acquired during the flanker tasks showed more neural activations in the right prefrontal cortex and subcortical areas in the L2-L3 and L1-L3 condition on one hand as compared to the L1-L2 condition on the other hand, suggesting greater involvement of the cognitive control areas when participants were performing the flanker task in L2-L3 and L1-L3 contexts. Effective connectivity analyses displayed a cortical-subcortical-cerebellar circuitry for inhibitory control in the trilinguals. However, contrary to the right-lateralized network in the L1-L2 condition, functional networks for inhibitory control in the L2-L3 and L1-L3 condition are less integrated and more left-lateralized. These findings provide a novel perspective for investigating the interaction between bilingualism (multilingualism and inhibitory control by demonstrating instant behavioral effects and neural plasticity as a function of changes in global language contexts.

  9. Pramipexole Modulates Interregional Connectivity Within the Sensorimotor Network.

    Ye, Zheng; Hammer, Anke; Münte, Thomas F

    2017-05-01

    Pramipexole is widely prescribed to treat Parkinson's disease but has been reported to cause impulse control disorders such as pathological gambling. Recent neurocomputational models suggested that D2 agonists may distort functional connections between the striatum and the motor cortex, resulting in impaired reinforcement learning and pathological gambling. To examine how D2 agonists modulate the striatal-motor connectivity, we carried out a pharmacological resting-state functional magnetic resonance imaging study with a double-blind randomized within-subject crossover design. We analyzed the medication-induced changes of network connectivity and topology with two approaches, an independent component analysis (ICA) and a graph theoretical analysis (GTA). The ICA identified the sensorimotor network (SMN) as well as other classical resting-state networks. Within the SMN, the connectivity between the right caudate nucleus and other cortical regions was weaker under pramipexole than under placebo. The GTA measured the topological properties of the whole-brain network at global and regional levels. Both the whole-brain network under placebo and that under pramipexole were identified as small-world networks. The two whole-brain networks were similar in global efficiency, clustering coefficient, small-world index, and modularity. However, the degree of the right caudate nucleus decreased under pramipexole mainly due to the loss of the connectivity with the supplementary motor area, paracentral lobule, and precentral and postcentral gyrus of the SMN. The two network analyses consistently revealed that pramipexole weakened the functional connectivity between the caudate nucleus and the SMN regions.

  10. High Dimensional Modulation and MIMO Techniques for Access Networks

    Binti Othman, Maisara

    Exploration of advanced modulation formats and multiplexing techniques for next generation optical access networks are of interest as promising solutions for delivering multiple services to end-users. This thesis addresses this from two different angles: high dimensionality carrierless...... the capacity per wavelength of the femto-cell network. Bit rate up to 1.59 Gbps with fiber-wireless transmission over 1 m air distance is demonstrated. The results presented in this thesis demonstrate the feasibility of high dimensionality CAP in increasing the number of dimensions and their potentially......) optical access network. 2 X 2 MIMO RoF employing orthogonal frequency division multiplexing (OFDM) with 5.6 GHz RoF signaling over all-vertical cavity surface emitting lasers (VCSEL) WDM passive optical networks (PONs). We have employed polarization division multiplexing (PDM) to further increase...

  11. Validating module network learning algorithms using simulated data.

    Michoel, Tom; Maere, Steven; Bonnet, Eric; Joshi, Anagha; Saeys, Yvan; Van den Bulcke, Tim; Van Leemput, Koenraad; van Remortel, Piet; Kuiper, Martin; Marchal, Kathleen; Van de Peer, Yves

    2007-05-03

    In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Despite the demonstrated success of such algorithms in uncovering biologically relevant regulatory relations, further developments in the area are hampered by a lack of tools to compare the performance of alternative module network learning strategies. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators. We show that data simulators such as SynTReN are very well suited for the purpose of developing, testing and improving module network

  12. Pro-cognitive drug effects modulate functional brain network organization

    Giessing, Carsten; Thiel, Christiane M.

    2012-01-01

    Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with functional magnetic resonance imaging (fMRI). Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e., the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the “global workspace” theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs

  13. Implementation of quantum key distribution network simulation module in the network simulator NS-3

    Mehic, Miralem; Maurhart, Oliver; Rass, Stefan; Voznak, Miroslav

    2017-10-01

    As the research in quantum key distribution (QKD) technology grows larger and becomes more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. Due to the specificity of the QKD link which requires optical and Internet connection between the network nodes, to deploy a complete testbed containing multiple network hosts and links to validate and verify a certain network algorithm or protocol would be very costly. Network simulators in these circumstances save vast amounts of money and time in accomplishing such a task. The simulation environment offers the creation of complex network topologies, a high degree of control and repeatable experiments, which in turn allows researchers to conduct experiments and confirm their results. In this paper, we described the design of the QKD network simulation module which was developed in the network simulator of version 3 (NS-3). The module supports simulation of the QKD network in an overlay mode or in a single TCP/IP mode. Therefore, it can be used to simulate other network technologies regardless of QKD.

  14. Learning modulation of odor representations: new findings from Arc-indexed networks

    Qi eYuan

    2014-12-01

    Full Text Available We first review our understanding of odor representations in rodent olfactory bulb and anterior piriform cortex. We then consider learning-induced representation changes. Finally we describe the perspective on network representations gained from examining Arc-indexed odor networks of awake rats. Arc-indexed networks are sparse and distributed, consistent with current views. However Arc provides representations of repeated odors. Arc-indexed repeated odor representations are quite variable. Sparse representations are assumed to be compact and reliable memory codes. Arc suggests this is not necessarily the case. The variability seen is consistent with electrophysiology in awake animals and may reflect top down-cortical modulation of context. Arc-indexing shows that distinct odors share larger than predicted neuron pools. These may be low-threshold neuronal subsets.Learning’s effect on Arc-indexed representations is to increase the stable or overlapping component of rewarded odor representations. This component can decrease for similar odors when their discrimination is rewarded. The learning effects seen are supported by electrophysiology, but mechanisms remain to be elucidated.

  15. Load-induced modulation of signal transduction networks.

    Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

    2011-10-11

    Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

  16. Modulation of attentional networks by food-related disinhibition.

    Hege, Maike A; Stingl, Krunoslav T; Veit, Ralf; Preissl, Hubert

    2017-07-01

    The risk of weight gain is especially related to disinhibition, which indicates the responsiveness to external food stimuli with associated disruptions in eating control. We adapted a food-related version of the attention network task and used functional magnetic resonance imaging to study the effects of disinhibition on attentional networks in 19 normal-weight participants. High disinhibition scores were associated with a rapid reorienting response to food pictures after invalid cueing and with an enhanced alerting effect of a warning cue signalizing the upcoming appearance of a food picture. Imaging data revealed activation of a right-lateralized ventral attention network during reorienting. The faster the reorienting and the higher the disinhibition score, the less activation of this network was observed. The alerting contrast showed activation in visual, temporo-parietal and anterior sites. These modulations of attentional networks by food-related disinhibition might be related to an attentional bias to energy dense and palatable food and increased intake of food in disinhibited individuals. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Space station common module network topology and hardware development

    Anderson, P.; Braunagel, L.; Chwirka, S.; Fishman, M.; Freeman, K.; Eason, D.; Landis, D.; Lech, L.; Martin, J.; Mccorkle, J.

    1990-01-01

    Conceptual space station common module power management and distribution (SSM/PMAD) network layouts and detailed network evaluations were developed. Individual pieces of hardware to be developed for the SSM/PMAD test bed were identified. A technology assessment was developed to identify pieces of equipment requiring development effort. Equipment lists were developed from the previously selected network schematics. Additionally, functional requirements for the network equipment as well as other requirements which affected the suitability of specific items for use on the Space Station Program were identified. Assembly requirements were derived based on the SSM/PMAD developed requirements and on the selected SSM/PMAD network concepts. Basic requirements and simplified design block diagrams are included. DC remote power controllers were successfully integrated into the DC Marshall Space Flight Center breadboard. Two DC remote power controller (RPC) boards experienced mechanical failure of UES 706 stud-mounted diodes during mechanical installation of the boards into the system. These broken diodes caused input to output shorting of the RPC's. The UES 706 diodes were replaced on these RPC's which eliminated the problem. The DC RPC's as existing in the present breadboard configuration do not provide ground fault protection because the RPC was designed to only switch the hot side current. If ground fault protection were to be implemented, it would be necessary to design the system so the RPC switched both the hot and the return sides of power.

  18. Different types of laughter modulate connectivity within distinct parts of the laughter perception network.

    Wildgruber, Dirk; Szameitat, Diana P; Ethofer, Thomas; Brück, Carolin; Alter, Kai; Grodd, Wolfgang; Kreifelts, Benjamin

    2013-01-01

    Laughter is an ancient signal of social communication among humans and non-human primates. Laughter types with complex social functions (e.g., taunt and joy) presumably evolved from the unequivocal and reflex-like social bonding signal of tickling laughter already present in non-human primates. Here, we investigated the modulations of cerebral connectivity associated with different laughter types as well as the effects of attention shifts between implicit and explicit processing of social information conveyed by laughter using functional magnetic resonance imaging (fMRI). Complex social laughter types and tickling laughter were found to modulate connectivity in two distinguishable but partially overlapping parts of the laughter perception network irrespective of task instructions. Connectivity changes, presumably related to the higher acoustic complexity of tickling laughter, occurred between areas in the prefrontal cortex and the auditory association cortex, potentially reflecting higher demands on acoustic analysis associated with increased information load on auditory attention, working memory, evaluation and response selection processes. In contrast, the higher degree of socio-relational information in complex social laughter types was linked to increases of connectivity between auditory association cortices, the right dorsolateral prefrontal cortex and brain areas associated with mentalizing as well as areas in the visual associative cortex. These modulations might reflect automatic analysis of acoustic features, attention direction to informative aspects of the laughter signal and the retention of those in working memory during evaluation processes. These processes may be associated with visual imagery supporting the formation of inferences on the intentions of our social counterparts. Here, the right dorsolateral precentral cortex appears as a network node potentially linking the functions of auditory and visual associative sensory cortices with those of the

  19. Different types of laughter modulate connectivity within distinct parts of the laughter perception network.

    Dirk Wildgruber

    Full Text Available Laughter is an ancient signal of social communication among humans and non-human primates. Laughter types with complex social functions (e.g., taunt and joy presumably evolved from the unequivocal and reflex-like social bonding signal of tickling laughter already present in non-human primates. Here, we investigated the modulations of cerebral connectivity associated with different laughter types as well as the effects of attention shifts between implicit and explicit processing of social information conveyed by laughter using functional magnetic resonance imaging (fMRI. Complex social laughter types and tickling laughter were found to modulate connectivity in two distinguishable but partially overlapping parts of the laughter perception network irrespective of task instructions. Connectivity changes, presumably related to the higher acoustic complexity of tickling laughter, occurred between areas in the prefrontal cortex and the auditory association cortex, potentially reflecting higher demands on acoustic analysis associated with increased information load on auditory attention, working memory, evaluation and response selection processes. In contrast, the higher degree of socio-relational information in complex social laughter types was linked to increases of connectivity between auditory association cortices, the right dorsolateral prefrontal cortex and brain areas associated with mentalizing as well as areas in the visual associative cortex. These modulations might reflect automatic analysis of acoustic features, attention direction to informative aspects of the laughter signal and the retention of those in working memory during evaluation processes. These processes may be associated with visual imagery supporting the formation of inferences on the intentions of our social counterparts. Here, the right dorsolateral precentral cortex appears as a network node potentially linking the functions of auditory and visual associative sensory cortices

  20. Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion.

    Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-José; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmann, Helmut; Buchheim, Anna; Metzger, Coraline D; Nolte, Tobias; Walter, Martin

    2016-01-01

    Attachment patterns influence actions, thoughts and feeling through a person's "inner working model". Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic resonance imaging (fMRI)-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants' attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC) analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described "social aversion network" including dorsal anterior cingulated cortex (dACC) and left anterior middle temporal gyrus (aMTG) specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants' avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the "social aversion network", namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule (IPL). Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of

  1. Development of Active External Network Topology Module for Floodlight SDN Controller

    A. A. Noskov

    2015-01-01

    Full Text Available Traditional network architecture is inflexible and complicated. This observation has led to a paradigm shift towards software-defined networking (SDN, where network management level is separated from data forwarding level. This change was made possible by control plane transfer from the switching equipment to software modules that run on a dedicated server, called the controller (or network operating system, or network applications, that work with this controller. Methods of representation, storage and communication interfaces with network topology elements are the most important aspects of network operating systems available to SDN user because performance of some key controller modules is heavily dependent on internal representation of the network topology. Notably, firewall and routing modules are examples of such modules. This article describes the methods used for presentation and storage of network topologies, as well as interface to the corresponding Floodlight modules. An alternative algorithm has been suggested and developed for message exchange conveying network topology alterations between the controller and network applications. Proposed algorithm makes implementation of module alerting based on subscription to the relevant events. API for interaction between controller and network applications has been developed. This algorithm and API formed the base for Topology Tracker module capable to inform network applications about the changes that had occurred in the network topology and also stores compact representation of the network to speed up the interaction process.

  2. Country-overlapping radiation protection education and training by the CHERNE network; Laenderuebergreifende Strahlenschutzausbildung im Rahmen des CHERNE-Netzwerks

    Hoyler, Frieder [Fachhochschule Aachen, Juelich (Germany). Strahlenschutzkursstaette

    2013-09-01

    The CHERNE network is promoting the cooperation between colleges and research facilities at the training of students. The article describes particular study courses in the field of radiation protection. (orig.)

  3. Partially Overlapping Sensorimotor Networks Underlie Speech Praxis and Verbal Short-Term Memory: Evidence from Apraxia of Speech Following Acute Stroke

    Gregory eHickok

    2014-08-01

    Full Text Available We tested the hypothesis that motor planning and programming of speech articulation and verbal short-term memory (vSTM depend on partially overlapping networks of neural regions. We evaluated this proposal by testing 76 individuals with acute ischemic stroke for impairment in motor planning of speech articulation (apraxia of speech; AOS and vSTM in the first day of stroke, before the opportunity for recovery or reorganization of structure-function relationships. We also evaluate areas of both infarct and low blood flow that might have contributed to AOS or impaired vSTM in each person. We found that AOS was associated with tissue dysfunction in motor-related areas (posterior primary motor cortex, pars opercularis; premotor cortex, insula and sensory-related areas (primary somatosensory cortex, secondary somatosensory cortex, parietal operculum/auditory cortex; while impaired vSTM was associated with primarily motor-related areas (pars opercularis and pars triangularis, premotor cortex, and primary motor cortex. These results are consistent with the hypothesis, also supported by functional imaging data, that both speech praxis and vSTM rely on partially overlapping networks of brain regions.

  4. Partially overlapping sensorimotor networks underlie speech praxis and verbal short-term memory: evidence from apraxia of speech following acute stroke.

    Hickok, Gregory; Rogalsky, Corianne; Chen, Rong; Herskovits, Edward H; Townsley, Sarah; Hillis, Argye E

    2014-01-01

    We tested the hypothesis that motor planning and programming of speech articulation and verbal short-term memory (vSTM) depend on partially overlapping networks of neural regions. We evaluated this proposal by testing 76 individuals with acute ischemic stroke for impairment in motor planning of speech articulation (apraxia of speech, AOS) and vSTM in the first day of stroke, before the opportunity for recovery or reorganization of structure-function relationships. We also evaluated areas of both infarct and low blood flow that might have contributed to AOS or impaired vSTM in each person. We found that AOS was associated with tissue dysfunction in motor-related areas (posterior primary motor cortex, pars opercularis; premotor cortex, insula) and sensory-related areas (primary somatosensory cortex, secondary somatosensory cortex, parietal operculum/auditory cortex); while impaired vSTM was associated with primarily motor-related areas (pars opercularis and pars triangularis, premotor cortex, and primary motor cortex). These results are consistent with the hypothesis, also supported by functional imaging data, that both speech praxis and vSTM rely on partially overlapping networks of brain regions.

  5. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  6. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Jianfeng Xu

    Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  7. Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

  8. Dismissing attachment characteristics dynamically modulate brain networks subserving social aversion.

    Anna Linda eKrause

    2016-03-01

    Full Text Available Attachment patterns influence actions, thoughts and feeling through a person’s ‘Inner Working Model’. Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest fMRI-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants’ attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described ‘social aversion network’ including dorsal anterior cingulated cortex (dACC and left anterior middle temporal gyrus (aMTG specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants’ avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the ‘social aversion network’, namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule. Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of direct

  9. The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

    Krishnan, J. [Department of Chemical Engineering, Centre for Process Systems Engineering, Institute for Systems and Synthetic Biology, Imperial College London, London SW7 2AZ (United Kingdom); Mois, Kristina; Suwanmajo, Thapanar [Department of Chemical Engineering, Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)

    2014-11-07

    In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work, and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.

  10. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

    Li, Jun; Zhao, Patrick X

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.

  11. Automatic modulation format recognition for the next generation optical communication networks using artificial neural networks

    Guesmi, Latifa; Hraghi, Abir; Menif, Mourad

    2015-03-01

    A new technique for Automatic Modulation Format Recognition (AMFR) in next generation optical communication networks is presented. This technique uses the Artificial Neural Network (ANN) in conjunction with the features of Linear Optical Sampling (LOS) of the detected signal at high bit rates using direct detection or coherent detection. The use of LOS method for this purpose mainly driven by the increase of bit rates which enables the measurement of eye diagrams. The efficiency of this technique is demonstrated under different transmission impairments such as chromatic dispersion (CD) in the range of -500 to 500 ps/nm, differential group delay (DGD) in the range of 0-15 ps and the optical signal tonoise ratio (OSNR) in the range of 10-30 dB. The results of numerical simulation for various modulation formats demonstrate successful recognition from a known bit rates with a higher estimation accuracy, which exceeds 99.8%.

  12. Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

    Astegiano, Julia; Altermatt, Florian; Massol, François

    2017-11-13

    Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

  13. Overlapping clusters for distributed computation.

    Mirrokni, Vahab (Google Research, New York, NY); Andersen, Reid (Microsoft Corporation, Redmond, WA); Gleich, David F.

    2010-11-01

    Scalable, distributed algorithms must address communication problems. We investigate overlapping clusters, or vertex partitions that intersect, for graph computations. This setup stores more of the graph than required but then affords the ease of implementation of vertex partitioned algorithms. Our hope is that this technique allows us to reduce communication in a computation on a distributed graph. The motivation above draws on recent work in communication avoiding algorithms. Mohiyuddin et al. (SC09) design a matrix-powers kernel that gives rise to an overlapping partition. Fritzsche et al. (CSC2009) develop an overlapping clustering for a Schwarz method. Both techniques extend an initial partitioning with overlap. Our procedure generates overlap directly. Indeed, Schwarz methods are commonly used to capitalize on overlap. Elsewhere, overlapping communities (Ahn et al, Nature 2009; Mishra et al. WAW2007) are now a popular model of structure in social networks. These have long been studied in statistics (Cole and Wishart, CompJ 1970). We present two types of results: (i) an estimated swapping probability {rho}{infinity}; and (ii) the communication volume of a parallel PageRank solution (link-following {alpha} = 0.85) using an additive Schwarz method. The volume ratio is the amount of extra storage for the overlap (2 means we store the graph twice). Below, as the ratio increases, the swapping probability and PageRank communication volume decreases.

  14. Quetiapine modulates functional connectivity in brain aggression networks.

    Klasen, Martin; Zvyagintsev, Mikhail; Schwenzer, Michael; Mathiak, Krystyna A; Sarkheil, Pegah; Weber, René; Mathiak, Klaus

    2013-07-15

    Aggressive behavior is associated with dysfunctions in an affective regulation network encompassing amygdala and prefrontal areas such as orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC). In particular, prefrontal regions have been postulated to control amygdala activity by inhibitory projections, and this process may be disrupted in aggressive individuals. The atypical antipsychotic quetiapine successfully attenuates aggressive behavior in various disorders; the underlying neural processes, however, are unknown. A strengthened functional coupling in the prefrontal-amygdala system may account for these anti-aggressive effects. An inhibition of this network has been reported for virtual aggression in violent video games as well. However, there have been so far no in-vivo observations of pharmacological influences on corticolimbic projections during human aggressive behavior. In a double-blind, placebo-controlled study, quetiapine and placebo were administered for three successive days prior to an fMRI experiment. In this experiment, functional brain connectivity was assessed during virtual aggressive behavior in a violent video game and an aggression-free control task in a non-violent modification. Quetiapine increased the functional connectivity of ACC and DLPFC with the amygdala during virtual aggression, whereas OFC-amygdala coupling was attenuated. These effects were observed neither for placebo nor for the non-violent control. These results demonstrate for the first time a pharmacological modification of aggression-related human brain networks in a naturalistic setting. The violence-specific modulation of prefrontal-amygdala networks appears to control aggressive behavior and provides a neurobiological model for the anti-aggressive effects of quetiapine. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. Cluster-based single-sink wireless sensor networks and passive optical network converged network incorporating sideband modulation schemes

    Kumar, Love; Sharma, Vishal; Singh, Amarpal

    2018-02-01

    Wireless sensor networks have tremendous applications, such as civil, military, and environmental monitoring. In most of the applications, sensor data are required to be propagated over the internet/core networks, which result in backhaul setback. Subsequently, there is a necessity to backhaul the sensed information of such networks together with prolonging of the transmission link. Passive optical network (PON) is next-generation access technology emerging as a potential candidate for convergence of the sensed data to the core system. Earlier, the work with single-optical line terminal-PON was demonstrated and investigated merely analytically. This work is an attempt to demonstrate a practical model of a bidirectional single-sink wireless sensor network-PON converged network in which the collected data from cluster heads are transmitted over PON networks. Further, modeled converged structure has been investigated under the influence of double, single, and tandem sideband modulation schemes incorporating a corresponding phase-delay to the sensor data entities that have been overlooked in the past. The outcome illustrates the successful fusion of the sensor data entities over PON with acceptable bit error rate and signal to noise ratio serving as a potential development in the sphere of such converged networks. It has also been revealed that the data entities treated with tandem side band modulation scheme help in improving the performance of the converged structure. Additionally, analysis for uplink transmission reported with queue theory in terms of time cycle, average time delay, data packet generation, and bandwidth utilization. An analytical analysis of proposed converged network shows that average time delay for data packet transmission is less as compared with time cycle delay.

  16. Limited overlap between phylogenetic HIV and hepatitis C virus clusters illustrates the dynamic sexual network structure of Dutch HIV-infected MSM.

    Vanhommerig, Joost W; Bezemer, Daniela; Molenkamp, Richard; Van Sighem, Ard I; Smit, Colette; Arends, Joop E; Lauw, Fanny N; Brinkman, Kees; Rijnders, Bart J; Newsum, Astrid M; Bruisten, Sylvia M; Prins, Maria; Van Der Meer, Jan T; Van De Laar, Thijs J; Schinkel, Janke

    2017-09-24

    MSM are at increased risk for infection with HIV-1 and hepatitis C virus (HCV). Is HIV/HCV coinfection confined to specific HIV transmission networks? A HIV phylogenetic tree was constructed for 5038 HIV-1 subtype B polymerase (pol) sequences obtained from MSM in the AIDS therapy evaluation in the Netherlands cohort. We investigated the existence of HIV clusters with increased HCV prevalence, the HIV phylogenetic density (i.e. the number of potential HIV transmission partners) of HIV/HCV-coinfected MSM compared with HIV-infected MSM without HCV, and the overlap in HIV and HCV phylogenies using HCV nonstructural protein 5B sequences from 183 HIV-infected MSM with acute HCV infection. Five hundred and sixty-three of 5038 (11.2%) HIV-infected MSM tested HCV positive. Phylogenetic analysis revealed 93 large HIV clusters (≥10 MSM), 370 small HIV clusters (2-9 MSM), and 867 singletons with a median HCV prevalence of 11.5, 11.6, and 9.3%, respectively. We identified six large HIV clusters with elevated HCV prevalence (range 23.5-46.2%). Median HIV phylogenetic densities for MSM with HCV (3, interquartile range 1-7) and without HCV (3, interquartile range 1-8) were similar. HCV phylogeny showed 12 MSM-specific HCV clusters (clustersize: 2-39 HCV sequences); 12.7% of HCV infections were part of the same HIV and HCV cluster. We observed few HIV clusters with elevated HCV prevalence, no increase in the HIV phylogenetic density of HIV/HCV-coinfected MSM compared to HIV-infected MSM without HCV, and limited overlap between HIV and HCV phylogenies among HIV/HCV-coinfected MSM. Our data do not support the existence of MSM-specific sexual networks that fuel both the HIV and HCV epidemic.

  17. Pramipexole modulates the neural network of reward anticipation.

    Ye, Zheng; Hammer, Anke; Camara, Estela; Münte, Thomas F

    2011-05-01

    Pramipexole is widely prescribed to treat Parkinson's disease. It has been found to cause impulse control disorders such as pathological gambling. To examine how pramipexole modulates the network of reward anticipation, we carried out a pharmacological functional magnetic resonance imaging study with a double-blind, within-subject design. During the anticipation of monetary rewards, pramipexole increased the activity of the nucleus accumbens (NAcc), enhanced the interaction between the NAcc and the anterior insula, but weakened the interaction between the NAcc and the prefrontal cortex. These results suggest that pramipexole may exaggerate incentive and affective responses to possible rewards, but reduce the top-down control of impulses, leading to an increase in impulsive behaviors. This imbalance between the prefrontal-striatum connectivity and the insula-striatum connectivity may represent the neural mechanism of pathological gambling caused by pramipexole. Copyright © 2010 Wiley-Liss, Inc.

  18. Spinal cellular and network properties modulate pain perception

    Darbon Pascal

    2016-01-01

    Previously, it has been shown that high levels of plasma glucocorticoids give rise to analgesia. However to our knowledge nothing has been reported regarding a direct non genomic modulation of neuronal spinal activity by peripheral CORT. In the present study, we used combined in vivo and in vitro electrophysiology approaches, associated with the measure of nociceptive mechanical sensitivity and plasma corticosterone level measurement to assess the impact of circulating CORT on rat nociception. We showed that CORT plasma level elevation produced analgesia via the reduction of nociceptive fiber mediated spinal responses. CORT is spinally reduced in the neuroactive metabolite THDOC that specifically enhances lamina II GABAergic synaptic transmission. The main consequence is a reduction of lamina II network excitability reflecting a selective decrease in processing of nociceptive inputs. The depressed neuronal activity at the spinal level then in turn leads to a weaker nociceptive message transmission to supraspinal structures and hence to an alleviation of pain.

  19. Differential network analysis reveals genetic effects on catalepsy modules.

    Ovidiu D Iancu

    Full Text Available We performed short-term bi-directional selective breeding for haloperidol-induced catalepsy, starting from three mouse populations of increasingly complex genetic structure: an F2 intercross, a heterogeneous stock (HS formed by crossing four inbred strains (HS4 and a heterogeneous stock (HS-CC formed from the inbred strain founders of the Collaborative Cross (CC. All three selections were successful, with large differences in haloperidol response emerging within three generations. Using a custom differential network analysis procedure, we found that gene coexpression patterns changed significantly; importantly, a number of these changes were concordant across genetic backgrounds. In contrast, absolute gene-expression changes were modest and not concordant across genetic backgrounds, in spite of the large and similar phenotypic differences. By inferring strain contributions from the parental lines, we are able to identify significant differences in allelic content between the selected lines concurrent with large changes in transcript connectivity. Importantly, this observation implies that genetic polymorphisms can affect transcript and module connectivity without large changes in absolute expression levels. We conclude that, in this case, selective breeding acts at the subnetwork level, with the same modules but not the same transcripts affected across the three selections.

  20. OFDM with Index Modulation for Asynchronous mMTC Networks.

    Doğan, Seda; Tusha, Armed; Arslan, Hüseyin

    2018-04-21

    One of the critical missions for next-generation wireless communication systems is to fulfill the high demand for massive Machine-Type Communications (mMTC). In mMTC systems, a sporadic transmission is performed between machine users and base station (BS). Lack of coordination between the users and BS in time destroys orthogonality between the subcarriers, and causes inter-carrier interference (ICI). Therefore, providing services to asynchronous massive machine users is a major challenge for Orthogonal Frequency Division Multiplexing (OFDM). In this study, OFDM with index modulation (OFDM-IM) is proposed as an eligible solution to alleviate ICI caused by asynchronous transmission in uncoordinated mMTC networks. In OFDM-IM, data transmission is performed not only by modulated subcarriers but also by the indices of active subcarriers. Unlike classical OFDM, fractional subcarrier activation leads to less ICI in OFDM-IM technology. A novel subcarrier mapping scheme (SMS) named as Inner Subcarrier Activation is proposed to further alleviate adjacent user interference in asynchronous OFDM-IM-based systems. ISA reduces inter-user interference since it gives more activation priority to inner subcarriers compared with the existing SMS-s. The superiority of the proposed SMS is shown through both theoretical analysis and computer-based simulations in comparison to existing mapping schemes for asynchronous systems.

  1. Overlapping community detection using weighted consensus ...

    2016-09-21

    Sep 21, 2016 ... Complex networks; overlapping community; consensus clustering. PACS Nos 89.75 ... networks, a person may be in several social groups like family, friends ..... the social interactions between individuals in a karate club in an.

  2. Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks.

    Du, Yuhui; Liu, Jingyu; Sui, Jing; He, Hao; Pearlson, Godfrey D; Calhoun, Vince D

    2014-01-01

    Schizophrenia, schizoaffective and bipolar disorders share some common symptoms. However, the biomarkers underlying those disorders remain unclear. In fact, there is still controversy about the schizoaffective disorder with respect to its validity of independent category and its relationship with schizophrenia and bipolar disorders. In this paper, based on brain functional networks extracted from resting-state fMRI using a recently proposed group information guided ICA (GIG-ICA) method, we explore the biomarkers for discriminating healthy controls, schizophrenia patients, bipolar patients, and patients with two symptom defined subsets of schizoaffective disorder, and then investigate the relationship between different groups. The results demonstrate that the discriminating regions mainly including frontal, parietal, precuneus, cingulate, supplementary motor, cerebellar, insular and supramarginal cortices perform well in distinguishing the different diagnostic groups. The results also suggest that schizoaffective disorder may be an independent disorder, although its subtype characterized by depressive episodes shares more similarity with schizophrenia.

  3. Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

    Chen Xiaoyu

    2007-12-01

    Full Text Available Abstract Background In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression. Results We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure. Conclusion Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.

  4. Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

    Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

    2018-05-01

    Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

  5. A core eating network and its modulations underlie diverse eating phenomena

    Chen, Jing|info:eu-repo/dai/nl/411887548; Papies, Esther K.|info:eu-repo/dai/nl/304832766; Barsalou, Lawrence W.

    2016-01-01

    We propose that a core eating network and its modulations account for much of what is currently known about the neural activity underlying a wide range of eating phenomena in humans (excluding homeostasis and related phenomena). The core eating network is closely adapted from a network that Kaye,

  6. Improving functional modules discovery by enriching interaction networks with gene profiles

    Salem, Saeed

    2013-05-01

    Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.

  7. Network statistics of genetically-driven gene co-expression modules in mouse crosses

    Marie-Pier eScott-Boyer

    2013-12-01

    Full Text Available In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS. For six out of the 7 networks, we found that linkage to module QTLs (mQTLs could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as genetically-driven had network statistic properties (density, centralization and heterogeneity that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

  8. Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

    Oyang Yen-Jen

    2010-10-01

    Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

  9. RM-SORN: a reward-modulated self-organizing recurrent neural network.

    Aswolinskiy, Witali; Pipa, Gordon

    2015-01-01

    Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

  10. A fuzzy network module extraction technique for gene expression data

    2014-05-01

    expression network from the distance matrix. The distance matrix is .... mental process, cellular component assembly involved in ..... the molecules are present in the network. User can ... hsa05213:Endometrial cancer. 24. 0.07.

  11. OVERLAPPING VIRTUAL CADASTRAL DOCUMENTATION

    Madalina - Cristina Marian

    2013-12-01

    Full Text Available Two cadastrale plans of buildings, can overlap virtual. Overlap is highlighted when digital reception. According to Law no. 7/1996 as amended and supplemented, to solve these problems is by updating the database graphs, the repositioning. This paper addresses the issue of overlapping virtual cadastre in the history of the period 1999-2012.

  12. Advanced Modulation Formats in Cognitive Optical Networks: EU project CHRON Demonstration

    Borkowski, Robert; Caballero Jambrina, Antonio; Klonidis, Dimitris

    2014-01-01

    We demonstrate real-time path establishment and switching of coherent modulation formats (QPSK, 16QAM) within an optical network driven by cognitive algorithms. Cognition aims at autonomous configuration optimization to satisfy quality of transmission requirements.......We demonstrate real-time path establishment and switching of coherent modulation formats (QPSK, 16QAM) within an optical network driven by cognitive algorithms. Cognition aims at autonomous configuration optimization to satisfy quality of transmission requirements....

  13. Ecological modules and roles of species in heathland plant-insect flower visitor networks

    Dupont, Yoko; Olesen, Jens Mogens

    2009-01-01

    1.  Co-existing plants and flower-visiting animals often form complex interaction networks. A long-standing question in ecology and evolutionary biology is how to detect nonrandom subsets (compartments, blocks, modules) of strongly interacting species within such networks. Here we use a network...... analytical approach to (i) detect modularity in pollination networks, (ii) investigate species composition of modules, and (iii) assess the stability of modules across sites. 2.  Interactions between entomophilous plants and their flower-visitors were recorded throughout the flowering season at three...... heathland sites in Denmark, separated by ≥ 10 km. Among sites, plant communities were similar, but composition of flower-visiting insect faunas differed. Visitation frequencies of visitor species were recorded as a measure of insect abundance. 3.  Qualitative (presence-absence) interaction networks were...

  14. Development of a diagnostic system for Klystron modulators using a neural network

    Mutoh, M.; Oonuma, T.; Shibasaki, Y.; Abe, I.; Nakahara, K.

    1992-01-01

    The diagnostic system for klystron modulators using a neural network has been developed. Large changes in the voltage and current of the main circuit in a klystron modulator were observed just several ten milli-seconds before the modulator experienced trouble. These changes formed a peculiar pattern that depended on the parts with problems. Diagnosis was possible by means of pattern recognition. The recognition test of patterns using a neutral network has shown good results. This system, which is built in a linac control system, is presently being operated so as to collect new trouble patterns and to carry out tests for practical use. (author)

  15. Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

    Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

    2017-10-03

    With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

  16. Robustness and modular structure in networks

    Bagrow, James P.; Lehmann, Sune; Ahn, Yong-Yeol

    2015-01-01

    -12]. Many complex systems, from power grids and the Internet to the brain and society [13-15], can be modeled using modular networks comprised of small, densely connected groups of nodes [16, 17]. These modules often overlap, with network elements belonging to multiple modules [18, 19]. Yet existing work...... on robustness has not considered the role of overlapping, modular structure. Here we study the robustness of these systems to the failure of elements. We show analytically and empirically that it is possible for the modules themselves to become uncoupled or non-overlapping well before the network disintegrates....... If overlapping modular organization plays a role in overall functionality, networks may be far more vulnerable than predicted by conventional percolation theory....

  17. Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis.

    Hu, Xueping; Wang, Xiangpeng; Gu, Yan; Luo, Pei; Yin, Shouhang; Wang, Lijun; Fu, Chao; Qiao, Lei; Du, Yi; Chen, Antao

    2017-10-01

    Numerous behavioral studies have found a modulation effect of phonological experience on voice discrimination. However, the neural substrates underpinning this phenomenon are poorly understood. Here we manipulated language familiarity to test the hypothesis that phonological experience affects voice discrimination via mediating the engagement of multiple perceptual and cognitive resources. The results showed that during voice discrimination, the activation of several prefrontal regions was modulated by language familiarity. More importantly, the same effect was observed concerning the functional connectivity from the fronto-parietal network to the voice-identity network (VIN), and from the default mode network to the VIN. Our findings indicate that phonological experience could bias the recruitment of cognitive control and information retrieval/comparison processes during voice discrimination. Therefore, the study unravels the neural substrates subserving the modulation effect of phonological experience on voice discrimination, and provides new insights into studying voice discrimination from the perspective of network interactions. Copyright © 2017. Published by Elsevier Inc.

  18. Linux containers networking: performance and scalability of kernel modules

    Claassen, J.; Koning, R.; Grosso, P.; Oktug Badonnel, S.; Ulema, M.; Cavdar, C.; Zambenedetti Granville, L.; dos Santos, C.R.P.

    2016-01-01

    Linux container virtualisation is gaining momentum as lightweight technology to support cloud and distributed computing. Applications relying on container architectures might at times rely on inter-container communication, and container networking solutions are emerging to address this need.

  19. State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

    Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

    2011-11-16

    The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

  20. Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

    He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

    2012-06-25

    Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the

  1. Hierarchical surface code for network quantum computing with modules of arbitrary size

    Li, Ying; Benjamin, Simon C.

    2016-10-01

    The network paradigm for quantum computing involves interconnecting many modules to form a scalable machine. Typically it is assumed that the links between modules are prone to noise while operations within modules have a significantly higher fidelity. To optimize fault tolerance in such architectures we introduce a hierarchical generalization of the surface code: a small "patch" of the code exists within each module and constitutes a single effective qubit of the logic-level surface code. Errors primarily occur in a two-dimensional subspace, i.e., patch perimeters extruded over time, and the resulting noise threshold for intermodule links can exceed ˜10 % even in the absence of purification. Increasing the number of qubits within each module decreases the number of qubits necessary for encoding a logical qubit. But this advantage is relatively modest, and broadly speaking, a "fine-grained" network of small modules containing only about eight qubits is competitive in total qubit count versus a "course" network with modules containing many hundreds of qubits.

  2. Asymmetrical Modulation for Uplink Communication in Cooperative Networks

    Zhang, Qi; Fitzek, Frank H.P.; Iversen, Villy Bæk

    2008-01-01

    -range links with neighboring mobile devices to form cooperative clusters. So far the physical communication over cellular links and over short-range links are separated in time or in frequency. Beyond this state of the art, we exploit a method, referred to as asymmetrical modulation, where a mobile device...

  3. Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion

    Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-Jose; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmanny, Helmut; Buchheim, Anna; Metzger, Coraline D.; Nolte, Tobias; Walter, Martin

    2016-01-01

    Attachment patterns influence actions, thoughts and feeling through a person's "inner working model". Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic

  4. Characterisation of PV CIS module by artificial neural networks. A comparative study with other methods

    Almonacid, F.; Rus, C.; Hontoria, L.; Munoz, F.J.

    2010-01-01

    The presence of PV modules made with new technologies and materials is increasing in PV market, in special Thin Film Solar Modules (TFSM). They are ready to make a substantial contribution to the world's electricity generation. Although Si wafer-based cells account for the most of increase, technologies of thin film have been those of the major growth in last three years. During 2007 they grew 133%. On the other hand, manufacturers provide ratings for PV modules for conditions referred to as Standard Test Conditions (STC). However, these conditions rarely occur outdoors, so the usefulness and applicability of the indoors characterisation in standard test conditions of PV modules is a controversial issue. Therefore, to carry out a correct photovoltaic engineering, a suitable characterisation of PV module electrical behaviour is necessary. The IDEA Research Group from Jaen University has developed a method based on artificial neural networks (ANNs) to electrical characterisation of PV modules. An ANN was able to generate V-I curves of si-crystalline PV modules for any irradiance and module cell temperature. The results show that the proposed ANN introduces a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method is going to be applied for electrical characterisation of PV CIS modules. Finally, a comparative study with other methods, of electrical characterisation, is done. (author)

  5. Sleep overlap syndrome

    Fariba Rezaeetalab

    2016-12-01

    Full Text Available Overlap syndrome, which is known as the coexistence of chronic obstructive pulmonary disease (COPD and obstructive sleep apnea (OSA, was first defined by Flenley. Although it can refer to concomitant occurrence of any of the pulmonary diseases and OSA, overlap syndrome is commonly considered as the coexistence of OSA and COPD. This disease has unique adverse health consequences distinct from either condition alone. Given the high prevalence of each solitary disease, overlap syndrome is also likely to be common and clinically relevant. Despite the fact that overlap syndrome has been described in the literature for nearly 30 years, paucity of evaluations and studies limited the discussion on diagnosis, prevalence, pathophysiology, treatment, and outcomes of this disease. This review article addresses these issues by reviewing several recent studies conducted in Iran or other countries. This review suggests that overlap syndrome has worse outcomes than either disease alone. Our findings accentuated the urgent need for further studies on overlap syndrome and all overlaps between OSA and chronic pulmonary disease to provide a deeper insight into diagnosis and non-invasive treatments of this disease.

  6. Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

    de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

    2015-08-01

    Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

  7. CommWalker: correctly evaluating modules in molecular networks in light of annotation bias.

    Luecken, M D; Page, M J T; Crosby, A J; Mason, S; Reinert, G; Deane, C M

    2018-03-15

    Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins. We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker's ability to overcome annotation bias using input communities from four community detection methods on two protein interaction networks. We find that modules accepted by CommWalker are similarly co-expressed as those accepted by current methods. Crucially, CommWalker performs well not only in well-annotated regions, but also in regions otherwise obscured by poor annotation. CommWalker community prioritization both faithfully captures well-validated communities and identifies functional modules that may correspond to more novel biology. The CommWalker algorithm is freely available at opig.stats.ox.ac.uk/resources or as a docker image on the Docker Hub at hub.docker.com/r/lueckenmd/commwalker/. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online.

  8. Action Potential Modulation of Neural Spin Networks Suggests Possible Role of Spin

    Hu, H P

    2004-01-01

    In this paper we show that nuclear spin networks in neural membranes are modulated by action potentials through J-coupling, dipolar coupling and chemical shielding tensors and perturbed by microscopically strong and fluctuating internal magnetic fields produced largely by paramagnetic oxygen. We suggest that these spin networks could be involved in brain functions since said modulation inputs information carried by the neural spike trains into them, said perturbation activates various dynamics within them and the combination of the two likely produce stochastic resonance thus synchronizing said dynamics to the neural firings. Although quantum coherence is desirable and may indeed exist, it is not required for these spin networks to serve as the subatomic components for the conventional neural networks.

  9. A smart modules network for real time data acquisition: application to biomedical research.

    Logier, R; De jonckheere, J; Dassonneville, A; Chaud, P; Jeanne, M

    2009-01-01

    Healthcare monitoring applications require the measurement and the analysis of multiple physiological data. In the field of biomedical research, these data are issued from different devices involving data centralization and synchronization difficulties. In this paper, we describe a smart hardware modules network for biomedical data real time acquisition. This toolkit, composed of multiple electronic modules, allows users to acquire and transmit all kind of biomedical signals and parameters. These highly efficient hardware modules have been developed and tested especially for biomedical studies and used in a large number of clinical investigations.

  10. Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia.

    Ding, Junhua; Chen, Keliang; Zhang, Weibin; Li, Ming; Chen, Yan; Yang, Qing; Lv, Yingru; Guo, Qihao; Han, Zaizhu

    2017-01-01

    Semantic dementia (SD) is characterized by a selective decline in semantic processing. Although the neuropsychological pattern of this disease has been identified, its topological global alterations and symptom-relevant modules in the whole-brain anatomical network have not been fully elucidated. This study aims to explore the topological alteration of anatomical network in SD and reveal the modules associated with semantic deficits in this disease. We first constructed the whole-brain white-matter networks of 20 healthy controls and 19 patients with SD. Then, the network metrics of graph theory were compared between these two groups. Finally, we separated the network of SD patients into different modules and correlated the structural integrity of each module with the severity of the semantic deficits across patients. The network of the SD patients presented a significantly reduced global efficiency, indicating that the long-distance connections were damaged. The network was divided into the following four distinctive modules: the left temporal/occipital/parietal, frontal, right temporal/occipital, and frontal/parietal modules. The first two modules were associated with the semantic deficits of SD. These findings illustrate the skeleton of the neuroanatomical network of SD patients and highlight the key role of the left temporal/occipital/parietal module and the left frontal module in semantic processing.

  11. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

    Rosenberg, Monica D.; Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S.; Shen, Xilin; Constable, R. Todd; Li, Chiang-Shan R.; Chun, Marvin M.

    2016-01-01

    Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained...

  12. Network Structure as a Modulator of Disturbance Impacts in Streams

    Warner, S.; Tullos, D. D.

    2017-12-01

    This study examines how river network structure affects the propagation of geomorphic and anthropogenic disturbances through streams. Geomorphic processes such as debris flows can alter channel morphology and modify habitat for aquatic biota. Anthropogenic disturbances such as road construction can interact with the geomorphology and hydrology of forested watersheds to change sediment and water inputs to streams. It was hypothesized that the network structure of streams within forested watersheds would influence the location and magnitude of the impacts of debris flows and road construction on sediment size and channel width. Longitudinal surveys were conducted every 50 meters for 11 kilometers of third-to-fifth order streams in the H.J. Andrews Experimental Forest in the Western Cascade Range of Oregon. Particle counts and channel geometry measurements were collected to characterize the geomorphic impacts of road crossings and debris flows as disturbances. Sediment size distributions and width measurements were plotted against the distance of survey locations through the network to identify variations in longitudinal trends of channel characteristics. Thresholds for the background variation in sediment size and channel width, based on the standard deviations of sample points, were developed for sampled stream segments characterized by location as well as geomorphic and land use history. Survey locations were classified as "disturbed" when they deviated beyond the reference thresholds in expected sediment sizes and channel widths, as well as flow-connected proximity to debris flows and road crossings. River network structure was quantified by drainage density and centrality of nodes upstream of survey locations. Drainage density and node centrality were compared between survey locations with similar channel characteristic classifications. Cluster analysis was used to assess the significance of survey location, proximity of survey location to debris flows and road

  13. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Recep Colak

    2010-10-01

    Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

  14. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

    2010-10-25

    Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

  15. Resveratrol modulates the inflammatory response via an estrogen receptor-signal integration network

    Nwachukwu, Jerome C; Srinivasan, Sathish; Bruno, Nelson E; Parent, Alexander A; Hughes, Travis S; Pollock, Julie A; Gjyshi, Olsi; Cavett, Valerie; Nowak, Jason; Garcia-Ordonez, Ruben D; Houtman, René; Griffin, Patrick R; Kojetin, Douglas J; Katzenellenbogen, John A; Conkright, Michael D; Nettles, Kendall W

    2014-01-01

    Resveratrol has beneficial effects on aging, inflammation and metabolism, which are thought to result from activation of the lysine deacetylase, sirtuin 1 (SIRT1), the cAMP pathway, or AMP-activated protein kinase. In this study, we report that resveratrol acts as a pathway-selective estrogen receptor-α (ERα) ligand to modulate the inflammatory response but not cell proliferation. A crystal structure of the ERα ligand-binding domain (LBD) as a complex with resveratrol revealed a unique perturbation of the coactivator-binding surface, consistent with an altered coregulator recruitment profile. Gene expression analyses revealed significant overlap of TNFα genes modulated by resveratrol and estradiol. Furthermore, the ability of resveratrol to suppress interleukin-6 transcription was shown to require ERα and several ERα coregulators, suggesting that ERα functions as a primary conduit for resveratrol activity. DOI: http://dx.doi.org/10.7554/eLife.02057.001 PMID:24771768

  16. Leveraging disjoint communities for detecting overlapping community structure

    Chakraborty, Tanmoy

    2015-01-01

    Network communities represent mesoscopic structure for understanding the organization of real-world networks, where nodes often belong to multiple communities and form overlapping community structure in the network. Due to non-triviality in finding the exact boundary of such overlapping communities, this problem has become challenging, and therefore huge effort has been devoted to detect overlapping communities from the network.In this paper, we present PVOC (Permanence based Vertex-replication algorithm for Overlapping Community detection), a two-stage framework to detect overlapping community structure. We build on a novel observation that non-overlapping community structure detected by a standard disjoint community detection algorithm from a network has high resemblance with its actual overlapping community structure, except the overlapping part. Based on this observation, we posit that there is perhaps no need of building yet another overlapping community finding algorithm; but one can efficiently manipulate the output of any existing disjoint community finding algorithm to obtain the required overlapping structure. We propose a new post-processing technique that by combining with any existing disjoint community detection algorithm, can suitably process each vertex using a new vertex-based metric, called permanence, and thereby finds out overlapping candidates with their community memberships. Experimental results on both synthetic and large real-world networks show that PVOC significantly outperforms six state-of-the-art overlapping community detection algorithms in terms of high similarity of the output with the ground-truth structure. Thus our framework not only finds meaningful overlapping communities from the network, but also allows us to put an end to the constant effort of building yet another overlapping community detection algorithm. (paper)

  17. Analysis on voltage stability of PFN in modulator using De-Qing network

    Wang Dong; Zhang Yongming; Zhu Fuquan

    1987-01-01

    Using the numerical simulation of PFN charging circuit and De-Qing network, a study of voltage stability of BEPC 80 MW klystron pulse modulator has been carried out. The results presented in the paper indicate the quantitative correlation between leakage inductance and voltage stability

  18. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular networks

    R. Colak; F. Moser; J. Shu; A. Schönhuth (Alexander); N. Chen; M. Ester

    2010-01-01

    htmlabstractBackground Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not

  19. A Scalable Permutation Approach Reveals Replication and Preservation Patterns of Network Modules in Large Datasets.

    Ritchie, Scott C; Watts, Stephen; Fearnley, Liam G; Holt, Kathryn E; Abraham, Gad; Inouye, Michael

    2016-07-01

    Network modules-topologically distinct groups of edges and nodes-that are preserved across datasets can reveal common features of organisms, tissues, cell types, and molecules. Many statistics to identify such modules have been developed, but testing their significance requires heuristics. Here, we demonstrate that current methods for assessing module preservation are systematically biased and produce skewed p values. We introduce NetRep, a rapid and computationally efficient method that uses a permutation approach to score module preservation without assuming data are normally distributed. NetRep produces unbiased p values and can distinguish between true and false positives during multiple hypothesis testing. We use NetRep to quantify preservation of gene coexpression modules across murine brain, liver, adipose, and muscle tissues. Complex patterns of multi-tissue preservation were revealed, including a liver-derived housekeeping module that displayed adipose- and muscle-specific association with body weight. Finally, we demonstrate the broader applicability of NetRep by quantifying preservation of bacterial networks in gut microbiota between men and women. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

  20. Experimental demonstration of large capacity WSDM optical access network with multicore fibers and advanced modulation formats.

    Li, Borui; Feng, Zhenhua; Tang, Ming; Xu, Zhilin; Fu, Songnian; Wu, Qiong; Deng, Lei; Tong, Weijun; Liu, Shuang; Shum, Perry Ping

    2015-05-04

    Towards the next generation optical access network supporting large capacity data transmission to enormous number of users covering a wider area, we proposed a hybrid wavelength-space division multiplexing (WSDM) optical access network architecture utilizing multicore fibers with advanced modulation formats. As a proof of concept, we experimentally demonstrated a WSDM optical access network with duplex transmission using our developed and fabricated multicore (7-core) fibers with 58.7km distance. As a cost-effective modulation scheme for access network, the optical OFDM-QPSK signal has been intensity modulated on the downstream transmission in the optical line terminal (OLT) and it was directly detected in the optical network unit (ONU) after MCF transmission. 10 wavelengths with 25GHz channel spacing from an optical comb generator are employed and each wavelength is loaded with 5Gb/s OFDM-QPSK signal. After amplification, power splitting, and fan-in multiplexer, 10-wavelength downstream signal was injected into six outer layer cores simultaneously and the aggregation downstream capacity reaches 300 Gb/s. -16 dBm sensitivity has been achieved for 3.8 × 10-3 bit error ratio (BER) with 7% Forward Error Correction (FEC) limit for all wavelengths in every core. Upstream signal from ONU side has also been generated and the bidirectional transmission in the same core causes negligible performance degradation to the downstream signal. As a universal platform for wired/wireless data access, our proposed architecture provides additional dimension for high speed mobile signal transmission and we hence demonstrated an upstream delivery of 20Gb/s per wavelength with QPSK modulation formats using the inner core of MCF emulating a mobile backhaul service. The IQ modulated data was coherently detected in the OLT side. -19 dBm sensitivity has been achieved under the FEC limit and more than 18 dB power budget is guaranteed.

  1. Network modules uncover mechanisms of skeletal muscle dysfunction in COPD patients

    Ákos Tényi

    2018-02-01

    Full Text Available Abstract Background Chronic obstructive pulmonary disease (COPD patients often show skeletal muscle dysfunction that has a prominent negative impact on prognosis. The study aims to further explore underlying mechanisms of skeletal muscle dysfunction as a characteristic systemic effect of COPD, potentially modifiable with preventive interventions (i.e. muscle training. The research analyzes network module associated pathways and evaluates the findings using independent measurements. Methods We characterized the transcriptionally active network modules of interacting proteins in the vastus lateralis of COPD patients (n = 15, FEV1 46 ± 12% pred, age 68 ± 7 years and healthy sedentary controls (n = 12, age 65 ± 9  years, at rest and after an 8-week endurance training program. Network modules were functionally evaluated using experimental data derived from the same study groups. Results At baseline, we identified four COPD specific network modules indicating abnormalities in creatinine metabolism, calcium homeostasis, oxidative stress and inflammatory responses, showing statistically significant associations with exercise capacity (VO2 peak, Watts peak, BODE index and blood lactate levels (P < 0.05 each, but not with lung function (FEV1. Training-induced network modules displayed marked differences between COPD and controls. Healthy subjects specific training adaptations were significantly associated with cell bioenergetics (P < 0.05 which, in turn, showed strong relationships with training-induced plasma metabolomic changes; whereas, effects of training in COPD were constrained to muscle remodeling. Conclusion In summary, altered muscle bioenergetics appears as the most striking finding, potentially driving other abnormal skeletal muscle responses. Trial registration The study was based on a retrospectively registered trial (May 2017, ClinicalTrials.gov identifier: NCT03169270

  2. Acoustic richness modulates the neural networks supporting intelligible speech processing.

    Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E

    2016-03-01

    The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high. Copyright © 2015 Elsevier

  3. Learning related modulation of functional retrieval networks in man.

    Petersson, K M; Sandblom, J; Gisselgård, J; Ingvar, M

    2001-07-01

    The medial temporal lobe has been implicated in studies of episodic memory tasks involving spatio-temporal context and object-location conjunctions. We have previously demonstrated that an increased level of practice in a free-recall task parallels a decrease in the functional activity of several brain regions, including the medial temporal lobe, the prefrontal, the anterior cingulate, the anterior insular, and the posterior parietal cortices, that in concert demonstrate a move from elaborate controlled processing towards a higher degree of automaticity. Here we report data from two experiments that extend these initial observations. We used a similar experimental approach but probed for effects of retrieval paradigms and stimulus material. In the first experiment we investigated practice related changes during recognition of object-location conjunctions and in the second during free-recall of pseudo-words. Learning in a neural network is a dynamic consequence of information processing and network plasticity. The present and previous PET results indicate that practice can induce a learning related functional restructuring of information processing. Different adaptive processes likely subserve the functional re-organisation observed. These may in part be related to different demands for attentional and working memory processing. It appears that the role(s) of the prefrontal cortex and the medial temporal lobe in memory retrieval are complex, perhaps reflecting several different interacting processes or cognitive components. We suggest that an integrative interactive perspective on the role of the prefrontal and medial temporal lobe is necessary for an understanding of the processing significance of these regions in learning and memory. It appears necessary to develop elaborated and explicit computational models for prefrontal and medial temporal functions in order to derive detailed empirical predictions, and in combination with an efficient use and development of

  4. Performance evaluation of multilevel modulation formats using partial response for capacity upgrade in access network with limited electronic bandwidth

    Madsen, Peter; Suhr, Lau Frejstrup; Rodríguez Páez, Juan Sebastián

    2016-01-01

    We present a successful experimental evaluation of 4 level Pulse Amplitude Modulation (4-PAM) and Duobinary modulation. An experimental performance evaluation is presented for Duobinary 4 PAM and other modulation formats. All modulation formants used, may be considered to be implemented in future...... Passive Optical Network (PON) class access networks with limited electrical bandwidth. We compared NRZ, Duobinary, 4-PAM and Duobinary 4-PAM operating at 9 Gbaud over 20 km single mode fiber. The results provides an insight and guidelines on the utilization of these advanced modulation formats....

  5. Short-term PV/T module temperature prediction based on PCA-RBF neural network

    Li, Jiyong; Zhao, Zhendong; Li, Yisheng; Xiao, Jing; Tang, Yunfeng

    2018-02-01

    Aiming at the non-linearity and large inertia of temperature control in PV/T system, short-term temperature prediction of PV/T module is proposed, to make the PV/T system controller run forward according to the short-term forecasting situation to optimize control effect. Based on the analysis of the correlation between PV/T module temperature and meteorological factors, and the temperature of adjacent time series, the principal component analysis (PCA) method is used to pre-process the original input sample data. Combined with the RBF neural network theory, the simulation results show that the PCA method makes the prediction accuracy of the network model higher and the generalization performance stronger than that of the RBF neural network without the main component extraction.

  6. Hardware Module for the Security Enhancement of Optical Telecom Network Equipment

    Nadeem; Ali, M.

    2015-01-01

    The telecommunication equipment physical security threats have increased not only in Pakistan but also anywhere in the world and hence, reducing the revenue. This new challenging and alarming situation is created for the telecom network provider. The main focus of this paper is to provide a low cost economical design for reducing the theft of the costly telecommunication equipment like optical network units (ONU). This system is based on instant messaging on the mobile in the event of theft through GSM modem. The proposed security module is dynamic, flexible and can also be integrated in the existing networks and separately having its own independent low power consumption source. The module will continuously work successfully under different scenarios such as completely isolated from other devices by power break down or by fibre cut. (author)

  7. Illusion induced overlapped optics.

    Zang, XiaoFei; Shi, Cheng; Li, Zhou; Chen, Lin; Cai, Bin; Zhu, YiMing; Zhu, HaiBin

    2014-01-13

    The traditional transformation-based cloak seems like it can only hide objects by bending the incident electromagnetic waves around the hidden region. In this paper, we prove that invisible cloaks can be applied to realize the overlapped optics. No matter how many in-phase point sources are located in the hidden region, all of them can overlap each other (this can be considered as illusion effect), leading to the perfect optical interference effect. In addition, a singular parameter-independent cloak is also designed to obtain quasi-overlapped optics. Even more amazing of overlapped optics is that if N identical separated in-phase point sources covered with the illusion media, the total power outside the transformation region is N2I0 (not NI0) (I0 is the power of just one point source, and N is the number point sources), which seems violating the law of conservation of energy. A theoretical model based on interference effect is proposed to interpret the total power of these two kinds of overlapped optics effects. Our investigation may have wide applications in high power coherent laser beams, and multiple laser diodes, and so on.

  8. Dynamics of neuromodulatory feedback determines frequency modulation in a reduced respiratory network: a computational study.

    Toporikova, Natalia; Butera, Robert J

    2013-02-01

    Neuromodulators, such as amines and neuropeptides, alter the activity of neurons and neuronal networks. In this work, we investigate how neuromodulators, which activate G(q)-protein second messenger systems, can modulate the bursting frequency of neurons in a critical portion of the respiratory neural network, the pre-Bötzinger complex (preBötC). These neurons are a vital part of the ponto-medullary neuronal network, which generates a stable respiratory rhythm whose frequency is regulated by neuromodulator release from the nearby Raphe nucleus. Using a simulated 50-cell network of excitatory preBötC neurons with a heterogeneous distribution of persistent sodium conductance and Ca(2+), we determined conditions for frequency modulation in such a network by simulating interaction between Raphe and preBötC nuclei. We found that the positive feedback between the Raphe excitability and preBötC activity induces frequency modulation in the preBötC neurons. In addition, the frequency of the respiratory rhythm can be regulated via phasic release of excitatory neuromodulators from the Raphe nucleus. We predict that the application of a G(q) antagonist will eliminate this frequency modulation by the Raphe and keep the network frequency constant and low. In contrast, application of a G(q) agonist will result in a high frequency for all levels of Raphe stimulation. Our modeling results also suggest that high [K(+)] requirement in respiratory brain slice experiments may serve as a compensatory mechanism for low neuromodulatory tone. Copyright © 2012 Elsevier B.V. All rights reserved.

  9. Identifying colon cancer risk modules with better classification performance based on human signaling network.

    Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

    2014-10-01

    Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

  10. Socio-Cognitive Phenotypes Differentially Modulate Large-Scale Structural Covariance Networks.

    Valk, Sofie L; Bernhardt, Boris C; Böckler, Anne; Trautwein, Fynn-Mathis; Kanske, Philipp; Singer, Tania

    2017-02-01

    Functional neuroimaging studies have suggested the existence of 2 largely distinct social cognition networks, one for theory of mind (taking others' cognitive perspective) and another for empathy (sharing others' affective states). To address whether these networks can also be dissociated at the level of brain structure, we combined behavioral phenotyping across multiple socio-cognitive tasks with 3-Tesla MRI cortical thickness and structural covariance analysis in 270 healthy adults, recruited across 2 sites. Regional thickness mapping only provided partial support for divergent substrates, highlighting that individual differences in empathy relate to left insular-opercular thickness while no correlation between thickness and mentalizing scores was found. Conversely, structural covariance analysis showed clearly divergent network modulations by socio-cognitive and -affective phenotypes. Specifically, individual differences in theory of mind related to structural integration between temporo-parietal and dorsomedial prefrontal regions while empathy modulated the strength of dorsal anterior insula networks. Findings were robust across both recruitment sites, suggesting generalizability. At the level of structural network embedding, our study provides a double dissociation between empathy and mentalizing. Moreover, our findings suggest that structural substrates of higher-order social cognition are reflected rather in interregional networks than in the the local anatomical markup of specific regions per se. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Energy-efficient routing, modulation and spectrum allocation in elastic optical networks

    Tan, Yanxia; Gu, Rentao; Ji, Yuefeng

    2017-07-01

    With tremendous growth in bandwidth demand, energy consumption problem in elastic optical networks (EONs) becomes a hot topic with wide concern. The sliceable bandwidth-variable transponder in EON, which can transmit/receive multiple optical flows, was recently proposed to improve a transponder's flexibility and save energy. In this paper, energy-efficient routing, modulation and spectrum allocation (EE-RMSA) in EONs with sliceable bandwidth-variable transponder is studied. To decrease the energy consumption, we develop a Mixed Integer Linear Programming (MILP) model with corresponding EE-RMSA algorithm for EONs. The MILP model jointly considers the modulation format and optical grooming in the process of routing and spectrum allocation with the objective of minimizing the energy consumption. With the help of genetic operators, the EE-RMSA algorithm iteratively optimizes the feasible routing path, modulation format and spectrum resources solutions by explore the whole search space. In order to save energy, the optical-layer grooming strategy is designed to transmit the lightpath requests. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the blocking probability (BP) performance compare with the existing First-Fit-KSP algorithm, Iterative Flipping algorithm and EAMGSP algorithm especially in large network topology. Our results also demonstrate that the proposed EE-RMSA algorithm achieves almost the same performance as MILP on an 8-node network.

  12. EEG Oscillations Are Modulated in Different Behavior-Related Networks during Rhythmic Finger Movements.

    Seeber, Martin; Scherer, Reinhold; Müller-Putz, Gernot R

    2016-11-16

    Sequencing and timing of body movements are essential to perform motoric tasks. In this study, we investigate the temporal relation between cortical oscillations and human motor behavior (i.e., rhythmic finger movements). High-density EEG recordings were used for source imaging based on individual anatomy. We separated sustained and movement phase-related EEG source amplitudes based on the actual finger movements recorded by a data glove. Sustained amplitude modulations in the contralateral hand area show decrease for α (10-12 Hz) and β (18-24 Hz), but increase for high γ (60-80 Hz) frequencies during the entire movement period. Additionally, we found movement phase-related amplitudes, which resembled the flexion and extension sequence of the fingers. Especially for faster movement cadences, movement phase-related amplitudes included high β (24-30 Hz) frequencies in prefrontal areas. Interestingly, the spectral profiles and source patterns of movement phase-related amplitudes differed from sustained activities, suggesting that they represent different frequency-specific large-scale networks. First, networks were signified by the sustained element, which statically modulate their synchrony levels during continuous movements. These networks may upregulate neuronal excitability in brain regions specific to the limb, in this study the right hand area. Second, movement phase-related networks, which modulate their synchrony in relation to the movement sequence. We suggest that these frequency-specific networks are associated with distinct functions, including top-down control, sensorimotor prediction, and integration. The separation of different large-scale networks, we applied in this work, improves the interpretation of EEG sources in relation to human motor behavior. EEG recordings provide high temporal resolution suitable to relate cortical oscillations to actual movements. Investigating EEG sources during rhythmic finger movements, we distinguish sustained from

  13. Optical vector network analyzer with improved accuracy based on polarization modulation and polarization pulling.

    Li, Wei; Liu, Jian Guo; Zhu, Ning Hua

    2015-04-15

    We report a novel optical vector network analyzer (OVNA) with improved accuracy based on polarization modulation and stimulated Brillouin scattering (SBS) assisted polarization pulling. The beating between adjacent higher-order optical sidebands which are generated because of the nonlinearity of an electro-optic modulator (EOM) introduces considerable error to the OVNA. In our scheme, the measurement error is significantly reduced by removing the even-order optical sidebands using polarization discrimination. The proposed approach is theoretically analyzed and experimentally verified. The experimental results show that the accuracy of the OVNA is greatly improved compared to a conventional OVNA.

  14. On network coding and modulation mapping for three-phase bidirectional relaying

    Chang, Ronald Y.; Lin, Sian Jheng; Chung, Wei-Ho

    2015-01-01

    © 2015 IEEE. In this paper, we consider the network coding (NC) enabled three-phase protocol for information exchange between two users in a wireless two-way (bidirectional) relay network. Modulo-based (nonbinary) and XOR-based (binary) NC schemes are considered as information mixture schemes at the relay while all transmissions adopt pulse amplitude modulation (PAM). We first obtain the optimal constellation mapping at the relay that maximizes the decoding performance at the users for each NC scheme. Then, we compare the two NC schemes, each in conjunction with the optimal constellation mapping at the relay, in different conditions. Our results demonstrate that, in the low SNR regime, binary NC outperforms nonbinary NC with 4-PAM, while they have mixed performance with 8-PAM. This observation applies to quadrature amplitude modulation (QAM) composed of two parallel PAMs.

  15. Neural Network-Based Receiver in Band-Limited Communication System with MPPSK Modulation

    Wang Zixin

    2018-01-01

    Full Text Available As a type of the spectrally efficient modulation, the m-ary phase position shift keying (MPPSK has been considered to meet the increasing spectrum requirement in the future wireless system. To limit the signal bandwidth and cancel the out-band interference the band-pass filters are used, which introduce the waveform distortion and inter-symbol interference (ISI. Therefore, a single hidden-layer neural network (NN-based receiver is proposed to jointly equalize and demodulate the received signal. The impulse response of the system is static and the network parameters can be obtained after off-line training. The number of the hidden nodes is also determined through simulations. Simulation results show that the NN-based receiver works well in the communication system with different allocated bandwidths. By observing the modified confusion matrix, the false symbol decision is relevant to modulation index, waveform distortions and the ISI.

  16. Degree of synchronization modulated by inhibitory neurons in clustered excitatory-inhibitory recurrent networks

    Li, Huiyan; Sun, Xiaojuan; Xiao, Jinghua

    2018-01-01

    An excitatory-inhibitory recurrent neuronal network is established to numerically study the effect of inhibitory neurons on the synchronization degree of neuronal systems. The obtained results show that, with the number of inhibitory neurons and the coupling strength from an inhibitory neuron to an excitatory neuron increasing, inhibitory neurons can not only reduce the synchronization degree when the synchronization degree of the excitatory population is initially higher, but also enhance it when it is initially lower. Meanwhile, inhibitory neurons could also help the neuronal networks to maintain moderate synchronized states. In this paper, we call this effect as modulation effect of inhibitory neurons. With the obtained results, it is further revealed that the ratio of excitatory neurons to inhibitory neurons being nearly 4 : 1 is an economic and affordable choice for inhibitory neurons to realize this modulation effect.

  17. On network coding and modulation mapping for three-phase bidirectional relaying

    Chang, Ronald Y.

    2015-12-03

    © 2015 IEEE. In this paper, we consider the network coding (NC) enabled three-phase protocol for information exchange between two users in a wireless two-way (bidirectional) relay network. Modulo-based (nonbinary) and XOR-based (binary) NC schemes are considered as information mixture schemes at the relay while all transmissions adopt pulse amplitude modulation (PAM). We first obtain the optimal constellation mapping at the relay that maximizes the decoding performance at the users for each NC scheme. Then, we compare the two NC schemes, each in conjunction with the optimal constellation mapping at the relay, in different conditions. Our results demonstrate that, in the low SNR regime, binary NC outperforms nonbinary NC with 4-PAM, while they have mixed performance with 8-PAM. This observation applies to quadrature amplitude modulation (QAM) composed of two parallel PAMs.

  18. Uncovering co-expression gene network modules regulating fruit acidity in diverse apples.

    Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Zhong, Gan-Yuan; Xu, Kenong

    2015-08-16

    Acidity is a major contributor to fruit quality. Several organic acids are present in apple fruit, but malic acid is predominant and determines fruit acidity. The trait is largely controlled by the Malic acid (Ma) locus, underpinning which Ma1 that putatively encodes a vacuolar aluminum-activated malate transporter1 (ALMT1)-like protein is a strong candidate gene. We hypothesize that fruit acidity is governed by a gene network in which Ma1 is key member. The goal of this study is to identify the gene network and the potential mechanisms through which the network operates. Guided by Ma1, we analyzed the transcriptomes of mature fruit of contrasting acidity from six apple accessions of genotype Ma_ (MaMa or Mama) and four of mama using RNA-seq and identified 1301 fruit acidity associated genes, among which 18 were most significant acidity genes (MSAGs). Network inferring using weighted gene co-expression network analysis (WGCNA) revealed five co-expression gene network modules of significant (P acidity. Overall, this study provides important insight into the Ma1-mediated gene network controlling acidity in mature apple fruit of diverse genetic background.

  19. Small-world organization of self-similar modules in functional brain networks

    Sigman, Mariano; Gallos, Lazaros; Makse, Hernan

    2012-02-01

    The modular organization of the brain implies the parallel nature of brain computations. These modules have to remain functionally independent, but at the same time they need to be sufficiently connected to guarantee the unitary nature of brain perception. Small-world architectures have been suggested as probable structures explaining this behavior. However, there is intrinsic tension between shortcuts generating small-worlds and the persistence of modularity. In this talk, we study correlations between the activity in different brain areas. We suggest that the functional brain network formed by the percolation of strong links is highly modular. Contrary to the common view, modules are self-similar and therefore are very far from being small-world. Incorporating the weak ties to the network converts it into a small-world preserving an underlying backbone of well-defined modules. Weak ties are shown to follow a pattern that maximizes information transfer with minimal wiring costs. This architecture is reminiscent of the concept of weak-ties strength in social networks and provides a natural solution to the puzzle of efficient infomration flow in the highly modular structure of the brain.

  20. Cytokines and cytokine networks target neurons to modulate long-term potentiation.

    Prieto, G Aleph; Cotman, Carl W

    2017-04-01

    Cytokines play crucial roles in the communication between brain cells including neurons and glia, as well as in the brain-periphery interactions. In the brain, cytokines modulate long-term potentiation (LTP), a cellular correlate of memory. Whether cytokines regulate LTP by direct effects on neurons or by indirect mechanisms mediated by non-neuronal cells is poorly understood. Elucidating neuron-specific effects of cytokines has been challenging because most brain cells express cytokine receptors. Moreover, cytokines commonly increase the expression of multiple cytokines in their target cells, thus increasing the complexity of brain cytokine networks even after single-cytokine challenges. Here, we review evidence on both direct and indirect-mediated modulation of LTP by cytokines. We also describe novel approaches based on neuron- and synaptosome-enriched systems to identify cytokines able to directly modulate LTP, by targeting neurons and synapses. These approaches can test multiple samples in parallel, thus allowing the study of multiple cytokines simultaneously. Hence, a cytokine networks perspective coupled with neuron-specific analysis may contribute to delineation of maps of the modulation of LTP by cytokines. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Joint OSNR monitoring and modulation format identification in digital coherent receivers using deep neural networks.

    Khan, Faisal Nadeem; Zhong, Kangping; Zhou, Xian; Al-Arashi, Waled Hussein; Yu, Changyuan; Lu, Chao; Lau, Alan Pak Tao

    2017-07-24

    We experimentally demonstrate the use of deep neural networks (DNNs) in combination with signals' amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio (OSNR) monitoring and modulation format identification (MFI) in digital coherent receivers. The proposed technique automatically extracts OSNR and modulation format dependent features of AHs, obtained after constant modulus algorithm (CMA) equalization, and exploits them for the joint estimation of these parameters. Experimental results for 112 Gbps polarization-multiplexed (PM) quadrature phase-shift keying (QPSK), 112 Gbps PM 16 quadrature amplitude modulation (16-QAM), and 240 Gbps PM 64-QAM signals demonstrate OSNR monitoring with mean estimation errors of 1.2 dB, 0.4 dB, and 1 dB, respectively. Similarly, the results for MFI show 100% identification accuracy for all three modulation formats. The proposed technique applies deep machine learning algorithms inside standard digital coherent receiver and does not require any additional hardware. Therefore, it is attractive for cost-effective multi-parameter estimation in next-generation elastic optical networks (EONs).

  2. Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

    Smith, Aaron; Evans, Michael; Downey, Joseph

    2017-01-01

    National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

  3. A Fuzzy Preprocessing Module for Optimizing the Access Network Selection in Wireless Networks

    Faisal Kaleem

    2013-01-01

    Full Text Available A heterogeneous wireless network is characterized by the presence of different wireless access technologies that coexist in an overlay fashion. These wireless access technologies usually differ in terms of their operating parameters. On the other hand, Mobile Stations (MSs in a heterogeneous wireless network are equipped with multiple interfaces to access different types of services from these wireless access technologies. The ultimate goal of these heterogeneous wireless networks is to provide global connectivity with efficient ubiquitous computing to these MSs based on the Always Best Connected (ABC principle. This is where the need for intelligent and efficient Vertical Handoffs (VHOs between wireless technologies in a heterogeneous environment becomes apparent. This paper presents the design and implementation of a fuzzy multicriteria based Vertical Handoff Necessity Estimation (VHONE scheme that determines the proper time for VHO, while considering the continuity and quality of the currently utilized service, and the end-users' satisfaction.

  4. Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach

    Buer Jan

    2004-12-01

    Full Text Available Abstract Background Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules. Moreover, network motifs such as feed forward loop are recently proposed to be basic building blocks of TRN. However, their relationship to functional modules is not clear. Results In this work we proposed a top-down approach to identify modules in the TRN of E. coli. By studying the global connectivity structure of the regulatory network, we first revealed a five-layer hierarchical structure in which all the regulatory relationships are downward. Based on this regulatory hierarchy, we developed a new method to decompose the regulatory network into functional modules and to identify global regulators governing multiple modules. As a result, 10 global regulators and 39 modules were identified and shown to have well defined functions. We then investigated the distribution and composition of the two basic network motifs (feed forward loop and bi-fan motif in the hierarchical structure of TRN. We found that most of these network motifs include global regulators, indicating that these motifs are not basic building blocks of modules since modules should not contain global regulators. Conclusion The transcriptional regulatory network of E. coli possesses a multi-layer hierarchical modular structure without feedback regulation at transcription level. This hierarchical structure builds the basis for a new and simple decomposition method which is suitable for the identification of functional modules and global regulators in the transcriptional regulatory network of E

  5. Unilateral deafness in children affects development of multi-modal modulation and default mode networks

    Vincent eSchmithorst

    2014-03-01

    Full Text Available Monaural auditory input due to congenital or acquired unilateral hearing loss (UHL may have neurobiological effects on the developing brain. Using fMRI, we investigated the effect of UHL on the development of functional brain networks used for cross-modal processing. Children ages 7-12 with moderate or greater unilateral hearing loss of sensorineural origin (UHL-SN; N = 21 and normal-hearing controls (N = 23 performed an fMRI-compatible adaptation of the Token Test involving listening to a sentence such as touched the small green circle and the large blue square and simultaneously viewing an arrow touching colored shapes on a video. Children with right or severe-to-profound UHL-SN displayed smaller activation in a region encompassing the right inferior temporal, middle temporal, and middle occipital gyrus (BA 19/37/39, evidencing differences due to monaural hearing in cross-modal modulation of the visual processing pathway. Children with UHL-SN displayed increased activation in the left posterior superior temporal gyrus, likely the result either of more effortful low-level processing of auditory stimuli or differences in cross-modal modulation of the auditory processing pathway. Additionally, children with UHL-SN displayed reduced deactivation of anterior and posterior regions of the default mode network. Results suggest that monaural hearing affects the development of brain networks related to cross-modal sensory processing and the regulation of the default network during processing of spoken language.

  6. Two-level modulation scheme to reduce latency for optical mobile fronthaul networks.

    Sung, Jiun-Yu; Chow, Chi-Wai; Yeh, Chien-Hung; Chang, Gee-Kung

    2016-10-31

    A system using optical two-level orthogonal-frequency-division-multiplexing (OFDM) - amplitude-shift-keying (ASK) modulation is proposed and demonstrated to reduce the processing latency for the optical mobile fronthaul networks. At the proposed remote-radio-head (RRH), the high data rate OFDM signal does not need to be processed, but is directly launched into a high speed photodiode (HSPD) and subsequently emitted by an antenna. Only a low bandwidth PD is needed to recover the low data rate ASK control signal. Hence, it is simple and provides low-latency. Furthermore, transporting the proposed system over the already deployed optical-distribution-networks (ODNs) of passive-optical-networks (PONs) is also demonstrated with 256 ODN split-ratios.

  7. Acupuncture induce the different modulation patterns of the default mode network: an fMRI study

    Liu, Peng; Qin, Wei; Tian, Jie; Zhang, Yi

    2009-02-01

    According to Traditional Chinese Medicine (TCM) theory and certain clinical treatment reports, the sustained effects of acupuncture indeed exist, which may last several minutes or hours. Furthermore, increased attention has fallen on the sustained effects of acupuncture. Recently, it is reported that the sustained acupuncture effects may alter the default mode network (DMN). It raises interesting questions: whether the modulations of acupuncture effects to the DMN are still detected at other acupoints and whether the modulation patterns are different induced by different acupoints. In the present study, we wanted to investigate the questions. An experiment fMRI design was carried out on 36 subjects with the electroacupuncture stimulation (EAS) at the three acupoints: Guangming (GB37), Kunlun (BL60) and Jiaoxin (KI8) on the left leg. The data sets were analyzed by a data driven method named independent component analysis (ICA). The results indicated that the three acupoints stimulations may modulate the DMN. Moreover, the modulation patterns were distinct. We suggest the different modulation patterns on the DMN may attribute to the distinct functional effects of acupoints.

  8. XPS-and-DFT analyses of the Pb 4f — Zn 3s and Pb 5d — O 2s overlapped ambiguity contributions to the final electronic structure of bulk and thin-film Pb-modulated zincite

    Zatsepin, D.A. [M.N. Miheev Institute of Metal Physics of Ural Branch of Russian Academy of Sciences, 620990 Yekaterinburg (Russian Federation); Institute of Physics and Technology, Ural Federal University, 620002 Yekaterinburg (Russian Federation); Boukhvalov, D.W., E-mail: danil@hanyang.ac.kr [Department of Chemistry, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791 (Korea, Republic of); Theoretical Physics and Applied Mathematics Department, Ural Federal University,Mira Street 19, 620002 Yekaterinburg (Russian Federation); Gavrilov, N.V. [Institute of Electrophysics, Russian Academy of Sciences, Ural Branch, 620990 Yekaterinburg (Russian Federation); Kurmaev, E.Z. [M.N. Miheev Institute of Metal Physics of Ural Branch of Russian Academy of Sciences, 620990 Yekaterinburg (Russian Federation); Institute of Physics and Technology, Ural Federal University, 620002 Yekaterinburg (Russian Federation); Zatsepin, A.F. [Institute of Physics and Technology, Ural Federal University, 620002 Yekaterinburg (Russian Federation); Cui, L. [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055 (China); Shur, V. Ya.; Esin, A.A. [Institute of Natural Sciences, Ural Federal University, 51 Lenin Ave, 620000 Yekaterinburg (Russian Federation)

    2017-05-31

    Highlights: • Two modes of ZnO:Pb in the bulk and surface morphologies were established: the high- and low-interaction. • It was shown the ambiguity contribution of Pb 4f − Zn 3s and Pb 5d − O 2s states into final electronic structure. • The main type of defects is PbO-like with some PbO{sub 2}-like contributions. • An applied wurzite-like structural model well agrees with experimental data obtained for zincite. - Abstract: The electronic structures of zincite Pb-modulated bulk and thin-films were studied via X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) techniques. Both XPS data and DFT-calculations allowed the derivation of two different Pb-embedding scenarios into the ZnO-hosts. These included the high-interaction mode of Pb-impurity with initial zinc-oxygen host-lattice for the bulk morphology, accompanied with low Pb-metal losses; and the low-interaction mode for thin-films, where there was intake of Pb-impurities into the hollows of the surface. Despite dissimilar mechanisms of Pb-impurity accumulation and distribution in the bulk and thin-films zincite host-matrices, the strong Pb 4f — Zn 3s and Pb 5d — O 2s overlapped ambiguity contribution to the appropriate core-level structure and valence bands was established by XPS analysis and reproduced with the help of DFT-calculations. It was shown that the microscopic structure of the embedded lead-impurity played a crucial role in the Pb ion-beam stimulated synthesis of secondary lead-oxygen phases via large-area defect fabrication, and the difference among zincite and wurzite polymorphs played almost no role in this case.

  9. Gene Network for Identifying the Entropy Changes of Different Modules in Pediatric Sepsis

    Jing Yang

    2016-12-01

    Full Text Available Background/Aims: Pediatric sepsis is a disease that threatens life of children. The incidence of pediatric sepsis is higher in developing countries due to various reasons, such as insufficient immunization and nutrition, water and air pollution, etc. Exploring the potential genes via different methods is of significance for the prevention and treatment of pediatric sepsis. This study aimed to identify potential genes associated with pediatric sepsis utilizing analysis of gene network and entropy. Methods: The mRNA expression in the blood samples collected from 20 septic children and 30 healthy controls was quantified by using Affymetrix HG-U133A microarray. Two condition-specific protein-protein interaction networks (PINs, one for the healthy control and the other one for the children with sepsis, were deduced by combining the fundamental human PINs with gene expression profiles in the two phenotypes. Subsequently, distinct modules from the two conditional networks were extracted by adopting a maximal clique-merging approach. Delta entropy (ΔS was calculated between sepsis and control modules. Results: Then, key genes displaying changes in gene composition were identified by matching the control and sepsis modules. Two objective modules were obtained, in which ribosomal protein RPL4 and RPL9 as well as TOP2A were probably considered as the key genes differentiating sepsis from healthy controls. Conclusion: According to previous reports and this work, TOP2A is the potential gene therapy target for pediatric sepsis. The relationship between pediatric sepsis and RPL4 and RPL9 needs further investigation.

  10. Anger Modulates Influence Hierarchies Within and Between Emotional Reactivity and Regulation Networks

    Jacob, Yael; Gilam, Gadi; Lin, Tamar; Raz, Gal; Hendler, Talma

    2018-01-01

    Emotion regulation is hypothesized to be mediated by the interactions between emotional reactivity and regulation networks during the dynamic unfolding of the emotional episode. Yet, it remains unclear how to delineate the effective relationships between these networks. In this study, we examined the aforementioned networks’ information flow hierarchy during viewing of an anger provoking movie excerpt. Anger regulation is particularly essential for averting individuals from aggression and violence, thus improving prosocial behavior. Using subjective ratings of anger intensity we differentiated between low and high anger periods of the film. We then applied the Dependency Network Analysis (DEPNA), a newly developed graph theory method to quantify networks’ node importance during the two anger periods. The DEPNA analysis revealed that the impact of the ventromedial prefrontal cortex (vmPFC) was higher in the high anger condition, particularly within the regulation network and on the connections between the reactivity and regulation networks. We further showed that higher levels of vmPFC impact on the regulation network were associated with lower subjective anger intensity during the high-anger cinematic period, and lower trait anger levels. Supporting and replicating previous findings, these results emphasize the previously acknowledged central role of vmPFC in modulating negative affect. We further show that the impact of the vmPFC relies on its correlational influence on the connectivity between reactivity and regulation networks. More importantly, the hierarchy network analysis revealed a link between connectivity patterns of the vmPFC and individual differences in anger reactivity and trait, suggesting its potential therapeutic role. PMID:29681803

  11. Generation of non-overlapping fiber architecture

    Chapelle, Lucie; Lévesque, M.; Brøndsted, Povl

    2015-01-01

    and polymer networks. The model takes into account the complex geometry of the fiber arrangement in which a fiber can be modeled with a certain degree of bending while keeping a main fiber orientation. The model is built in two steps. First, fibers are generated as a chain of overlapping spheres or as a chain......: a repulsion force to suppress the overlap between two fibers and a bending and stretching force to ensure that the fiber structure is kept unchanged. The model can be used as the geometrical basis for further finite-element modelling....

  12. Influence of current pulse shape on directly modulated system performance in metro area optical networks

    Campos, Carmina del Rio; Horche, Paloma R.; Martin-Minguez, Alfredo

    2011-03-01

    Due to the fact that a metro network market is very cost sensitive, direct modulated schemes appear attractive. In this paper a CWDM (Coarse Wavelength Division Multiplexing) system is studied in detail by means of an Optical Communication System Design Software; a detailed study of the modulated current shape (exponential, sine and gaussian) for 2.5 Gb/s CWDM Metropolitan Area Networks is performed to evaluate its tolerance to linear impairments such as signal-to-noise-ratio degradation and dispersion. Point-to-point links are investigated and optimum design parameters are obtained. Through extensive sets of simulation results, it is shown that some of these shape pulses are more tolerant to dispersion when compared with conventional gaussian shape pulses. In order to achieve a low Bit Error Rate (BER), different types of optical transmitters are considered including strongly adiabatic and transient chirp dominated Directly Modulated Lasers (DMLs). We have used fibers with different dispersion characteristics, showing that the system performance depends, strongly, on the chosen DML-fiber couple.

  13. Flexible modulation of network connectivity related to cognition in Alzheimer’s disease

    McLaren, Donald G.; Sperling, Reisa A.; Atria, Alireza

    2014-01-01

    Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer’s disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54–82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive

  14. Detecting highly overlapping community structure by greedy clique expansion

    Lee, Conrad; Reid, Fergal; McDaid, Aaron; Hurley, Neil

    2010-01-01

    In complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. Recent advances in benchmarking indicate that existing community assignment algorithms that are capable of detecting overlapping communities perform well only when the extent of community overlap is kept to modest levels. To overcome this limitation, we introduce a new community assignment algorithm called Greedy Clique Expansion (GCE). The algorithm identifies d...

  15. Plastic modulation of PTSD resting-state networks by EEG neurofeedback

    Kluetsch, Rosemarie C.; Ros, Tomas; Théberge, Jean; Frewen, Paul A.; Calhoun, Vince D.; Schmahl, Christian; Jetly, Rakesh; Lanius, Ruth A.

    2015-01-01

    Objective Electroencephalographic (EEG) neurofeedback training has been shown to produce plastic modulations in salience network and default mode network functional connectivity in healthy individuals. In this study, we investigated whether a single session of neurofeedback training aimed at the voluntary reduction of alpha rhythm (8–12 Hz) amplitude would be related to differences in EEG network oscillations, functional MRI (fMRI) connectivity, and subjective measures of state anxiety and arousal in a group of individuals with PTSD. Method 21 individuals with PTSD related to childhood abuse underwent 30 minutes of EEG neurofeedback training preceded and followed by a resting-state fMRI scan. Results Alpha desynchronizing neurofeedback was associated with decreased alpha amplitude during training, followed by a significant increase (‘rebound’) in resting-state alpha synchronization. This rebound was linked to increased calmness, greater salience network connectivity with the right insula, and enhanced default mode network connectivity with bilateral posterior cingulate, right middle frontal gyrus, and left medial prefrontal cortex. Conclusion Our study represents a first step in elucidating the potential neurobehavioral mechanisms mediating the effects of neurofeedback treatment on regulatory systems in PTSD. Moreover, it documents for the first time a spontaneous EEG ‘rebound’ after neurofeedback, pointing to homeostatic/compensatory mechanisms operating in the brain. PMID:24266644

  16. Plastic modulation of PTSD resting-state networks and subjective wellbeing by EEG neurofeedback.

    Kluetsch, R C; Ros, T; Théberge, J; Frewen, P A; Calhoun, V D; Schmahl, C; Jetly, R; Lanius, R A

    2014-08-01

    Electroencephalographic (EEG) neurofeedback training has been shown to produce plastic modulations in salience network and default mode network functional connectivity in healthy individuals. In this study, we investigated whether a single session of neurofeedback training aimed at the voluntary reduction of alpha rhythm (8-12 Hz) amplitude would be related to differences in EEG network oscillations, functional MRI (fMRI) connectivity, and subjective measures of state anxiety and arousal in a group of individuals with post-traumatic stress disorder (PTSD). Twenty-one individuals with PTSD related to childhood abuse underwent 30 min of EEG neurofeedback training preceded and followed by a resting-state fMRI scan. Alpha desynchronizing neurofeedback was associated with decreased alpha amplitude during training, followed by a significant increase ('rebound') in resting-state alpha synchronization. This rebound was linked to increased calmness, greater salience network connectivity with the right insula, and enhanced default mode network connectivity with bilateral posterior cingulate, right middle frontal gyrus, and left medial prefrontal cortex. Our study represents a first step in elucidating the potential neurobehavioural mechanisms mediating the effects of neurofeedback treatment on regulatory systems in PTSD. Moreover, it documents for the first time a spontaneous EEG 'rebound' after neurofeedback, pointing to homeostatic/compensatory mechanisms operating in the brain. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  17. Trends in intensity modulated radiation therapy use for locally advanced rectal cancer at National Comprehensive Cancer Network centers

    Marsha Reyngold, MD, PhD; Joyce Niland, PhD; Anna ter Veer, MS; Tanios Bekaii-Saab, MD; Lily Lai, MD; Joshua E. Meyer, MD; Steven J. Nurkin, MD, MS; Deborah Schrag, MD, MPH; John M. Skibber, MD, FACS; Al B. Benson, MD; Martin R. Weiser, MD; Christopher H. Crane, MD; Karyn A. Goodman, MD, MS

    2018-01-01

    Purpose: Intensity modulated radiation therapy (IMRT) has been rapidly incorporated into clinical practice because of its technological advantages over 3-dimensional conformal radiation therapy (CRT). We characterized trends in IMRT utilization in trimodality treatment of locally advanced rectal cancer at National Comprehensive Cancer Network cancer centers between 2005 and 2011. Methods and materials: Using the prospective National Comprehensive Cancer Network Colorectal Cancer Database, ...

  18. Molecular Correlates of Cortical Network Modulation by Long-Term Sensory Experience in the Adult Rat Barrel Cortex

    Vallès, Astrid; Granic, Ivica; De Weerd, Peter; Martens, Gerard J. M.

    2014-01-01

    Modulation of cortical network connectivity is crucial for an adaptive response to experience. In the rat barrel cortex, long-term sensory stimulation induces cortical network modifications and neuronal response changes of which the molecular basis is unknown. Here, we show that long-term somatosensory stimulation by enriched environment…

  19. Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks

    Xianghan Zheng

    2017-04-01

    Full Text Available Proteomics research has become one of the most important topics in the field of life science and natural science. At present, research on protein–protein interaction networks (PPIN mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate detection mechanisms of functional modules in PPIN, including open database, existing detection algorithms, and recent solutions. After that, we describe the proposed approach based on the simplified swarm optimization (SSO algorithm and the knowledge of Gene Ontology (GO. The proposed solution implements the SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species datasets for experiment: fruitfly, mouse, scere, and human. The testing and analysis result show that the proposed solution is feasible, efficient, and could achieve a higher accuracy of prediction than existing approaches.

  20. Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations.

    Xin Wang

    Full Text Available Combinatorial gene perturbations provide rich information for a systematic exploration of genetic interactions. Despite successful applications to bacteria and yeast, the scalability of this approach remains a major challenge for higher organisms such as humans. Here, we report a novel experimental and computational framework to efficiently address this challenge by limiting the 'search space' for important genetic interactions. We propose to integrate rich phenotypes of multiple single gene perturbations to robustly predict functional modules, which can subsequently be subjected to further experimental investigations such as combinatorial gene silencing. We present posterior association networks (PANs to predict functional interactions between genes estimated using a Bayesian mixture modelling approach. The major advantage of this approach over conventional hypothesis tests is that prior knowledge can be incorporated to enhance predictive power. We demonstrate in a simulation study and on biological data, that integrating complementary information greatly improves prediction accuracy. To search for significant modules, we perform hierarchical clustering with multiscale bootstrap resampling. We demonstrate the power of the proposed methodologies in applications to Ewing's sarcoma and human adult stem cells using publicly available and custom generated data, respectively. In the former application, we identify a gene module including many confirmed and highly promising therapeutic targets. Genes in the module are also significantly overrepresented in signalling pathways that are known to be critical for proliferation of Ewing's sarcoma cells. In the latter application, we predict a functional network of chromatin factors controlling epidermal stem cell fate. Further examinations using ChIP-seq, ChIP-qPCR and RT-qPCR reveal that the basis of their genetic interactions may arise from transcriptional cross regulation. A Bioconductor package

  1. Emerging subspecialties in neurology: deep brain stimulation and electrical neuro-network modulation.

    Hassan, Anhar; Okun, Michael S

    2013-01-29

    Deep brain stimulation (DBS) is a surgical therapy that involves the delivery of an electrical current to one or more brain targets. This technology has been rapidly expanding to address movement, neuropsychiatric, and other disorders. The evolution of DBS has created a niche for neurologists, both in the operating room and in the clinic. Since DBS is not always deep, not always brain, and not always simply stimulation, a more accurate term for this field may be electrical neuro-network modulation (ENM). Fellowships will likely in future years evolve their scope to include other technologies, and other nervous system regions beyond typical DBS therapy.

  2. Prosody production networks are modulated by sensory cues and social context.

    Klasen, Martin; von Marschall, Clara; Isman, Güldehen; Zvyagintsev, Mikhail; Gur, Ruben C; Mathiak, Klaus

    2018-03-05

    The neurobiology of emotional prosody production is not well investigated. In particular, the effects of cues and social context are not known. The present study sought to differentiate cued from free emotion generation and the effect of social feedback from a human listener. Online speech filtering enabled fMRI during prosodic communication in 30 participants. Emotional vocalizations were a) free, b) auditorily cued, c) visually cued, or d) with interactive feedback. In addition to distributed language networks, cued emotions increased activity in auditory and - in case of visual stimuli - visual cortex. Responses were larger in pSTG at the right hemisphere and the ventral striatum when participants were listened to and received feedback from the experimenter. Sensory, language, and reward networks contributed to prosody production and were modulated by cues and social context. The right pSTG is a central hub for communication in social interactions - in particular for interpersonal evaluation of vocal emotions.

  3. Importance Sampling for a Markov Modulated Queuing Network with Customer Impatience until the End of Service

    Ebrahim MAHDIPOUR

    2009-01-01

    Full Text Available For more than two decades, there has been a growing of interest in fast simulation techniques for estimating probabilities of rare events in queuing networks. Importance sampling is a variance reduction method for simulating rare events. The present paper carries out strict deadlines to the paper by Dupuis et al for a two node tandem network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We derive a closed form solution for the probability of missing deadlines. Then we have employed the results to an importance sampling technique to estimate the probability of total population overflow which is a rare event. We have also shown that the probability of this rare event may be affected by various deadline values.

  4. Neuroplasticity pathways and protein-interaction networks are modulated by vortioxetine in rodents

    Waller, Jessica A.; Nygaard, Sara Holm; Li, Yan

    2017-01-01

    species and sexes, different brain regions, and in response to distinct routes of administration and regimens. Conclusions: A recurring theme, based on the present study as well as previous findings, is that networks related to synaptic plasticity, synaptic transmission, signal transduction...... and rat in response to distinct treatment regimens and in different brain regions. Furthermore, analysis of complexes of physically-interacting proteins reveal that biomarkers involved in transcriptional regulation, neurodevelopment, neuroplasticity, and endocytosis are modulated by vortioxetine....... A subsequent qPCR study examining the expression of targets in the protein-protein interactome space in response to chronic vortioxetine treatment over a range of doses provides further biological validation that vortioxetine engages neuroplasticity networks. Thus, the same biology is regulated in different...

  5. Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

    Farber, Charles R

    2010-11-01

    Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD. © 2010 American Society for Bone and Mineral Research.

  6. Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

    Jun Ren

    2014-01-01

    Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

  7. Serotonergic modulation of spatial working memory: predictions from a computational network model

    Maria eCano-Colino

    2013-09-01

    Full Text Available Serotonin (5-HT receptors of types 1A and 2A are massively expressed in prefrontal cortex (PFC neurons, an area associated with cognitive function. Hence, 5-HT could be effective in modulating prefrontal-dependent cognitive functions, such as spatial working memory (SWM. However, a direct association between 5-HT and SWM has proved elusive in psycho-pharmacological studies. Recently, a computational network model of the PFC microcircuit was used to explore the relationship between 5‑HT and SWM (Cano-Colino et al. 2013. This study found that both excessive and insufficient 5-HT levels lead to impaired SWM performance in the network, and it concluded that analyzing behavioral responses based on confidence reports could facilitate the experimental identification of SWM behavioral effects of 5‑HT neuromodulation. Such analyses may have confounds based on our limited understanding of metacognitive processes. Here, we extend these results by deriving three additional predictions from the model that do not rely on confidence reports. Firstly, only excessive levels of 5-HT should result in SWM deficits that increase with delay duration. Secondly, excessive 5-HT baseline concentration makes the network vulnerable to distractors at distances that were robust to distraction in control conditions, while the network still ignores distractors efficiently for low 5‑HT levels that impair SWM. Finally, 5-HT modulates neuronal memory fields in neurophysiological experiments: Neurons should be better tuned to the cued stimulus than to the behavioral report for excessive 5-HT levels, while the reverse should happen for low 5-HT concentrations. In all our simulations agonists of 5-HT1A receptors and antagonists of 5-HT2A receptors produced behavioral and physiological effects in line with global 5-HT level increases. Our model makes specific predictions to be tested experimentally and advance our understanding of the neural basis of SWM and its neuromodulation

  8. Extrasynaptic neurotransmission in the modulation of brain function. Focus on the striatal neuronal-glial networks

    Kjell eFuxe

    2012-06-01

    Full Text Available Extrasynaptic neurotransmission is an important short distance form of volume transmission (VT and describes the extracellular diffusion of transmitters and modulators after synaptic spillover or extrasynaptic release in the local circuit regions binding to and activating mainly extrasynaptic neuronal and glial receptors in the neuroglial networks of the brain. Receptor-receptor interactions in G protein-coupled receptor (GPCR heteromers play a major role, on dendritic spines and nerve terminals including glutamate synapses, in the integrative processes of the extrasynaptic signaling. Heteromeric complexes between GPCR and ion-channel receptors play a special role in the integration of the synaptic and extrasynaptic signals. Changes in extracellular concentrations of the classical synaptic neurotransmitters glutamate and GABA found with microdialysis is likely an expression of the activity of the neuron-astrocyte unit of the brain and can be used as an index of VT-mediated actions of these two neurotransmitters in the brain. Thus, the activity of neurons may be functionally linked to the activity of astrocytes, which may release glutamate and GABA to the extracellular space where extrasynaptic glutamate and GABA receptors do exist. Wiring transmission (WT and VT are fundamental properties of all neurons of the CNS but the balance between WT and VT varies from one nerve cell population to the other. The focus is on the striatal cellular networks, and the WT and VT and their integration via receptor heteromers are described in the GABA projection neurons, the glutamate, dopamine, 5-hydroxytryptamine (5-HT and histamine striatal afferents, the cholinergic interneurons and different types of GABA interneurons. In addition, the role in these networks of VT signaling of the energy-dependent modulator adenosine and of endocannabinoids mainly formed in the striatal projection neurons will be underlined to understand the communication in the striatal

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

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

    2016-01-01

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

  10. Electro-acupuncture at different acupoints modulating the relative specific brain functional network

    Fang, Jiliang; Wang, Xiaoling; Wang, Yin; Liu, Hesheng; Hong, Yang; Liu, Jun; Zhou, Kehua; Wang, Lei; Xue, Chao; Song, Ming; Liu, Baoyan; Zhu, Bing

    2010-11-01

    Objective: The specific brain effects of acupoint are important scientific concern in acupuncture. However, previous acupuncture fMRI studies focused on acupoints in muscle layer on the limb. Therefore, researches on acupoints within connective tissue at trunk are warranted. Material and Methods: Brain effects of acupuncture on abdomen at acupoints Guanyuan (CV4) and Zhongwan (CV12) were tested using fMRI on 21 healthy volunteers. The data acquisition was performed at resting state, during needle retention, electroacupuncture (EA) and post-EA resting state. Needling sensations were rated after every electroacupuncture (EA) procedure. The needling sensations and the brain functional activity and connectivity were compared between CV4 and CV12 using SPSS, SPM2 and the local and remote connectivity maps. Results and conclusion: EA at CV4 and CV12 induced apparent deactivation effects in the limbic-paralimbic-neocortical network. The default mode of the brain was modified by needle retention and EA, respectively. The functional brain network was significantly changed post EA. However, the minor differences existed between these two acupoints. The results demonstrated similarity between functional brain network mode of acupuncture modulation and functional circuits of emotional and cognitive regulation. Acupuncture may produce analgesia, anti-anxiety and anti-depression via the limbic-paralimbic-neocortical network (LPNN).

  11. Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

    Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M.

    2016-01-01

    Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules

  12. Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance.

    Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

    2017-03-14

    Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.

  13. Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity

    Jinyu Hu

    2012-01-01

    Full Text Available In this study, a gene positive network is proposed based on a weighted undirected graph, where the weight represents the positive correlation of the genes. A Pearson agglomerative clustering algorithm is employed to build a clustering tree, where dotted lines cut the tree from bottom to top leading to a number of subsets of the modules. In order to achieve better module partitions, the Pearson correlation coefficient modularity is addressed to seek optimal module decomposition by selecting an optimal threshold value. For the liver cancer gene network under study, we obtain a strong threshold value at 0.67302, and a very strong correlation threshold at 0.80086. On the basis of these threshold values, fourteen strong modules and thirteen very strong modules are obtained respectively. A certain degree of correspondence between the two types of modules is addressed as well. Finally, the biological significance of the two types of modules is analyzed and explained, which shows that these modules are closely related to the proliferation and metastasis of liver cancer. This discovery of the new modules may provide new clues and ideas for liver cancer treatment.

  14. Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

    Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

    2016-01-01

    A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

  15. Robust Automatic Modulation Classification Technique for Fading Channels via Deep Neural Network

    Jung Hwan Lee

    2017-08-01

    Full Text Available In this paper, we propose a deep neural network (DNN-based automatic modulation classification (AMC for digital communications. While conventional AMC techniques perform well for additive white Gaussian noise (AWGN channels, classification accuracy degrades for fading channels where the amplitude and phase of channel gain change in time. The key contributions of this paper are in two phases. First, we analyze the effectiveness of a variety of statistical features for AMC task in fading channels. We reveal that the features that are shown to be effective for fading channels are different from those known to be good for AWGN channels. Second, we introduce a new enhanced AMC technique based on DNN method. We use the extensive and diverse set of statistical features found in our study for the DNN-based classifier. The fully connected feedforward network with four hidden layers are trained to classify the modulation class for several fading scenarios. Numerical evaluation shows that the proposed technique offers significant performance gain over the existing AMC methods in fading channels.

  16. Sequential interrogation of multiple FBG sensors using LPG modulation and an artificial neural network

    Basu, Mainak; Ghorai, S K

    2015-01-01

    Interrogating multiple fiber Bragg gratings (FBG) requires highly sensitive spectrum scanning equipment such as optical spectrum analyzers, tunable filters, acousto-optic tunable filters etc, which are expensive, bulky and time consuming. In this paper, we present a new approach for multiple FBG sensor interrogation using long-period gratings and an artificial neural network. The reflection spectra of the multiplexed FBGs are modulated by two long period gratings separately and the modulated optical intensities were detected by two photodetectors. The outputs of the detectors are then used as input in a previously trained artificial neural network to interrogate the FBG sensors. Simulations have been performed to determine the strain and wavelength shift using two and four sensors. The interrogation system has also been demonstrated experimentally for two sensors using simply supported beams in the range of 0–350 μstrain. The proposed interrogation scheme has been found to identify the perturbed FBG, and to determine strain and wavelength shift with reasonable accuracy. (paper)

  17. Performance evaluations of hybrid modulation with different optical labels over PDQ in high bit-rate OLS network systems.

    Xu, M; Li, Y; Kang, T Z; Zhang, T S; Ji, J H; Yang, S W

    2016-11-14

    Two orthogonal modulation optical label switching(OLS) schemes, which are based on payload of polarization multiplexing-differential quadrature phase shift keying(POLMUX-DQPSK or PDQ) modulated with identifications of duobinary (DB) label and pulse position modulation(PPM) label, are researched in high bit-rate OLS network. The BER performance of hybrid modulation with payload and label signals are discussed and evaluated in theory and simulation. The theoretical BER expressions of PDQ, PDQ-DB and PDQ-PPM are given with analysis method of hybrid modulation encoding in different the bit-rate ratios of payload and label. Theoretical derivation results are shown that the payload of hybrid modulation has a certain gain of receiver sensitivity than payload without label. The sizes of payload BER gain obtained from hybrid modulation are related to the different types of label. The simulation results are consistent with that of theoretical conclusions. The extinction ratio (ER) conflicting between hybrid encoding of intensity and phase types can be compromised and optimized in OLS system of hybrid modulation. The BER analysis method of hybrid modulation encoding in OLS system can be applied to other n-ary hybrid modulation or combination modulation systems.

  18. Subthalamic stimulation modulates cortical motor network activity and synchronization in Parkinson’s disease

    Klotz, Rosa; Govindan, Rathinaswamy B.; Scholten, Marlieke; Naros, Georgios; Ramos-Murguialday, Ander; Bunjes, Friedemann; Meisner, Christoph; Plewnia, Christian; Krüger, Rejko

    2015-01-01

    Dynamic modulations of large-scale network activity and synchronization are inherent to a broad spectrum of cognitive processes and are disturbed in neuropsychiatric conditions including Parkinson’s disease. Here, we set out to address the motor network activity and synchronization in Parkinson’s disease and its modulation with subthalamic stimulation. To this end, 20 patients with idiopathic Parkinson’s disease with subthalamic nucleus stimulation were analysed on externally cued right hand finger movements with 1.5-s interstimulus interval. Simultaneous recordings were obtained from electromyography on antagonistic muscles (right flexor digitorum and extensor digitorum) together with 64-channel electroencephalography. Time-frequency event-related spectral perturbations were assessed to determine cortical and muscular activity. Next, cross-spectra in the time-frequency domain were analysed to explore the cortico-cortical synchronization. The time-frequency modulations enabled us to select a time-frequency range relevant for motor processing. On these time-frequency windows, we developed an extension of the phase synchronization index to quantify the global cortico-cortical synchronization and to obtain topographic differentiations of distinct electrode sites with respect to their contributions to the global phase synchronization index. The spectral measures were used to predict clinical and reaction time outcome using regression analysis. We found that movement-related desynchronization of cortical activity in the upper alpha and beta range was significantly facilitated with ‘stimulation on’ compared to ‘stimulation off’ on electrodes over the bilateral parietal, sensorimotor, premotor, supplementary-motor, and prefrontal areas, including the bilateral inferior prefrontal areas. These spectral modulations enabled us to predict both clinical and reaction time improvement from subthalamic stimulation. With ‘stimulation on’, interhemispheric cortico

  19. Pre-stimulus BOLD-network activation modulates EEG spectral activity during working memory retention

    Mara eKottlow

    2015-05-01

    Full Text Available Working memory (WM processes depend on our momentary mental state and therefore exhibit considerable fluctuations. Here, we investigate the interplay of task-preparatory and task-related brain activity as represented by pre-stimulus BOLD-fluctuations and spectral EEG from the retention periods of a visual WM task. Visual WM is used to maintain sensory information in the brain enabling the performance of cognitive operations and is associated with mental health.We tested 22 subjects simultaneously with EEG and fMRI while performing a visuo-verbal Sternberg task with two different loads, allowing for the temporal separation of preparation, encoding, retention and retrieval periods.Four temporally coherent networks - the default mode network (DMN, the dorsal attention, the right and the left WM network - were extracted from the continuous BOLD data by means of a group ICA. Subsequently, the modulatory effect of these networks’ pre-stimulus activation upon retention-related EEG activity in the theta, alpha and beta frequencies was analyzed. The obtained results are informative in the context of state-dependent information processing.We were able to replicate two well-known load-dependent effects: the frontal-midline theta increase during the task and the decrease of pre-stimulus DMN activity. As our main finding, these two measures seem to depend on each other as the significant negative correlations at frontal-midline channels suggested. Thus, suppressed pre-stimulus DMN levels facilitated later task related frontal midline theta increases. In general, based on previous findings that neuronal coupling in different frequency bands may underlie distinct functions in WM retention, our results suggest that processes reflected by spectral oscillations during retention seem not only to be online synchronized with activity in different attention-related networks but are also modulated by activity in these networks during preparation intervals.

  20. Modulation of dynamic modes by interplay between positive and negative feedback loops in gene regulatory networks

    Wang, Liu-Suo; Li, Ning-Xi; Chen, Jing-Jia; Zhang, Xiao-Peng; Liu, Feng; Wang, Wei

    2018-04-01

    A positive and a negative feedback loop can induce bistability and oscillation, respectively, in biological networks. Nevertheless, they are frequently interlinked to perform more elaborate functions in many gene regulatory networks. Coupled positive and negative feedback loops may exhibit either oscillation or bistability depending on the intensity of the stimulus in some particular networks. It is less understood how the transition between the two dynamic modes is modulated by the positive and negative feedback loops. We developed an abstract model of such systems, largely based on the core p53 pathway, to explore the mechanism for the transformation of dynamic behaviors. Our results show that enhancing the positive feedback may promote or suppress oscillations depending on the strength of both feedback loops. We found that the system oscillates with low amplitudes in response to a moderate stimulus and switches to the on state upon a strong stimulus. When the positive feedback is activated much later than the negative one in response to a strong stimulus, the system exhibits long-term oscillations before switching to the on state. We explain this intriguing phenomenon using quasistatic approximation. Moreover, early switching to the on state may occur when the system starts from a steady state in the absence of stimuli. The interplay between the positive and negative feedback plays a key role in the transitions between oscillation and bistability. Of note, our conclusions should be applicable only to some specific gene regulatory networks, especially the p53 network, in which both oscillation and bistability exist in response to a certain type of stimulus. Our work also underscores the significance of transient dynamics in determining cellular outcome.

  1. Disruption of structural covariance networks for language in autism is modulated by verbal ability.

    Sharda, Megha; Khundrakpam, Budhachandra S; Evans, Alan C; Singh, Nandini C

    2016-03-01

    The presence of widespread speech and language deficits is a core feature of autism spectrum disorders (ASD). These impairments have often been attributed to altered connections between brain regions. Recent developments in anatomical correlation-based approaches to map structural covariance offer an effective way of studying such connections in vivo. In this study, we employed such a structural covariance network (SCN)-based approach to investigate the integrity of anatomical networks in fronto-temporal brain regions of twenty children with ASD compared to an age and gender-matched control group of twenty-two children. Our findings reflected large-scale disruption of inter and intrahemispheric covariance in left frontal SCNs in the ASD group compared to controls, but no differences in right fronto-temporal SCNs. Interhemispheric covariance in left-seeded networks was further found to be modulated by verbal ability of the participants irrespective of autism diagnosis, suggesting that language function might be related to the strength of interhemispheric structural covariance between frontal regions. Additionally, regional cortical thickening was observed in right frontal and left posterior regions, which was predicted by decreasing symptom severity and increasing verbal ability in ASD. These findings unify reports of regional differences in cortical morphology in ASD. They also suggest that reduced left hemisphere asymmetry and increased frontal growth may not only reflect neurodevelopmental aberrations but also compensatory mechanisms.

  2. Working Memory Modulation of Frontoparietal Network Connectivity in First-Episode Schizophrenia

    Nielsen, Jesper Duemose; Madsen, Kristoffer Hougaard; Wang, Zheng

    2017-01-01

    Working memory (WM) impairment is regarded as a core aspect of schizophrenia. However, the neural mechanisms behind this cognitive deficit remain unclear. The connectivity of a frontoparietal network is known to be important for subserving WM. Using functional magnetic resonance imaging, the curr......Working memory (WM) impairment is regarded as a core aspect of schizophrenia. However, the neural mechanisms behind this cognitive deficit remain unclear. The connectivity of a frontoparietal network is known to be important for subserving WM. Using functional magnetic resonance imaging......, the current study investigated whether WM-dependent modulation of effective connectivity in this network is affected in a group of first-episode schizophrenia (FES) patients compared with similarly performing healthy participants during a verbal n-back task. Dynamic causal modeling (DCM) of the coupling...... between regions (left inferior frontal gyrus (IFG), left inferior parietal lobe (IPL), and primary visual area) identified in a psychophysiological interaction (PPI) analysis was performed to characterize effective connectivity during the n-back task. The PPI analysis revealed that the connectivity...

  3. Analysis of hepatocellular carcinoma and metastatic hepatic carcinoma via functional modules in a protein-protein interaction network

    Jun Pan

    2014-01-01

    Full Text Available Introduction: This study aims to identify protein clusters with potential functional relevance in the pathogenesis of hepatocellular carcinoma (HCC and metastatic hepatic carcinoma using network analysis. Materials and Methods: We used human protein interaction data to build a protein-protein interaction network with Cytoscape and then derived functional clusters using MCODE. Combining the gene expression profiles, we calculated the functional scores for the clusters and selected statistically significant clusters. Meanwhile, Gene Ontology was used to assess the functionality of these clusters. Finally, a support vector machine was trained on the gold standard data sets. Results: The differentially expressed genes of HCC were mainly involved in metabolic and signaling processes. We acquired 13 significant modules from the gene expression profiles. The area under the curve value based on the differentially expressed modules were 98.31%, which outweighed the classification with DEGs. Conclusions: Differentially expressed modules are valuable to screen biomarkers combined with functional modules.

  4. Hippocampal Ripple Oscillations and Inhibition-First Network Models: Frequency Dynamics and Response to GABA Modulators.

    Donoso, José R; Schmitz, Dietmar; Maier, Nikolaus; Kempter, Richard

    2018-03-21

    Hippocampal ripples are involved in memory consolidation, but the mechanisms underlying their generation remain unclear. Models relying on interneuron networks in the CA1 region disagree on the predominant source of excitation to interneurons: either "direct," via the Schaffer collaterals that provide feedforward input from CA3 to CA1, or "indirect," via the local pyramidal cells in CA1, which are embedded in a recurrent excitatory-inhibitory network. Here, we used physiologically constrained computational models of basket-cell networks to investigate how they respond to different conditions of transient, noisy excitation. We found that direct excitation of interneurons could evoke ripples (140-220 Hz) that exhibited intraripple frequency accommodation and were frequency-insensitive to GABA modulators, as previously shown in in vitro experiments. In addition, the indirect excitation of the basket-cell network enabled the expression of intraripple frequency accommodation in the fast-gamma range (90-140 Hz), as in vivo In our model, intraripple frequency accommodation results from a hysteresis phenomenon in which the frequency responds differentially to the rising and descending phases of the transient excitation. Such a phenomenon predicts a maximum oscillation frequency occurring several milliseconds before the peak of excitation. We confirmed this prediction for ripples in brain slices from male mice. These results suggest that ripple and fast-gamma episodes are produced by the same interneuron network that is recruited via different excitatory input pathways, which could be supported by the previously reported intralaminar connectivity bias between basket cells and functionally distinct subpopulations of pyramidal cells in CA1. Together, our findings unify competing inhibition-first models of rhythm generation in the hippocampus. SIGNIFICANCE STATEMENT The hippocampus is a part of the brain of humans and other mammals that is critical for the acquisition and

  5. Competitive STDP Learning of Overlapping Spatial Patterns.

    Krunglevicius, Dalius

    2015-08-01

    Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

  6. Network-state modulation of power-law frequency-scaling in visual cortical neurons.

    El Boustani, Sami; Marre, Olivier; Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves

    2009-09-01

    Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of V(m) activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the V(m) reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the "effective" connectivity responsible for the dynamical signature of the population signals measured

  7. Network-state modulation of power-law frequency-scaling in visual cortical neurons.

    Sami El Boustani

    2009-09-01

    Full Text Available Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of V(m activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the V(m reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the "effective" connectivity responsible for the dynamical signature of the population

  8. Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

    He Weiming

    2010-07-01

    Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

  9. Barium Titanate Photonic Crystal Electro-Optic Modulators for Telecommunication and Data Network Applications

    Girouard, Peter D.

    The microwave, optical, and electro-optic properties of epitaxial barium titanate thin films grown on (100) MgO substrates and photonic crystal electro-optic modulators fabricated on these films were investigated to demonstrate the applicability of these devices for telecommunication and data networks. The electrical and electro-optical properties were characterized up to modulation frequencies of 50 GHz, and the optical properties of photonic crystal waveguides were determined for wavelengths spanning the optical C band between 1500 and 1580 nm. Microwave scattering parameters were measured on coplanar stripline devices with electrode gap spacings between 5 and 12 mum on barium titanate films with thicknesses between 230 and 680 nm. The microwave index and device characteristic impedance were obtained from the measurements. Larger (lower) microwave indices (impedances) were obtained for devices with narrower electrode gap spacings and on thicker films. Thinner film devices have both lower index mismatch between the co-propagating microwave and optical signals and lower impedance mismatch to a 50O system, resulting in a larger predicted electro-optical 3 dB bandwidth. This was experimentally verified with electro-optical frequency response measurements. These observations were applied to demonstrate a record high 28 GHz electro-optic bandwidth measured for a BaTiO3 conventional ridge waveguide modulator having 1mm long electrodes and 12 mum gap spacing on a 260nm thick film. The half-wave voltage and electro-optic coefficients of barium titanate modulators were measured for films having thicknesses between 260 and 500 nm. The half-wave voltage was directly measured at low frequencies using a polarizer-sample-compensator-analyzer setup by over-driving waveguide integrated modulators beyond their linear response regime. Effective in-device electro-optic coefficients were obtained from the measured half-wave voltages. The effective electro-optic coefficients were

  10. How long do satellites need to overlap? Evaluation of climate data stability from overlapping satellite records

    Weatherhead, Elizabeth C.; Harder, Jerald; Araujo-Pradere, Eduardo A.; Bodeker, Greg; English, Jason M.; Flynn, Lawrence E.; Frith, Stacey M.; Lazo, Jeffrey K.; Pilewskie, Peter; Weber, Mark; Woods, Thomas N.

    2017-12-01

    applicable to satellite Earth observations. Approaches for Earth observations offer additional challenges due to the complexity of the observations, but Earth observations may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.

  11. Cortical hubs form a module for multisensory integration on top of the hierarchy of cortical networks

    Gorka Zamora-López

    2010-03-01

    Full Text Available Sensory stimuli entering the nervous system follow particular paths of processing, typically separated (segregated from the paths of other modal information. However, sensory perception, awareness and cognition emerge from the combination of information (integration. The corticocortical networks of cats and macaque monkeys display three prominent characteristics: (i modular organisation (facilitating the segregation, (ii abundant alternative processing paths and (iii the presence of highly connected hubs. Here, we study in detail the organisation and potential function of the cortical hubs by graph analysis and information theoretical methods. We find that the cortical hubs form a spatially delocalised, but topologically central module with the capacity to integrate multisensory information in a collaborative manner. With this, we resolve the underlying anatomical substrate that supports the simultaneous capacity of the cortex to segregate and to integrate multisensory information.

  12. Experience on the FMS Communication module Development for an Application to Safety- Critical Communication Network

    Son, Kwang Seop; Lee, Jang Soo; Kim, Jung Heon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2009-05-15

    The field bus has been developed for a network system which supports the real-time communication of various controls and automation equipment. It is known for Profibus in the field of a production automation environment. The Profibus standard uses open communication based on the ISO/OSI model. The Probibus standard uses layer 1, layer 2, layer 7. Layer 7 of Probibus FMS(Fieldbus Message Specification) provides a information and the user of a station. The high-level communication of the safety-grade PLC (POSAFE-Q) developed through the KNICS(Korea Nuclear I and C System) project is the FMS This paper describes the design, the configuration, and the test method of the FMS communication module.

  13. Experience on the FMS Communication module Development for an Application to Safety- Critical Communication Network

    Son, Kwang Seop; Lee, Jang Soo; Kim, Jung Heon

    2009-01-01

    The field bus has been developed for a network system which supports the real-time communication of various controls and automation equipment. It is known for Profibus in the field of a production automation environment. The Profibus standard uses open communication based on the ISO/OSI model. The Probibus standard uses layer 1, layer 2, layer 7. Layer 7 of Probibus FMS(Fieldbus Message Specification) provides a information and the user of a station. The high-level communication of the safety-grade PLC (POSAFE-Q) developed through the KNICS(Korea Nuclear I and C System) project is the FMS This paper describes the design, the configuration, and the test method of the FMS communication module

  14. Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M; Dan, Bernard; McIntyre, Joseph; Cheron, Guy

    2014-01-01

    In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

  15. Accurate optical vector network analyzer based on optical single-sideband modulation and balanced photodetection.

    Xue, Min; Pan, Shilong; Zhao, Yongjiu

    2015-02-15

    A novel optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation and balanced photodetection is proposed and experimentally demonstrated, which can eliminate the measurement error induced by the high-order sidebands in the OSSB signal. According to the analytical model of the conventional OSSB-based OVNA, if the optical carrier in the OSSB signal is fully suppressed, the measurement result is exactly the high-order-sideband-induced measurement error. By splitting the OSSB signal after the optical device-under-test (ODUT) into two paths, removing the optical carrier in one path, and then detecting the two signals in the two paths using a balanced photodetector (BPD), high-order-sideband-induced measurement error can be ideally eliminated. As a result, accurate responses of the ODUT can be achieved without complex post-signal processing. A proof-of-concept experiment is carried out. The magnitude and phase responses of a fiber Bragg grating (FBG) measured by the proposed OVNA with different modulation indices are superimposed, showing that the high-order-sideband-induced measurement error is effectively removed.

  16. Modulation of Cortical-subcortical Networks in Parkinson’s Disease by Applied Field Effects

    Christopher William Hess

    2013-09-01

    Full Text Available Studies suggest that endogenous field effects may play a role in neuronal oscillations and communication. Non-invasive transcranial electrical stimulation with low-intensity currents can also have direct effects on the underlying cortex as well as distant network effects. While Parkinson's disease (PD is amenable to invasive neuromodulation in the basal ganglia by deep brain stimulation, techniques of non-invasive neuromodulation like transcranial direct current stimulation (tDCS and transcranial alternating current stimulation (tACS are being investigated as possible therapies. tDCS and tACS have the potential to influence the abnormal cortical-subcortical network activity that occurs in PD through sub-threshold changes in cortical excitability or through entrainment or disruption of ongoing rhythmic cortical activity. This may allow for the targeting of specific features of the disease involving abnormal oscillatory activity, as well as the enhancement of potential cortical compensation for basal ganglia dysfunction and modulation of cortical plasticity in neurorehabilitation. However, little is currently known about how cortical stimulation will affect subcortical structures, the size of any effect, and the factors of stimulation that will influence these effects.

  17. Treatment with olanzapine is associated with modulation of the default mode network in patients with Schizophrenia.

    Sambataro, Fabio; Blasi, Giuseppe; Fazio, Leonardo; Caforio, Grazia; Taurisano, Paolo; Romano, Raffaella; Di Giorgio, Annabella; Gelao, Barbara; Lo Bianco, Luciana; Papazacharias, Apostolos; Popolizio, Teresa; Nardini, Marcello; Bertolino, Alessandro

    2010-03-01

    Earlier studies have shown widespread alterations of functional connectivity of various brain networks in schizophrenia, including the default mode network (DMN). The DMN has also an important role in the performance of cognitive tasks. Furthermore, treatment with second-generation antipsychotic drugs may ameliorate to some degree working memory (WM) deficits and related brain activity. The aim of this study was to evaluate the effects of treatment with olanzapine monotherapy on functional connectivity among brain regions of the DMN during WM. Seventeen patients underwent an 8-week prospective study and completed two functional magnetic resonance imaging (fMRI) scans at 4 and 8 weeks of treatment during the performance of the N-back WM task. To control for potential repetition effects, 19 healthy controls also underwent two fMRI scans at a similar time interval. We used spatial group-independent component analysis (ICA) to analyze fMRI data. Relative to controls, patients with schizophrenia had reduced connectivity strength within the DMN in posterior cingulate, whereas it was greater in precuneus and inferior parietal lobule. Treatment with olanzapine was associated with increases in DMN connectivity with ventromedial prefrontal cortex, but not in posterior regions of DMN. These results suggest that treatment with olanzapine is associated with the modulation of DMN connectivity in schizophrenia. In addition, our findings suggest critical functional differences in the regions of DMN.

  18. Acupuncture analgesia involves modulation of pain-induced gamma oscillations and cortical network connectivity.

    Hauck, Michael; Schröder, Sven; Meyer-Hamme, Gesa; Lorenz, Jürgen; Friedrichs, Sunja; Nolte, Guido; Gerloff, Christian; Engel, Andreas K

    2017-11-24

    Recent studies support the view that cortical sensory, limbic and executive networks and the autonomic nervous system might interact in distinct manners under the influence of acupuncture to modulate pain. We performed a double-blind crossover design study to investigate subjective ratings, EEG and ECG following experimental laser pain under the influence of sham and verum acupuncture in 26 healthy volunteers. We analyzed neuronal oscillations and inter-regional coherence in the gamma band of 128-channel-EEG recordings as well as heart rate variability (HRV) on two experimental days. Pain ratings and pain-induced gamma oscillations together with vagally-mediated power in the high-frequency bandwidth (vmHF) of HRV decreased significantly stronger during verum than sham acupuncture. Gamma oscillations were localized in the prefrontal cortex (PFC), mid-cingulate cortex (MCC), primary somatosensory cortex and insula. Reductions of pain ratings and vmHF-power were significantly correlated with increase of connectivity between the insula and MCC. In contrast, connectivity between left and right PFC and between PFC and insula correlated positively with vmHF-power without a relationship to acupuncture analgesia. Overall, these findings highlight the influence of the insula in integrating activity in limbic-saliency networks with vagally mediated homeostatic control to mediate antinociception under the influence of acupuncture.

  19. The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network.

    Fernanda Palhano-Fontes

    Full Text Available The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN, a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN. Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC/Precuneus and the medial Prefrontal Cortex (mPFC. Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic, meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.

  20. The psychedelic state induced by ayahuasca modulates the activity and connectivity of the default mode network.

    Palhano-Fontes, Fernanda; Andrade, Katia C; Tofoli, Luis F; Santos, Antonio C; Crippa, Jose Alexandre S; Hallak, Jaime E C; Ribeiro, Sidarta; de Araujo, Draulio B

    2015-01-01

    The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.

  1. Modulation of attention network activation under antidepressant agents in healthy subjects.

    Graf, Heiko; Abler, Birgit; Hartmann, Antonie; Metzger, Coraline D; Walter, Martin

    2013-07-01

    While antidepressants are supposed to exert similar effects on mood and drive via various mechanisms of action, diverging effects are observed regarding side-effects and accordingly on neural correlates of motivation, emotion, reward and salient stimuli processing as a function of the drugs impact on neurotransmission. In the context of erotic stimulation, a unidirectional modulation of attentional functioning despite opposite effects on sexual arousal has been suggested for the selective serotonin reuptake-inhibitor (SSRI) paroxetine and the selective dopamine and noradrenaline reuptake-inhibitor (SDNRI) bupropion. To further elucidate the effects of antidepressant-related alterations of neural attention networks, we investigated 18 healthy males under subchronic administration (7 d) of paroxetine (20 mg), bupropion (150 mg) and placebo within a randomized placebo-controlled cross-over double-blind functional magnetic resonance imaging (fMRI) design during an established preceding attention task. Neuropsychological effects beyond the fMRI-paradigm were assessed by measuring alertness and divided attention. Comparing preceding attention periods of salient vs. neutral pictures, we revealed congruent effects of both drugs vs. placebo within the anterior midcingulate cortex, dorsolateral prefrontal cortex, anterior prefrontal cortex, superior temporal gyrus, anterior insula and the thalamus. Relatively decreased activation in this network was paralleled by slower reaction times in the divided attention task in both verum conditions compared to placebo. Our results suggest similar effects of antidepressant treatments on behavioural and neural attentional functioning by diverging neurochemical pathways. Concurrent alterations of brain regions within a fronto-parietal and cingulo-opercular attention network for top-down control could point to basic neural mechanisms of antidepressant action irrespective of receptor profiles.

  2. Modulations of the executive control network by stimulus onset asynchrony in a Stroop task

    2013-01-01

    Background Manipulating task difficulty is a useful way of elucidating the functional recruitment of the brain’s executive control network. In a Stroop task, pre-exposing the irrelevant word using varying stimulus onset asynchronies (‘negative’ SOAs) modulates the amount of behavioural interference and facilitation, suggesting disparate mechanisms of cognitive processing in each SOA. The current study employed a Stroop task with three SOAs (−400, -200, 0 ms), using functional magnetic resonance imaging to investigate for the first time the neural effects of SOA manipulation. Of specific interest were 1) how SOA affects the neural representation of interference and facilitation; 2) response priming effects in negative SOAs; and 3) attentional effects of blocked SOA presentation. Results The results revealed three regions of the executive control network that were sensitive to SOA during Stroop interference; the 0 ms SOA elicited the greatest activation of these areas but experienced relatively smaller behavioural interference, suggesting that the enhanced recruitment led to more efficient conflict processing. Response priming effects were localized to the right inferior frontal gyrus, which is consistent with the idea that this region performed response inhibition in incongruent conditions to overcome the incorrectly-primed response, as well as more general action updating and response preparation. Finally, the right superior parietal lobe was sensitive to blocked SOA presentation and was most active for the 0 ms SOA, suggesting that this region is involved in attentional control. Conclusions SOA exerted both trial-specific and block-wide effects on executive processing, providing a unique paradigm for functional investigations of the cognitive control network. PMID:23902451

  3. A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks.

    Gallos, Lazaros K; Makse, Hernán A; Sigman, Mariano

    2012-02-21

    The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are "large-world" self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the "strength of weak ties" crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain.

  4. Nonorthogonal multiple access and carrierless amplitude phase modulation for flexible multiuser provisioning in 5G mobile networks

    Altabas, J.A.; Rommel, S.; Puerta, R.; Izquierdo, D.; Ignacio Garces, J.; Antonio Lazaro, J.; Vegas Olmos, J.J.; Tafur Monroy, I.

    2017-01-01

    In this paper, a combined nonorthogonal multiple access (NOMA) and multiband carrierless amplitude phase modulation (multiCAP) scheme is proposed for capacity enhancement of and flexible resource provisioning in 5G mobile networks. The proposed scheme is experimentally evaluated over a W-band

  5. Interaction of multiple networks modulated by the working memory training based on real-time fMRI

    Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

    2015-03-01

    Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

  6. Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

    Uddin, Raihan; Singh, Shiva M

    2017-01-01

    As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

  7. Evaluation of four-dimensional nonbinary LDPC-coded modulation for next-generation long-haul optical transport networks.

    Zhang, Yequn; Arabaci, Murat; Djordjevic, Ivan B

    2012-04-09

    Leveraging the advanced coherent optical communication technologies, this paper explores the feasibility of using four-dimensional (4D) nonbinary LDPC-coded modulation (4D-NB-LDPC-CM) schemes for long-haul transmission in future optical transport networks. In contrast to our previous works on 4D-NB-LDPC-CM which considered amplified spontaneous emission (ASE) noise as the dominant impairment, this paper undertakes transmission in a more realistic optical fiber transmission environment, taking into account impairments due to dispersion effects, nonlinear phase noise, Kerr nonlinearities, and stimulated Raman scattering in addition to ASE noise. We first reveal the advantages of using 4D modulation formats in LDPC-coded modulation instead of conventional two-dimensional (2D) modulation formats used with polarization-division multiplexing (PDM). Then we demonstrate that 4D LDPC-coded modulation schemes with nonbinary LDPC component codes significantly outperform not only their conventional PDM-2D counterparts but also the corresponding 4D bit-interleaved LDPC-coded modulation (4D-BI-LDPC-CM) schemes, which employ binary LDPC codes as component codes. We also show that the transmission reach improvement offered by the 4D-NB-LDPC-CM over 4D-BI-LDPC-CM increases as the underlying constellation size and hence the spectral efficiency of transmission increases. Our results suggest that 4D-NB-LDPC-CM can be an excellent candidate for long-haul transmission in next-generation optical networks.

  8. Modular co-evolution of metabolic networks

    Yu Zhong-Hao

    2007-08-01

    Full Text Available Abstract Background The architecture of biological networks has been reported to exhibit high level of modularity, and to some extent, topological modules of networks overlap with known functional modules. However, how the modular topology of the molecular network affects the evolution of its member proteins remains unclear. Results In this work, the functional and evolutionary modularity of Homo sapiens (H. sapiens metabolic network were investigated from a topological point of view. Network decomposition shows that the metabolic network is organized in a highly modular core-periphery way, in which the core modules are tightly linked together and perform basic metabolism functions, whereas the periphery modules only interact with few modules and accomplish relatively independent and specialized functions. Moreover, over half of the modules exhibit co-evolutionary feature and belong to specific evolutionary ages. Peripheral modules tend to evolve more cohesively and faster than core modules do. Conclusion The correlation between functional, evolutionary and topological modularity suggests that the evolutionary history and functional requirements of metabolic systems have been imprinted in the architecture of metabolic networks. Such systems level analysis could demonstrate how the evolution of genes may be placed in a genome-scale network context, giving a novel perspective on molecular evolution.

  9. Prediction of the anti-inflammatory mechanisms of curcumin by module-based protein interaction network analysis

    Yanxiong Gan

    2015-11-01

    Full Text Available Curcumin, the medically active component from Curcuma longa (Turmeric, is widely used to treat inflammatory diseases. Protein interaction network (PIN analysis was used to predict its mechanisms of molecular action. Targets of curcumin were obtained based on ChEMBL and STITCH databases. Protein–protein interactions (PPIs were extracted from the String database. The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology (GO enrichment analysis based on molecular complex detection (MCODE. A PIN of curcumin with 482 nodes and 1688 interactions was constructed, which has scale-free, small world and modular properties. Based on analysis of these function modules, the mechanism of curcumin is proposed. Two modules were found to be intimately associated with inflammation. With function modules analysis, the anti-inflammatory effects of curcumin were related to SMAD, ERG and mediation by the TLR family. TLR9 may be a potential target of curcumin to treat inflammation.

  10. Non-binary coded modulation for FMF-based coherent optical transport networks

    Lin, Changyu

    The Internet has fundamentally changed the way of modern communication. Current trends indicate that high-capacity demands are not going to be saturated anytime soon. From Shannon's theory, we know that information capacity is a logarithmic function of signal-to-noise ratio (SNR), but a linear function of the number of dimensions. Ideally, we can increase the capacity by increasing the launch power, however, due to the nonlinear characteristics of silica optical fibers that imposes a constraint on the maximum achievable optical-signal-to-noise ratio (OSNR). So there exists a nonlinear capacity limit on the standard single mode fiber (SSMF). In order to satisfy never ending capacity demands, there are several attempts to employ additional degrees of freedom in transmission system, such as few-mode fibers (FMFs), which can dramatically improve the spectral efficiency. On the other hand, for the given physical links and network equipment, an effective solution to relax the OSNR requirement is based on forward error correction (FEC), as the response to the demands of high speed reliable transmission. In this dissertation, we first discuss the model of FMF with nonlinear effects considered. Secondly, we simulate the FMF based OFDM system with various compensation and modulation schemes. Thirdly, we propose tandem-turbo-product nonbinary byte-interleaved coded modulation (BICM) for next-generation high-speed optical transmission systems. Fourthly, we study the Q factor and mutual information as threshold in BICM scheme. Lastly, an experimental study of the limits of nonlinearity compensation with digital signal processing has been conducted.

  11. An ELMO2-RhoG-ILK network modulates microtubule dynamics.

    Jackson, Bradley C; Ivanova, Iordanka A; Dagnino, Lina

    2015-07-15

    ELMO2 belongs to a family of scaffold proteins involved in phagocytosis and cell motility. ELMO2 can simultaneously bind integrin-linked kinase (ILK) and RhoG, forming tripartite ERI complexes. These complexes are involved in promoting β1 integrin-dependent directional migration in undifferentiated epidermal keratinocytes. ELMO2 and ILK have also separately been implicated in microtubule regulation at integrin-containing focal adhesions. During differentiation, epidermal keratinocytes cease to express integrins, but ERI complexes persist. Here we show an integrin-independent role of ERI complexes in modulation of microtubule dynamics in differentiated keratinocytes. Depletion of ERI complexes by inactivating the Ilk gene in these cells reduces microtubule growth and increases the frequency of catastrophe. Reciprocally, exogenous expression of ELMO2 or RhoG stabilizes microtubules, but only if ILK is also present. Mechanistically, activation of Rac1 downstream from ERI complexes mediates their effects on microtubule stability. In this pathway, Rac1 serves as a hub to modulate microtubule dynamics through two different routes: 1) phosphorylation and inactivation of the microtubule-destabilizing protein stathmin and 2) phosphorylation and inactivation of GSK-3β, which leads to the activation of CRMP2, promoting microtubule growth. At the cellular level, the absence of ERI species impairs Ca(2+)-mediated formation of adherens junctions, critical to maintaining mechanical integrity in the epidermis. Our findings support a key role for ERI species in integrin-independent stabilization of the microtubule network in differentiated keratinocytes. © 2015 Jackson et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  12. Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia.

    Ruiz, Sergio; Lee, Sangkyun; Soekadar, Surjo R; Caria, Andrea; Veit, Ralf; Kircher, Tilo; Birbaumer, Niels; Sitaram, Ranganatha

    2013-01-01

    Real-time functional magnetic resonance imaging (rtfMRI) is a novel technique that has allowed subjects to achieve self-regulation of circumscribed brain regions. Despite its anticipated therapeutic benefits, there is no report on successful application of this technique in psychiatric populations. The objectives of the present study were to train schizophrenia patients to achieve volitional control of bilateral anterior insula cortex on multiple days, and to explore the effect of learned self-regulation on face emotion recognition (an extensively studied deficit in schizophrenia) and on brain network connectivity. Nine patients with schizophrenia were trained to regulate the hemodynamic response in bilateral anterior insula with contingent rtfMRI neurofeedback, through a 2-weeks training. At the end of the training stage, patients performed a face emotion recognition task to explore behavioral effects of learned self-regulation. A learning effect in self-regulation was found for bilateral anterior insula, which persisted through the training. Following successful self-regulation, patients recognized disgust faces more accurately and happy faces less accurately. Improvements in disgust recognition were correlated with levels of self-activation of right insula. RtfMRI training led to an increase in the number of the incoming and outgoing effective connections of the anterior insula. This study shows for the first time that patients with schizophrenia can learn volitional brain regulation by rtfMRI feedback training leading to changes in the perception of emotions and modulations of the brain network connectivity. These findings open the door for further studies of rtfMRI in severely ill psychiatric populations, and possible therapeutic applications. Copyright © 2011 Wiley Periodicals, Inc.

  13. Interaction of acupuncture treatment and manipulation laterality modulated by the default mode network.

    Niu, Xuan; Zhang, Ming; Liu, Zhenyu; Bai, Lijun; Sun, Chuanzhu; Wang, Shan; Wang, Xiaocui; Chen, Zhen; Chen, Hongyan; Tian, Jie

    2017-01-01

    lobule, inferior parietal lobule, precuneus, and left posterior cingulate cortex. It is also proved that disruptions of the default mode network may account for the cognitive and behavioral impairments in chronic pain patients. Our findings further suggested that default mode network participates in the modulation of spatial-oriented attention on placebo analgesia as a mechanism underlying the degree to which treatment side corresponding to the pain.

  14. Flexible establishment of functional brain networks supports attentional modulation of unconscious cognition.

    Ulrich, Martin; Adams, Sarah C; Kiefer, Markus

    2014-11-01

    In classical theories of attention, unconscious automatic processes are thought to be independent of higher-level attentional influences. Here, we propose that unconscious processing depends on attentional enhancement of task-congruent processing pathways implemented by a dynamic modulation of the functional communication between brain regions. Using functional magnetic resonance imaging, we tested our model with a subliminally primed lexical decision task preceded by an induction task preparing either a semantic or a perceptual task set. Subliminal semantic priming was significantly greater after semantic compared to perceptual induction in ventral occipito-temporal (vOT) and inferior frontal cortex, brain areas known to be involved in semantic processing. The functional connectivity pattern of vOT varied depending on the induction task and successfully predicted the magnitude of behavioral and neural priming. Together, these findings support the proposal that dynamic establishment of functional networks by task sets is an important mechanism in the attentional control of unconscious processing. © 2014 Wiley Periodicals, Inc.

  15. The Mechanism Research of Qishen Yiqi Formula by Module-Network Analysis

    Shichao Zheng

    2015-01-01

    Full Text Available Qishen Yiqi formula (QSYQ has the effect of tonifying Qi and promoting blood circulation, which is widely used to treat the cardiovascular diseases with Qi deficiency and blood stasis syndrome. However, the mechanism of QSYQ to tonify Qi and promote blood circulation is rarely reported at molecular or systems level. This study aimed to elucidate the mechanism of QSYQ based on the protein interaction network (PIN analysis. The targets’ information of the active components was obtained from ChEMBL and STITCH databases and was further used to search against protein-protein interactions by String database. Next, the PINs of QSYQ were constructed by Cytoscape and were analyzed by gene ontology enrichment analysis based on Markov Cluster algorithm. Finally, based on the topological parameters, the properties of scale-free, small world, and modularity of the QSYQ’s PINs were analyzed. And based on function modules, the mechanism of QSYQ was elucidated. The results indicated that Qi-tonifying efficacy of QSYQ may be partly attributed to the regulation of amino acid metabolism, carbohydrate metabolism, lipid metabolism, and cAMP metabolism, while QSYQ improves the blood stasis through the regulation of blood coagulation and cardiac muscle contraction. Meanwhile, the “synergy” of formula compatibility was also illuminated.

  16. Modulation of cultured neural networks using neurotrophin release from hydrogel-coated microelectrode arrays

    Jun, Sang Beom; Hynd, Matthew R.; Dowell-Mesfin, Natalie M.; Al-Kofahi, Yousef; Roysam, Badrinath; Shain, William; Kim, Sung June

    2008-06-01

    Polyacrylamide and poly(ethylene glycol) diacrylate hydrogels were synthesized and characterized for use as drug release and substrates for neuron cell culture. Protein release kinetics was determined by incorporating bovine serum albumin (BSA) into hydrogels during polymerization. To determine if hydrogel incorporation and release affect bioactivity, alkaline phosphatase was incorporated into hydrogels and a released enzyme activity determined using the fluorescence-based ELF-97 assay. Hydrogels were then used to deliver a brain-derived neurotrophic factor (BDNF) from hydrogels polymerized over planar microelectrode arrays (MEAs). Primary hippocampal neurons were cultured on both control and neurotrophin-containing hydrogel-coated MEAs. The effect of released BDNF on neurite length and process arborization was investigated using automated image analysis. An increased spontaneous activity as a response to the released BDNF was recorded from the neurons cultured on the top of hydrogel layers. These results demonstrate that proteins of biological interest can be incorporated into hydrogels to modulate development and function of cultured neural networks. These results also set the stage for development of hydrogel-coated neural prosthetic devices for local delivery of various biologically active molecules.

  17. Wideband optical vector network analyzer based on optical single-sideband modulation and optical frequency comb.

    Xue, Min; Pan, Shilong; He, Chao; Guo, Ronghui; Zhao, Yongjiu

    2013-11-15

    A novel approach to increase the measurement range of the optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation is proposed and experimentally demonstrated. In the proposed system, each comb line in an optical frequency comb (OFC) is selected by an optical filter and used as the optical carrier for the OSSB-based OVNA. The frequency responses of an optical device-under-test (ODUT) are thus measured channel by channel. Because the comb lines in the OFC have fixed frequency spacing, by fitting the responses measured in all channels together, the magnitude and phase responses of the ODUT can be accurately achieved in a large range. A proof-of-concept experiment is performed. A measurement range of 105 GHz and a resolution of 1 MHz is achieved when a five-comb-line OFC with a frequency spacing of 20 GHz is applied to measure the magnitude and phase responses of a fiber Bragg grating.

  18. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

    Xinguo Lu

    2018-01-01

    Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

  19. Overlapping communities detection based on spectral analysis of line graphs

    Gui, Chun; Zhang, Ruisheng; Hu, Rongjing; Huang, Guoming; Wei, Jiaxuan

    2018-05-01

    Community in networks are often overlapping where one vertex belongs to several clusters. Meanwhile, many networks show hierarchical structure such that community is recursively grouped into hierarchical organization. In order to obtain overlapping communities from a global hierarchy of vertices, a new algorithm (named SAoLG) is proposed to build the hierarchical organization along with detecting the overlap of community structure. SAoLG applies the spectral analysis into line graphs to unify the overlap and hierarchical structure of the communities. In order to avoid the limitation of absolute distance such as Euclidean distance, SAoLG employs Angular distance to compute the similarity between vertices. Furthermore, we make a micro-improvement partition density to evaluate the quality of community structure and use it to obtain the more reasonable and sensible community numbers. The proposed SAoLG algorithm achieves a balance between overlap and hierarchy by applying spectral analysis to edge community detection. The experimental results on one standard network and six real-world networks show that the SAoLG algorithm achieves higher modularity and reasonable community number values than those generated by Ahn's algorithm, the classical CPM and GN ones.

  20. Modeling reveals bistability and low-pass filtering in the network module determining blood stem cell fate.

    Jatin Narula

    2010-05-01

    Full Text Available Combinatorial regulation of gene expression is ubiquitous in eukaryotes with multiple inputs converging on regulatory control elements. The dynamic properties of these elements determine the functionality of genetic networks regulating differentiation and development. Here we propose a method to quantitatively characterize the regulatory output of distant enhancers with a biophysical approach that recursively determines free energies of protein-protein and protein-DNA interactions from experimental analysis of transcriptional reporter libraries. We apply this method to model the Scl-Gata2-Fli1 triad-a network module important for cell fate specification of hematopoietic stem cells. We show that this triad module is inherently bistable with irreversible transitions in response to physiologically relevant signals such as Notch, Bmp4 and Gata1 and we use the model to predict the sensitivity of the network to mutations. We also show that the triad acts as a low-pass filter by switching between steady states only in response to signals that persist for longer than a minimum duration threshold. We have found that the auto-regulation loops connecting the slow-degrading Scl to Gata2 and Fli1 are crucial for this low-pass filtering property. Taken together our analysis not only reveals new insights into hematopoietic stem cell regulatory network functionality but also provides a novel and widely applicable strategy to incorporate experimental measurements into dynamical network models.

  1. Cost Effectiveness Analysis of Converting a Classroom Course to a Network Based Instruction Module

    green, Samantha

    1997-01-01

    ...) classes into NBL modules. This thesis performs a cost effectiveness analysis on converting the two modules and discusses the intangible costs and benefits associated with converting traditional classroom courses...

  2. Apparel Research Network (ARN); Apparel Order Processing Module (AOPM): Field User Manual, Version 1

    1997-09-30

    changes. Cancel Button Closes the Site Information Screen, abandoning changes. APPAREL ORDER PROCESSING MODULE FIELD USER MANUAL Ordering Official...on the Ordering Official Information Screen. APPAREL ORDER PROCESSING MODULE FIELD USER MANUAL Ordering Official Information Screen (Jjj

  3. Topological susceptibility from the overlap

    Del Debbio, Luigi; Pica, Claudio

    2003-01-01

    The chiral symmetry at finite lattice spacing of Ginsparg-Wilson fermionic actions constrains the renormalization of the lattice operators; in particular, the topological susceptibility does not require any renormalization, when using a fermionic estimator to define the topological charge....... Therefore, the overlap formalism appears as an appealing candidate to study the continuum limit of the topological susceptibility while keeping the systematic errors under theoretical control. We present results for the SU(3) pure gauge theory using the index of the overlap Dirac operator to study...

  4. A 3D Lumped Thermal Network Model for Long-term Load Profiles Analysis in High Power IGBT Modules

    Bahman, Amir Sajjad; Ma, Ke; Ghimire, Pramod

    2016-01-01

    )-based simulation is another method which is often used to analyze the steady-state thermal distribution of IGBT modules, but it is not possible to be used for long-term analysis of load profiles of power converter, which is needed for reliability assessments and better thermal design. This paper proposes a novel...... enables both accurate and fast temperature estimation of high power IGBT modules in the real loading conditions of the converter; meanwhile the critical details of the thermal dynamics and thermal distribution are also maintained. The proposed thermal model is verified by both FEM simulation......The conventional RC lumped thermal networks are widely used to estimate the temperature of power devices, but they are lack of accuracy in addressing detailed thermal behaviors/couplings in different locations and layers of the high power IGBT modules. On the other hand, Finite Element (FE...

  5. Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.

    Gu, Yunyan; Wang, Hongwei; Qin, Yao; Zhang, Yujing; Zhao, Wenyuan; Qi, Lishuang; Zhang, Yuannv; Wang, Chenguang; Guo, Zheng

    2013-03-01

    The heterogeneity of genetic alterations in human cancer genomes presents a major challenge to advancing our understanding of cancer mechanisms and identifying cancer driver genes. To tackle this heterogeneity problem, many approaches have been proposed to investigate genetic alterations and predict driver genes at the individual pathway level. However, most of these approaches ignore the correlation of alteration events between pathways and miss many genes with rare alterations collectively contributing to carcinogenesis. Here, we devise a network-based approach to capture the cooperative functional modules hidden in genome-wide somatic mutation and copy number alteration profiles of glioblastoma (GBM) from The Cancer Genome Atlas (TCGA), where a module is a set of altered genes with dense interactions in the protein interaction network. We identify 7 pairs of significantly co-altered modules that involve the main pathways known to be altered in GBM (TP53, RB and RTK signaling pathways) and highlight the striking co-occurring alterations among these GBM pathways. By taking into account the non-random correlation of gene alterations, the property of co-alteration could distinguish oncogenic modules that contain driver genes involved in the progression of GBM. The collaboration among cancer pathways suggests that the redundant models and aggravating models could shed new light on the potential mechanisms during carcinogenesis and provide new indications for the design of cancer therapeutic strategies.

  6. Enterasys Networks delivers standards-based 10-Gigabit ethernet modules for its Enterasys X-Pedition Routers and Enterasys Matrix Switches

    2002-01-01

    Enterasys Networks Inc. has announced new 10-Gigabit Ethernet modules for the Enterasys X-Pedition ER16 routers and Enterasys Matrix E1 OAS (Optical Access Switch). The addition of 10-Gigabit Ethernet technology enables the Enterasys X-Pedition ER16 enables real-time delivery of high-bandwidth, advanced applications across local area network (LAN), wide area network (WAN) and metropolitan area network (MAN) environments (1/2 page).

  7. Excitatory Modulation of the preBötzinger Complex Inspiratory Rhythm Generating Network by Endogenous Hydrogen Sulfide

    Glauber S. F. da Silva

    2017-06-01

    Full Text Available Hydrogen Sulfide (H2S is one of three gasotransmitters that modulate excitability in the CNS. Global application of H2S donors or inhibitors of H2S synthesis to the respiratory network has suggested that inspiratory rhythm is modulated by exogenous and endogenous H2S. However, effects have been variable, which may reflect that the RTN/pFRG (retrotrapezoid nucleus, parafacial respiratory group and the preBötzinger Complex (preBötC, critical for inspiratory rhythm generation are differentially modulated by exogenous H2S. Importantly, site-specific modulation of respiratory nuclei by H2S means that targeted, rather than global, manipulation of respiratory nuclei is required to understand the role of H2S signaling in respiratory control. Thus, our aim was to test whether endogenous H2S, which is produced by cystathionine-β-synthase (CBS in the CNS, acts specifically within the preBötC to modulate inspiratory activity under basal (in vitro/in vivo and hypoxic conditions (in vivo. Inhibition of endogenous H2S production by bath application of the CBS inhibitor, aminooxyacetic acid (AOAA, 0.1–1.0 mM to rhythmic brainstem spinal cord (BSSC and medullary slice preparations from newborn rats, or local application of AOAA into the preBötC (slices only caused a dose-dependent decrease in burst frequency. Unilateral injection of AOAA into the preBötC of anesthetized, paralyzed adult rats decreased basal inspiratory burst frequency, amplitude and ventilatory output. AOAA in vivo did not affect the initial hypoxia-induced (10% O2, 5 min increase in ventilatory output, but enhanced the secondary hypoxic respiratory depression. These data suggest that the preBötC inspiratory network receives tonic excitatory modulation from the CBS-H2S system, and that endogenous H2S attenuates the secondary hypoxic respiratory depression.

  8. Topological susceptibility from the overlap

    Del Debbio, Luigi; Pica, Claudio

    2004-01-01

    The chiral symmetry at finite lattice spacing of Ginsparg-Wilson fermionic actions constrains the renormalization of the lattice operators; in particular, the topological susceptibility does not require any renormalization, when using a fermionic estimator to define the topological charge. Therefore, the overlap formalism appears as an appealing candidate to study the continuum limit of the topological susceptibility while keeping the systematic errors under theoretical control. We present results for the SU(3) pure gauge theory using the index of the overlap Dirac operator to study the topology of the gauge configurations. The topological charge is obtained from the zero modes of the overlap and using a new algorithm for the spectral flow analysis. A detailed comparison with cooling techniques is presented. Particular care is taken in assessing the systematic errors. Relatively high statistics (500 to 1000 independent configurations) yield an extrapolated continuum limit with errors that are comparable with other methods. Our current value from the overlap is χ 1/4 = 188±12±5MeV (author)

  9. Angular overlap model in actinides

    Gajek, Z.; Mulak, J.

    1991-01-01

    Quantitative foundations of the Angular Overlap Model in actinides based on ab initio calculations of the crystal field effect in the uranium (III) (IV) and (V) ions in various crystals are presented. The calculations justify some common simplifications of the model and fix up the relations between the AOM parameters. Traps and limitations of the AOM phenomenology are discussed

  10. Angular overlap model in actinides

    Gajek, Z.; Mulak, J. (Polska Akademia Nauk, Wroclaw (PL). Inst. Niskich Temperatur i Badan Strukturalnych)

    1991-01-01

    Quantitative foundations of the Angular Overlap Model in actinides based on ab initio calculations of the crystal field effect in the uranium (III) (IV) and (V) ions in various crystals are presented. The calculations justify some common simplifications of the model and fix up the relations between the AOM parameters. Traps and limitations of the AOM phenomenology are discussed.

  11. The self-pleasantness judgment modulates the encoding performance and the Default Mode Network activity

    Perrone-Bertolotti eMarcela

    2016-03-01

    Full Text Available In this functional magnetic resonance imaging (fMRI study, we evaluated the effect of self-relevance on cerebral activity and behavioral performance during an incidental encoding task. Recent findings suggest that pleasantness judgments reliably induce self-oriented (internal thoughts and increase default mode network (DMN activity. We hypothesized that this increase in DMN activity would relate to increased memory recognition for pleasantly-judged stimuli (which depend on internally-oriented attention but decreased recognition for unpleasantly-judged items (which depend on externally-oriented attention. To test this hypothesis, brain activity was recorded from 21 healthy participants while they performed a pleasantness judgment requiring them to rate visual stimuli as pleasant or unpleasant. One hour later, participants performed a surprise memory recognition test outside of the scanner. Thus, we were able to evaluate the effects of pleasant and unpleasant judgments on cerebral activity and incidental encoding. The behavioral results showed that memory recognition was better for items rated as pleasant than items rated as unpleasant. The whole brain analysis indicated that successful encoding activates the inferior frontal and lateral temporal cortices, whereas unsuccessful encoding recruits two key medial posterior DMN regions, the posterior cingulate cortex and precuneus. A region of interest analysis including classic DMN areas, revealed significantly greater involvement of the medial Prefrontal Cortex in pleasant compared to unpleasant judgments, suggesting this region’s involvement in self-referential (i.e., internal processing. This area may be responsible for the greater recognition performance seen for pleasant stimuli. Furthermore, a significant interaction between the encoding performance (successful vs. unsuccessful and pleasantness was observed for the posterior cingulate cortex, precuneus and inferior frontal gyrus. Overall, our

  12. Monetary Reward and Punishment to Response Inhibition Modulate Activation and Synchronization Within the Inhibitory Brain Network

    Rupesh K. Chikara

    2018-03-01

    Full Text Available A reward or punishment can modulate motivation and emotions, which in turn affect cognitive processing. The present simultaneous functional magnetic resonance imaging-electroencephalography study examines neural mechanisms of response inhibition under the influence of a monetary reward or punishment by implementing a modified stop-signal task in a virtual battlefield scenario. The participants were instructed to play as snipers who open fire at a terrorist target but withhold shooting in the presence of a hostage. The participants performed the task under three different feedback conditions in counterbalanced order: a reward condition where each successfully withheld response added a bonus (i.e., positive feedback to the startup credit, a punishment condition where each failure in stopping deduced a penalty (i.e., negative feedback, and a no-feedback condition where response outcome had no consequences and served as a control setting. Behaviorally both reward and punishment conditions led to significantly down-regulated inhibitory function in terms of the critical stop-signal delay. As for the neuroimaging results, increased activities were found for the no-feedback condition in regions previously reported to be associated with response inhibition, including the right inferior frontal gyrus and the pre-supplementary motor area. Moreover, higher activation of the lingual gyrus, posterior cingulate gyrus (PCG and inferior parietal lobule were found in the reward condition, while stronger activation of the precuneus gyrus was found in the punishment condition. The positive feedback was also associated with stronger changes of delta, theta, and alpha synchronization in the PCG than were the negative or no-feedback conditions. These findings depicted the intertwining relationship between response inhibition and motivation networks.

  13. Modulation of steady state functional connectivity in the default mode and working memory networks by cognitive load.

    Newton, Allen T; Morgan, Victoria L; Rogers, Baxter P; Gore, John C

    2011-10-01

    Interregional correlations between blood oxygen level dependent (BOLD) magnetic resonance imaging (fMRI) signals in the resting state have been interpreted as measures of connectivity across the brain. Here we investigate whether such connectivity in the working memory and default mode networks is modulated by changes in cognitive load. Functional connectivity was measured in a steady-state verbal identity N-back task for three different conditions (N = 1, 2, and 3) as well as in the resting state. We found that as cognitive load increases, the functional connectivity within both the working memory the default mode network increases. To test whether functional connectivity between the working memory and the default mode networks changed, we constructed maps of functional connectivity to the working memory network as a whole and found that increasingly negative correlations emerged in a dorsal region of the posterior cingulate cortex. These results provide further evidence that low frequency fluctuations in BOLD signals reflect variations in neural activity and suggests interaction between the default mode network and other cognitive networks. Copyright © 2010 Wiley-Liss, Inc.

  14. Principles of Practical Training Organization in a Networking (Development of the Module "Psychological Prevention of Behavioral Disorders and Abnormalities in Development" as Example

    Bogdanovich N. V.

    2016-01-01

    Full Text Available The article presents principles of inserting study subjects and practices in educational modules running with network organizations (internship sites. We proposed a methodological basis of the modular organization of educational process in the framework of the master's program, combied the activity, competence and psychotechnical approaches. Networking of leading chair and specially selected organizations providing the base for practical training solves the problem of organizing activity-related content of educational module. We discussed the main options for networking with the databases of practice and offered methodological principles of designing the educational practice-oriented module, wherein the main principle is the reflexive and activity character of networking. We proposed activity-based content of educational module "Psychological prevention of behavioral disorders and abnormalities in development", based on the substantial psychological definition of psychoprophylaxis as a directions of professional activity of the psychologist.

  15. A high reliability module with thermoelectric device by molding technology for M2M wireless sensor network

    Nakagawa, K; Tanaka, T; Suzuki, T

    2015-01-01

    This paper presents the fabrication of a new energy harvesting module that uses a thermoelectric device (TED) by using molding technology. Through molding technology, the TED and circuit board can be properly protected and a heat-radiating fin structure can be simultaneously constructed. The output voltage per heater temperature of the TED module at 20 °C ambient temperature is 8 mV K −1 , similar to the result with the aluminum heat sink which is almost the same fin size as the TED module. The accelerated environmental tests are performed on a damp heat test, which is an aging test under high temperature and high humidity, highly accelerated temperature, and humidity stress test (HAST) for the purpose of evaluating the electrical reliability in harsh environments, cold test and thermal cycle test to evaluate degrading characteristics by cycling through two temperatures. All test results indicate that the TED and circuit board can be properly protected from harsh temperature and humidity by using molding technology because the output voltage of after-tested modules is reduced by less than 5%. This study presents a novel fabrication method for a high reliability TED-installed module appropriate for Machine to Machine wireless sensor networks. (paper)

  16. A high Reliability Module with Thermoelectric Device by Molding Technology for M2M Wireless Sensor Network

    Nakagawa, K; Tanaka, T; Suzuki, T

    2014-01-01

    This paper presents the fabrication of a new energy harvesting module that used the thermoelectric device (TED) by using molding technology. The output voltage per heater temperature of the TED module at 20 °C ambient temperature is 8mV/K and similar to the result with the aluminium heat sink which is almost the same fin size as the TED module. The accelerated environmental tests are performed on damp heat test that is an aging test under high temperature and high humidity, cold test and highly accelerated temperature and humidity stress test (HAST) for the purpose of evaluating the electrical reliability in harsh environments. Every result of tests indicates that the TED and circuit board can be properly protected from harsh temperature and humidity by using molding technology, because the output voltage of after tested modules is reduced by less than 5%.This study presents a novel fabrication method for a high reliability TED-installed module appropriate for Machine to Machine wireless sensor networks

  17. Noise-Induced Modulation of the Relaxation Kinetics around a Non-Equilibrium Steady State of Non-Linear Chemical Reaction Networks

    Ramaswamy, Rajesh; Sbalzarini, Ivo F; González-Segredo, Nélido

    2011-01-01

    Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confi...

  18. Identification of Gene Modules Associated with Low Temperatures Response in Bambara Groundnut by Network-Based Analysis.

    Venkata Suresh Bonthala

    Full Text Available Bambara groundnut (Vigna subterranea (L. Verdc. is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01 under the sub-optimal (23°C and very sub-optimal (18°C temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties.

  19. Handover Incentives for Self-Interested WLANs with Overlapping Coverage

    Fafoutis, Xenofon; Siris, Vasilios A.

    2012-01-01

    We consider an environment where self-interested IEEE 802.11 Wireless Local Area Networks (WLANs) have overlapping coverage, and investigate the incentives that can trigger handovers between the WLANs. Our focus is on the incentives for supporting handovers due solely to the improved performance...

  20. On-the-fly Overlapping of Sparse Generations

    Sørensen, Chres Wiant; Roetter, Daniel Enrique Lucani; Fitzek, Frank

    2014-01-01

    Traditionally, the idea of overlapping generations in network coding research has focused on reducing the complexity of decoding large data files while maintaining the delay performance expected of a system that combines all data packets. However, the effort for encoding and decoding individual g...

  1. [Asthma-COPD overlap syndrome].

    Odler, Balázs; Müller, Veronika

    2016-08-01

    Obstructive lung diseases represent a major health problem worldwide due to their high prevalence associated with elevated socioeconomic costs. Bronchial asthma and chronic obstructive pulmonary disease are chronic obstructive ventilatory disorders with airway inflammation, however they are separate nosological entities based on thedifferent development, diagnostic and therapeutic approaches, and prognostic features. However, these diseases may coexist and can be defined as the coexistence of increased variability of airflow in a patient with incompletely reversible airway obstruction. This phenotype is called asthma - chronic obstructive pulmonary disease overlap syndrome. The syndrome is a clinical and scientific challenge as the majority of these patients have been excluded from the clinical and pharmacological trials, thus well-defined clinical characteristics and therapeutic approaches are lacking. The aim of this review is to summarize the currently available literature focusing on pathophysiological and clinical features, and discuss possible therapeutic approaches of patients with asthma - chronic obstructive pulmonary disease overlap syndrome. Orv. Hetil., 2016, 157(33), 1304-1313.

  2. Cramer-Rao Lower Bound Evaluation for Linear Frequency Modulation Based Active Radar Networks Operating in a Rice Fading Environment

    Chenguang Shi

    2016-12-01

    Full Text Available This paper investigates the joint target parameter (delay and Doppler estimation performance of linear frequency modulation (LFM-based radar networks in a Rice fading environment. The active radar networks are composed of multiple radar transmitters and multichannel receivers placed on moving platforms. First, the log-likelihood function of the received signal for a Rician target is derived, where the received signal scattered off the target comprises of dominant scatterer (DS component and weak isotropic scatterers (WIS components. Then, the analytically closed-form expressions of the Cramer-Rao lower bounds (CRLBs on the Cartesian coordinates of target position and velocity are calculated, which can be adopted as a performance metric to access the target parameter estimation accuracy for LFM-based radar network systems in a Rice fading environment. It is found that the cumulative Fisher information matrix (FIM is a linear combination of both DS component and WIS components, and it also demonstrates that the joint CRLB is a function of signal-to-noise ratio (SNR, target’s radar cross section (RCS and transmitted waveform parameters, as well as the relative geometry between the target and the radar network architectures. Finally, numerical results are provided to indicate that the joint target parameter estimation performance of active radar networks can be significantly improved with the exploitation of DS component.

  3. Cramer-Rao Lower Bound Evaluation for Linear Frequency Modulation Based Active Radar Networks Operating in a Rice Fading Environment.

    Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

    2016-12-06

    This paper investigates the joint target parameter (delay and Doppler) estimation performance of linear frequency modulation (LFM)-based radar networks in a Rice fading environment. The active radar networks are composed of multiple radar transmitters and multichannel receivers placed on moving platforms. First, the log-likelihood function of the received signal for a Rician target is derived, where the received signal scattered off the target comprises of dominant scatterer (DS) component and weak isotropic scatterers (WIS) components. Then, the analytically closed-form expressions of the Cramer-Rao lower bounds (CRLBs) on the Cartesian coordinates of target position and velocity are calculated, which can be adopted as a performance metric to access the target parameter estimation accuracy for LFM-based radar network systems in a Rice fading environment. It is found that the cumulative Fisher information matrix (FIM) is a linear combination of both DS component and WIS components, and it also demonstrates that the joint CRLB is a function of signal-to-noise ratio (SNR), target's radar cross section (RCS) and transmitted waveform parameters, as well as the relative geometry between the target and the radar network architectures. Finally, numerical results are provided to indicate that the joint target parameter estimation performance of active radar networks can be significantly improved with the exploitation of DS component.

  4. Modulation of Network Oscillatory Activity and GABAergic Synaptic Transmission by CB1 Cannabinoid Receptors in the Rat Medial Entorhinal Cortex

    Nicola H. Morgan

    2008-01-01

    Full Text Available Cannabinoids modulate inhibitory GABAergic neurotransmission in many brain regions. Within the temporal lobe, cannabinoid receptors are highly expressed, and are located presynaptically at inhibitory terminals. Here, we have explored the role of type-1 cannabinoid receptors (CB1Rs at the level of inhibitory synaptic currents and field-recorded network oscillations. We report that arachidonylcyclopropylamide (ACPA; 10 M, an agonist at CB1R, inhibits GABAergic synaptic transmission onto both superficial and deep medial entorhinal (mEC neurones, but this has little effect on network oscillations in beta/gamma frequency bands. By contrast, the CB1R antagonist/inverse agonist LY320135 (500 nM, increased GABAergic synaptic activity and beta/gamma oscillatory activity in superficial mEC, was suppressed, whilst that in deep mEC was enhanced. These data indicate that cannabinoid-mediated effects on inhibitory synaptic activity may be constitutively active in vitro, and that modulation of CB1R activation using inverse agonists unmasks complex effects of CBR function on network activity.

  5. Modeling of chromosome intermingling by partially overlapping uniform random polygons.

    Blackstone, T; Scharein, R; Borgo, B; Varela, R; Diao, Y; Arsuaga, J

    2011-03-01

    During the early phase of the cell cycle the eukaryotic genome is organized into chromosome territories. The geometry of the interface between any two chromosomes remains a matter of debate and may have important functional consequences. The Interchromosomal Network model (introduced by Branco and Pombo) proposes that territories intermingle along their periphery. In order to partially quantify this concept we here investigate the probability that two chromosomes form an unsplittable link. We use the uniform random polygon as a crude model for chromosome territories and we model the interchromosomal network as the common spatial region of two overlapping uniform random polygons. This simple model allows us to derive some rigorous mathematical results as well as to perform computer simulations easily. We find that the probability that one uniform random polygon of length n that partially overlaps a fixed polygon is bounded below by 1 − O(1/√n). We use numerical simulations to estimate the dependence of the linking probability of two uniform random polygons (of lengths n and m, respectively) on the amount of overlapping. The degree of overlapping is parametrized by a parameter [Formula: see text] such that [Formula: see text] indicates no overlapping and [Formula: see text] indicates total overlapping. We propose that this dependence relation may be modeled as f (ε, m, n) = [Formula: see text]. Numerical evidence shows that this model works well when [Formula: see text] is relatively large (ε ≥ 0.5). We then use these results to model the data published by Branco and Pombo and observe that for the amount of overlapping observed experimentally the URPs have a non-zero probability of forming an unsplittable link.

  6. Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

    Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

    2013-03-28

    Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. Network analysis of S. aureus response to ramoplanin reveals modules for virulence factors and resistance mechanisms and characteristic novel genes.

    Subramanian, Devika; Natarajan, Jeyakumar

    2015-12-10

    Staphylococcus aureus is a major human pathogen and ramoplanin is an antimicrobial attributed for effective treatment. The goal of this study was to examine the transcriptomic profiles of ramoplanin sensitive and resistant S. aureus to identify putative modules responsible for virulence and resistance-mechanisms and its characteristic novel genes. The dysregulated genes were used to reconstruct protein functional association networks for virulence-factors and resistance-mechanisms individually. Strong link between metabolic-pathways and development of virulence/resistance is suggested. We identified 15 putative modules of virulence factors. Six hypothetical genes were annotated with novel virulence activity among which SACOL0281 was discovered to be an essential virulence factor EsaD. The roles of MazEF toxin-antitoxin system, SACOL0202/SACOL0201 two-component system and that of amino-sugar and nucleotide-sugar metabolism in virulence are also suggested. In addition, 14 putative modules of resistance mechanisms including modules of ribosomal protein-coding genes and metabolic pathways such as biotin-synthesis, TCA-cycle, riboflavin-biosynthesis, peptidoglycan-biosynthesis etc. are also indicated. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Long-term meditation training induced changes in the operational synchrony of default mode network modules during a resting state.

    Fingelkurts, Andrew A; Fingelkurts, Alexander A; Kallio-Tamminen, Tarja

    2016-02-01

    Using theoretical analysis of self-consciousness concept and experimental evidence on the brain default mode network (DMN) that constitutes the neural signature of self-referential processes, we hypothesized that the anterior and posterior subnets comprising the DMN should show differences in their integrity as a function of meditation training. Functional connectivity within DMN and its subnets (measured by operational synchrony) has been measured in ten novice meditators using an electroencephalogram (EEG) recording in a pre-/post-meditation intervention design. We have found that while the whole DMN was clearly suppressed, different subnets of DMN responded differently after 4 months of meditation training: The strength of EEG operational synchrony in the right and left posterior modules of the DMN decreased in resting post-meditation condition compared to a pre-meditation condition, whereas the frontal DMN module on the contrary exhibited an increase in the strength of EEG operational synchrony. These findings combined with published data on functional-anatomic heterogeneity within the DMN and on trait subjective experiences commonly found following meditation allow us to propose that the first-person perspective and the sense of agency (the witnessing observer) are presented by the frontal DMN module, while the posterior modules of the DMN are generally responsible for the experience of the continuity of 'I' as embodied and localized within bodily space. Significance of these findings is discussed.

  9. Interference management with partial uplink/downlink spectrum overlap

    Randrianantenaina, Itsikiantsoa

    2016-07-26

    Simultaneous reuse of spectral resources by uplink and downlink, denoted as in-band full duplex (FD) communication, is promoted to double the spectral efficiency when compared to its half-duplex (HD) counterpart. Interference management, however, remains challenging in FD cellular networks, especially when high disparity between uplink and downlink transmission powers exists. The uplink performance can be particularly deteriorated when operating on channels that are simultaneously occupied with downlink transmission. This paper considers a cellular wireless system with partial spectrum overlap between the downlink and uplink. The performance of the system becomes, therefore, a function of the overlap fraction, as well as the power levels of both the uplink and downlink transmissions. The paper considers the problem of maximizing an overall network utility to find the uplink/downlink transmission powers and the spectrum overlap fraction between the uplink and downlink spectrum in each cell, and proposes solving the problem using interior point method. Simulations results confirm the vulnerability of the uplink performance to the FD operation, and show the superiority of the proposed scheme over the FD and HD schemes. The results further show that explicit uplink and downlink performance should be considered for efficient design of cellular networks with overlapping uplink/downlink resources. © 2016 IEEE.

  10. Functional characterization of GABAA receptor-mediated modulation of cortical neuron network activity in microelectrode array recordings

    Bader, Benjamin M; Steder, Anne; Klein, Anders Bue

    2017-01-01

    The numerous γ-aminobutyric acid type A receptor (GABAAR) subtypes are differentially expressed and mediate distinct functions at neuronal level. In this study we have investigated GABAAR-mediated modulation of the spontaneous activity patterns of primary neuronal networks from murine frontal...... of the information extractable from the MEA recordings offers interesting insights into the contributions of various GABAAR subtypes/subgroups to cortical network activity and the putative functional interplay between these receptors in these neurons....... cortex by characterizing the effects induced by a wide selection of pharmacological tools at a plethora of activity parameters in microelectrode array (MEA) recordings. The basic characteristics of the primary cortical neurons used in the recordings were studied in some detail, and the expression levels...

  11. Plastic modulation of episodic memory networks in the aging brain with cognitive decline.

    Bai, Feng; Yuan, Yonggui; Yu, Hui; Zhang, Zhijun

    2016-07-15

    Social-cognitive processing has been posited to underlie general functions such as episodic memory. Episodic memory impairment is a recognized hallmark of amnestic mild cognitive impairment (aMCI) who is at a high risk for dementia. Three canonical networks, self-referential processing, executive control processing and salience processing, have distinct roles in episodic memory retrieval processing. It remains unclear whether and how these sub-networks of the episodic memory retrieval system would be affected in aMCI. This task-state fMRI study constructed systems-level episodic memory retrieval sub-networks in 28 aMCI and 23 controls using two computational approaches: a multiple region-of-interest based approach and a voxel-level functional connectivity-based approach, respectively. These approaches produced the remarkably similar findings that the self-referential processing network made critical contributions to episodic memory retrieval in aMCI. More conspicuous alterations in self-referential processing of the episodic memory retrieval network were identified in aMCI. In order to complete a given episodic memory retrieval task, increases in cooperation between the self-referential processing network and other sub-networks were mobilized in aMCI. Self-referential processing mediate the cooperation of the episodic memory retrieval sub-networks as it may help to achieve neural plasticity and may contribute to the prevention and treatment of dementia. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback.

    Ramot, Michal; Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

    2017-09-16

    The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants' awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.

  13. Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

    Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

    2017-01-01

    The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns. PMID:28917059

  14. Coordinations between gene modules control the operation of plant amino acid metabolic networks

    Galili Gad

    2009-01-01

    Full Text Available Abstract Background Being sessile organisms, plants should adjust their metabolism to dynamic changes in their environment. Such adjustments need particular coordination in branched metabolic networks in which a given metabolite can be converted into multiple other metabolites via different enzymatic chains. In the present report, we developed a novel "Gene Coordination" bioinformatics approach and use it to elucidate adjustable transcriptional interactions of two branched amino acid metabolic networks in plants in response to environmental stresses, using publicly available microarray results. Results Using our "Gene Coordination" approach, we have identified in Arabidopsis plants two oppositely regulated groups of "highly coordinated" genes within the branched Asp-family network of Arabidopsis plants, which metabolizes the amino acids Lys, Met, Thr, Ile and Gly, as well as a single group of "highly coordinated" genes within the branched aromatic amino acid metabolic network, which metabolizes the amino acids Trp, Phe and Tyr. These genes possess highly coordinated adjustable negative and positive expression responses to various stress cues, which apparently regulate adjustable metabolic shifts between competing branches of these networks. We also provide evidence implying that these highly coordinated genes are central to impose intra- and inter-network interactions between the Asp-family and aromatic amino acid metabolic networks as well as differential system interactions with other growth promoting and stress-associated genome-wide genes. Conclusion Our novel Gene Coordination elucidates that branched amino acid metabolic networks in plants are regulated by specific groups of highly coordinated genes that possess adjustable intra-network, inter-network and genome-wide transcriptional interactions. We also hypothesize that such transcriptional interactions enable regulatory metabolic adjustments needed for adaptation to the stresses.

  15. Overlapping sphincteroplasty and posterior repair.

    Crane, Andrea K; Myers, Erinn M; Lippmann, Quinn K; Matthews, Catherine A

    2014-12-01

    Knowledge of how to anatomically reconstruct extensive posterior-compartment defects is variable among gynecologists. The objective of this video is to demonstrate an effective technique of overlapping sphincteroplasty and posterior repair. In this video, a scripted storyboard was constructed that outlines the key surgical steps of a comprehensive posterior compartment repair: (1) surgical incision that permits access to posterior compartment and perineal body, (2) dissection of the rectovaginal space up to the level of the cervix, (3) plication of the rectovaginal muscularis, (4) repair of internal and external anal sphincters, and (5) reconstruction of the perineal body. Using a combination of graphic illustrations and live video footage, tips on repair are highlighted. The goals at the end of repair are to: (1) have improved vaginal caliber, (2) increase rectal tone along the entire posterior vaginal wall, (3) have the posterior vaginal wall at a perpendicular plane to the perineal body, (4) reform the hymenal ring, and (5) not have an overly elongated perineal body. This video provides a step-by-step guide on how to perform an overlapping sphincteroplasty and posterior repair.

  16. Bandwidth efficient bidirectional 5 Gb/s overlapped-SCM WDM PON with electronic equalization and forward-error correction.

    Buset, Jonathan M; El-Sahn, Ziad A; Plant, David V

    2012-06-18

    We demonstrate an improved overlapped-subcarrier multiplexed (O-SCM) WDM PON architecture transmitting over a single feeder using cost sensitive intensity modulation/direct detection transceivers, data re-modulation and simple electronics. Incorporating electronic equalization and Reed-Solomon forward-error correction codes helps to overcome the bandwidth limitation of a remotely seeded reflective semiconductor optical amplifier (RSOA)-based ONU transmitter. The O-SCM architecture yields greater spectral efficiency and higher bit rates than many other SCM techniques while maintaining resilience to upstream impairments. We demonstrate full-duplex 5 Gb/s transmission over 20 km and analyze BER performance as a function of transmitted and received power. The architecture provides flexibility to network operators by relaxing common design constraints and enabling full-duplex operation at BER ∼ 10(-10) over a wide range of OLT launch powers from 3.5 to 8 dBm.

  17. Brain Networks are Independently Modulated by Donepezil, Sleep, and Sleep Deprivation.

    Wirsich, Jonathan; Rey, Marc; Guye, Maxime; Bénar, Christian; Lanteaume, Laura; Ridley, Ben; Confort-Gouny, Sylviane; Cassé-Perrot, Catherine; Soulier, Elisabeth; Viout, Patrick; Rouby, Franck; Lefebvre, Marie-Noëlle; Audebert, Christine; Truillet, Romain; Jouve, Elisabeth; Payoux, Pierre; Bartrés-Faz, David; Bordet, Régis; Richardson, Jill C; Babiloni, Claudio; Rossini, Paolo Maria; Micallef, Joelle; Blin, Olivier; Ranjeva, Jean-Philippe

    2018-05-01

    Resting-state connectivity has been widely studied in the healthy and pathological brain. Less well-characterized are the brain networks altered during pharmacological interventions and their possible interaction with vigilance. In the hopes of finding new biomarkers which can be used to identify cortical activity and cognitive processes linked to the effects of drugs to treat neurodegenerative diseases such as Alzheimer's disease, the analysis of networks altered by medication would be particularly interesting. Eleven healthy subjects were recruited in the context of the European Innovative Medicines Initiative 'PharmaCog'. Each underwent five sessions of simultaneous EEG-fMRI in order to investigate the effects of donepezil and memantine before and after sleep deprivation (SD). The SD approach has been previously proposed as a model for cognitive impairment in healthy subjects. By applying network based statistics (NBS), we observed altered brain networks significantly linked to donepezil intake and sleep deprivation. Taking into account the sleep stages extracted from the EEG data we revealed that a network linked to sleep is interacting with sleep deprivation but not with medication intake. We successfully extracted the functional resting-state networks modified by donepezil intake, sleep and SD. We observed donepezil induced whole brain connectivity alterations forming a network separated from the changes induced by sleep and SD, a result which shows the utility of this approach to check for the validity of pharmacological resting-state analysis of the tested medications without the need of taking into account the subject specific vigilance.

  18. Improving functional modules discovery by enriching interaction networks with gene profiles

    Salem, Saeed; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Aljarah, Ibrahim; Brewer, James

    2013-01-01

    networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional

  19. ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

    Kuwahara, Hiroyuki; Umarov, Ramzan; Almasri, Islam; Gao, Xin

    2017-01-01

    To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

  20. Beyond network structure: How heterogeneous susceptibility modulates the spread of epidemics.

    Smilkov, Daniel; Hidalgo, Cesar A; Kocarev, Ljupco

    2014-04-25

    The compartmental models used to study epidemic spreading often assume the same susceptibility for all individuals, and are therefore, agnostic about the effects that differences in susceptibility can have on epidemic spreading. Here we show that-for the SIS model-differential susceptibility can make networks more vulnerable to the spread of diseases when the correlation between a node's degree and susceptibility are positive, and less vulnerable when this correlation is negative. Moreover, we show that networks become more likely to contain a pocket of infection when individuals are more likely to connect with others that have similar susceptibility (the network is segregated). These results show that the failure to include differential susceptibility to epidemic models can lead to a systematic over/under estimation of fundamental epidemic parameters when the structure of the networks is not independent from the susceptibility of the nodes or when there are correlations between the susceptibility of connected individuals.

  1. ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

    Kuwahara, Hiroyuki

    2017-03-01

    To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

  2. Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

    Silvia Tommasin

    2017-07-01

    Full Text Available Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN, are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task.

  3. Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

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

    2017-01-01

    Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task. PMID:28845420

  4. Task-related modulations of BOLD low-frequency fluctuations within the default mode network

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

    2017-07-01

    Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33±6 years, 8F/12M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the steady-state execution of a sustained working memory n-back task. We found that the steady state execution of such a task impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to steady-state task execution, can contribute to a better understanding of how brain networks rearrange themselves in response of a task.

  5. Overlapping community detection based on link graph using distance dynamics

    Chen, Lei; Zhang, Jing; Cai, Li-Jun

    2018-01-01

    The distance dynamics model was recently proposed to detect the disjoint community of a complex network. To identify the overlapping structure of a network using the distance dynamics model, an overlapping community detection algorithm, called L-Attractor, is proposed in this paper. The process of L-Attractor mainly consists of three phases. In the first phase, L-Attractor transforms the original graph to a link graph (a new edge graph) to assure that one node has multiple distances. In the second phase, using the improved distance dynamics model, a dynamic interaction process is introduced to simulate the distance dynamics (shrink or stretch). Through the dynamic interaction process, all distances converge, and the disjoint community structure of the link graph naturally manifests itself. In the third phase, a recovery method is designed to convert the disjoint community structure of the link graph to the overlapping community structure of the original graph. Extensive experiments are conducted on the LFR benchmark networks as well as real-world networks. Based on the results, our algorithm demonstrates higher accuracy and quality than other state-of-the-art algorithms.

  6. Optogenetic Modulation and Multi-Electrode Analysis of Cerebellar Networks In Vivo

    Kruse, Wolfgang; Krause, Martin; Aarse, Janna; Mark, Melanie D.; Manahan-Vaughan, Denise; Herlitze, Stefan

    2014-01-01

    The firing patterns of cerebellar Purkinje cells (PCs), as the sole output of the cerebellar cortex, determine and tune motor behavior. PC firing is modulated by various inputs from different brain regions and by cell-types including granule cells (GCs), climbing fibers and inhibitory interneurons. To understand how signal integration in PCs occurs and how subtle changes in the modulation of PC firing lead to adjustment of motor behaviors, it is important to precisely record PC firing in vivo and to control modulatory pathways in a spatio-temporal manner. Combining optogenetic and multi-electrode approaches, we established a new method to integrate light-guides into a multi-electrode system. With this method we are able to variably position the light-guide in defined regions relative to the recording electrode with micrometer precision. We show that PC firing can be precisely monitored and modulated by light-activation of channelrhodopsin-2 (ChR2) expressed in PCs, GCs and interneurons. Thus, this method is ideally suited to investigate the spatio/temporal modulation of PCs in anesthetized and in behaving mice. PMID:25144735

  7. Optogenetic modulation and multi-electrode analysis of cerebellar networks in vivo.

    Wolfgang Kruse

    Full Text Available The firing patterns of cerebellar Purkinje cells (PCs, as the sole output of the cerebellar cortex, determine and tune motor behavior. PC firing is modulated by various inputs from different brain regions and by cell-types including granule cells (GCs, climbing fibers and inhibitory interneurons. To understand how signal integration in PCs occurs and how subtle changes in the modulation of PC firing lead to adjustment of motor behaviors, it is important to precisely record PC firing in vivo and to control modulatory pathways in a spatio-temporal manner. Combining optogenetic and multi-electrode approaches, we established a new method to integrate light-guides into a multi-electrode system. With this method we are able to variably position the light-guide in defined regions relative to the recording electrode with micrometer precision. We show that PC firing can be precisely monitored and modulated by light-activation of channelrhodopsin-2 (ChR2 expressed in PCs, GCs and interneurons. Thus, this method is ideally suited to investigate the spatio/temporal modulation of PCs in anesthetized and in behaving mice.

  8. Trans-spinal direct current stimulation for the modulation of the lumbar spinal motor networks

    Kuck, Alexander

    2018-01-01

    Trans-spinal Direct Current Stimulation (tsDCS) is a noninvasive neuromodulatory tool for the modulation of the spinal neurocircuitry. Initial studies have shown that tsDCS is able to induce a significant and lasting change in spinal-reflex- and corticospinal information processing. It is therefore

  9. Hyper-modulation of brain networks by the amygdala among women with Borderline Personality Disorder: Network signatures of affective interference during cognitive processing.

    Soloff, Paul H; Abraham, Kristy; Ramaseshan, Karthik; Burgess, Ashley; Diwadkar, Vaibhav A

    2017-05-01

    Emotion dysregulation is a core characteristic of patients with Borderline Personality Disorder (BPD), and is often attributed to an imbalance in fronto-limbic network function. Hyperarousal of amygdala, especially in response to negative affective stimuli, results in affective interference with cognitive processing of executive functions. Clinical consequences include the impulsive-aggression, suicidal and self-injurious behaviors which characterize BPD. Dysfunctional interactions between amygdala and its network targets have not been well characterized during cognitive task performance. Using psychophysiological interaction analysis (PPI), we mapped network profiles of amygdala interaction with key regulatory regions during a Go No-Go task, modified to use negative, positive and neutral Ekman faces as targets. Fifty-six female subjects, 31 BPD and 25 healthy controls (HC), completed the affectively valenced Go No-Go task during fMRI scanning. In the negative affective condition, the amygdala exerted greater modulation of its targets in BPD compared to HC subjects in Rt. OFC, Rt. dACC, Rt. Parietal cortex, Rt. Basal Ganglia, and Rt. dlPFC. Across the spectrum of affective contrasts, hypermodulation in BPD subjects observed the following ordering: Negative > Neutral > Positive contrast. The amygdala seed exerted modulatory effects on specific target regions important in processing response inhibition and motor impulsiveness. The vulnerability of BPD subjects to affective interference with impulse control may be due to specific network dysfunction related to amygdala hyper-arousal and its effects on prefrontal regulatory regions such as the OFC and dACC. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Reciprocal cholinergic and GABAergic modulation of the small ventrolateral pacemaker neurons of Drosophila's circadian clock neuron network.

    Lelito, Katherine R; Shafer, Orie T

    2012-04-01

    The relatively simple clock neuron network of Drosophila is a valuable model system for the neuronal basis of circadian timekeeping. Unfortunately, many key neuronal classes of this network are inaccessible to electrophysiological analysis. We have therefore adopted the use of genetically encoded sensors to address the physiology of the fly's circadian clock network. Using genetically encoded Ca(2+) and cAMP sensors, we have investigated the physiological responses of two specific classes of clock neuron, the large and small ventrolateral neurons (l- and s-LN(v)s), to two neurotransmitters implicated in their modulation: acetylcholine (ACh) and γ-aminobutyric acid (GABA). Live imaging of l-LN(v) cAMP and Ca(2+) dynamics in response to cholinergic agonist and GABA application were well aligned with published electrophysiological data, indicating that our sensors were capable of faithfully reporting acute physiological responses to these transmitters within single adult clock neuron soma. We extended these live imaging methods to s-LN(v)s, critical neuronal pacemakers whose physiological properties in the adult brain are largely unknown. Our s-LN(v) experiments revealed the predicted excitatory responses to bath-applied cholinergic agonists and the predicted inhibitory effects of GABA and established that the antagonism of ACh and GABA extends to their effects on cAMP signaling. These data support recently published but physiologically untested models of s-LN(v) modulation and lead to the prediction that cholinergic and GABAergic inputs to s-LN(v)s will have opposing effects on the phase and/or period of the molecular clock within these critical pacemaker neurons.

  11. Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder

    Thomas Hassa

    2017-01-01

    Full Text Available Initial historical accounts as well as recent data suggest that emotion processing is dysfunctional in conversion disorder patients and that this alteration may be the pathomechanistic neurocognitive basis for symptoms in conversion disorder. However, to date evidence of direct interaction of altered negative emotion processing with motor control networks in conversion disorder is still lacking. To specifically study the neural correlates of emotion processing interacting with motor networks we used a task combining emotional and sensorimotor stimuli both separately as well as simultaneously during functional magnetic resonance imaging in a well characterized group of 13 conversion disorder patients with functional hemiparesis and 19 demographically matched healthy controls. We performed voxelwise statistical parametrical mapping for a priori regions of interest within emotion processing and motor control networks. Psychophysiological interaction (PPI was used to test altered functional connectivity of emotion and motor control networks. Only during simultaneous emotional stimulation and passive movement of the affected hand patients displayed left amygdala hyperactivity. PPI revealed increased functional connectivity in patients between the left amygdala and the (pre-supplemental motor area and the subthalamic nucleus, key regions within the motor control network. These findings suggest a novel mechanistic direct link between dysregulated emotion processing and motor control circuitry in conversion disorder.

  12. Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder.

    Hassa, Thomas; Sebastian, Alexandra; Liepert, Joachim; Weiller, Cornelius; Schmidt, Roger; Tüscher, Oliver

    2017-01-01

    Initial historical accounts as well as recent data suggest that emotion processing is dysfunctional in conversion disorder patients and that this alteration may be the pathomechanistic neurocognitive basis for symptoms in conversion disorder. However, to date evidence of direct interaction of altered negative emotion processing with motor control networks in conversion disorder is still lacking. To specifically study the neural correlates of emotion processing interacting with motor networks we used a task combining emotional and sensorimotor stimuli both separately as well as simultaneously during functional magnetic resonance imaging in a well characterized group of 13 conversion disorder patients with functional hemiparesis and 19 demographically matched healthy controls. We performed voxelwise statistical parametrical mapping for a priori regions of interest within emotion processing and motor control networks. Psychophysiological interaction (PPI) was used to test altered functional connectivity of emotion and motor control networks. Only during simultaneous emotional stimulation and passive movement of the affected hand patients displayed left amygdala hyperactivity. PPI revealed increased functional connectivity in patients between the left amygdala and the (pre-)supplemental motor area and the subthalamic nucleus, key regions within the motor control network. These findings suggest a novel mechanistic direct link between dysregulated emotion processing and motor control circuitry in conversion disorder.

  13. Overlapping structures in sensory-motor mappings.

    Kevin Earland

    Full Text Available This paper examines a biologically-inspired representation technique designed for the support of sensory-motor learning in developmental robotics. An interesting feature of the many topographic neural sheets in the brain is that closely packed receptive fields must overlap in order to fully cover a spatial region. This raises interesting scientific questions with engineering implications: e.g. is overlap detrimental? does it have any benefits? This paper examines the effects and properties of overlap between elements arranged in arrays or maps. In particular we investigate how overlap affects the representation and transmission of spatial location information on and between topographic maps. Through a series of experiments we determine the conditions under which overlap offers advantages and identify useful ranges of overlap for building mappings in cognitive robotic systems. Our motivation is to understand the phenomena of overlap in order to provide guidance for application in sensory-motor learning robots.

  14. Epigenetic Modulation of Brain Gene Networks for Cocaine and Alcohol Abuse

    Sean P Farris

    2015-05-01

    Full Text Available Cocaine and alcohol are two substances of abuse that prominently affect the central nervous system (CNS. Repeated exposure to cocaine and alcohol leads to longstanding changes in gene expression, and subsequent functional CNS plasticity, throughout multiple brain regions. Epigenetic modifications of histones are one proposed mechanism guiding these enduring changes to the transcriptome. Characterizing the large number of available biological relationships as network models can reveal unexpected biochemical relationships. Clustering analysis of variation from whole-genome sequencing of gene expression (RNA-Seq and histone H3 lysine 4 trimethylation (H3K4me3 events (ChIP-Seq revealed the underlying structure of the transcriptional and epigenomic landscape within hippocampal postmortem brain tissue of drug abusers and control cases. Distinct sets of interrelated networks for cocaine and alcohol abuse were determined for each abusive substance. The network approach identified subsets of functionally related genes that are regulated in agreement with H3K4me3 changes, suggesting cause and effect relationships between this epigenetic mark and gene expression. Gene expression networks consisted of recognized substrates for addiction, such as the dopamine- and cAMP-regulated neuronal phosphoprotein PPP1R1B / DARPP-32 and the vesicular glutamate transporter SLC17A7 / VGLUT1 as well as potentially novel molecular targets for substance abuse. Through a systems biology based approach our results illustrate the utility of integrating epigenetic and transcript expression to establish relevant biological networks in the human brain for addiction. Future work with laboratory models may clarify the functional relevance of these gene networks for cocaine and alcohol, and provide a framework for the development of medications for the treatment of addiction.

  15. Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks

    Chiwoo Lim

    2018-04-01

    Full Text Available In this paper, a new non-orthogonal multiple-access scheme, trellis tone modulation multiple-access (TTMMA, is proposed for peer discovery of distributed device-to-device (D2D communication. The range and capacity of discovery are important performance metrics in peer discovery. The proposed trellis tone modulation uses single-tone transmission and achieves a long discovery range due to its low Peak-to-Average Power Ratio (PAPR. The TTMMA also exploits non-orthogonal resource assignment to increase the discovery capacity. For the multi-user detection of superposed multiple-access signals, a message-passing algorithm with supplementary schemes are proposed. With TTMMA and its message-passing demodulation, approximately 1.5 times the number of devices are discovered compared to the conventional frequency division multiple-access (FDMA-based discovery.

  16. On the application of neural networks to the classification of phase modulated waveforms

    Buchenroth, Anthony; Yim, Joong Gon; Nowak, Michael; Chakravarthy, Vasu

    2017-04-01

    Accurate classification of phase modulated radar waveforms is a well-known problem in spectrum sensing. Identification of such waveforms aids situational awareness enabling radar and communications spectrum sharing. While various feature extraction and engineering approaches have sought to address this problem, the use of a machine learning algorithm that best utilizes these features is becomes foremost. In this effort, a comparison of a standard shallow and a deep learning approach are explored. Experiments provide insights into classifier architecture, training procedure, and performance.

  17. Overlapping riboflavin supply pathways in bacteria.

    García-Angulo, Víctor Antonio

    2017-03-01

    Riboflavin derivatives are essential cofactors for a myriad of flavoproteins. In bacteria, flavins importance extends beyond their role as intracellular protein cofactors, as secreted flavins are a key metabolite in a variety of physiological processes. Bacteria obtain riboflavin through the endogenous riboflavin biosynthetic pathway (RBP) or by the use of importer proteins. Bacteria frequently encode multiple paralogs of the RBP enzymes and as for other micronutrient supply pathways, biosynthesis and uptake functions largely coexist. It is proposed that bacteria shut down biosynthesis and would rather uptake riboflavin when the vitamin is environmentally available. Recently, the overlap of riboflavin provisioning elements has gained attention and the functions of duplicated paralogs of RBP enzymes started to be addressed. Results point towards the existence of a modular structure in the bacterial riboflavin supply pathways. Such structure uses subsets of RBP genes to supply riboflavin for specific functions. Given the importance of riboflavin in intra and extracellular bacterial physiology, this complex array of riboflavin provision pathways may have developed to contend with the various riboflavin requirements. In riboflavin-prototrophic bacteria, riboflavin transporters could represent a module for riboflavin provision for particular, yet unidentified processes, rather than substituting for the RBP as usually assumed.

  18. Modules in the metabolic network of E.coli with regulatory interactions

    Geryk, J.; Slanina, František

    2013-01-01

    Roč. 8, č. 2 (2013), s. 188-202 ISSN 1748-5673 R&D Projects: GA MŠk OC09078 Institutional support: RVO:68378271 Keywords : networks * modularity * biophysics Subject RIV: BO - Biophysics Impact factor: 0.655, year: 2013 http://www.inderscience.com/info/inarticle.php?artid=55500

  19. TDM interrogation of intensity-modulated USFBGs network based on multichannel lasers.

    Rohollahnejad, Jalal; Xia, Li; Cheng, Rui; Ran, Yanli; Rahubadde, Udaya; Zhou, Jiaao; Zhu, Lin

    2017-01-23

    We report a large-scale multi-channel fiber sensing network, where ultra-short FBGs (USFBGs) instead of conventional narrow-band ultra-weak FBGs are used as the sensors. In the time division multiplexing scheme of the network, each grating response is resolved as three adjacent discrete peaks. The central wavelengths of USFBGs are tracked with the differential detection, which is achieved by calculating the peak-to-peak ratio of two maximum peaks. Compared with previous large-scale hybrid multiplexing sensing networks (e.g., WDM/TDM) which typically have relatively low interrogation speed and very high complexity, the proposed system can achieve interrogation of all channel sensors through very fast and simple intensity measurements with a broad dynamic range. A proof-of-concept experiment with twenty USFBGs, at two wavelength channels, was performed and a fast static strain measurements were demonstrated, with a high average sensitivity of ~0.54dB/µƐ and wide dynamic range of over ~3000µƐ. The channel to channel switching time was 10ms and total network interrogation time was 50ms.

  20. Modules, networks and systems medicine for understanding disease and aiding diagnosis

    Gustafsson, Mika; Nestor, Colm E.; Zhang, Huan

    2014-01-01

    Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics dat...

  1. Modules, networks and systems medicine for understanding disease and aiding diagnosis

    Gustafsson, Mika; Nestor, Colm E.; Zhang, Huan; Barabási, Albert-László; Baranzini, Sergio; Brunak, Sören; Chung, Kian Fan; Federoff, Howard J.; Gavin, Anne-Claude; Meehan, Richard R.; Picotti, Paola; Pujana, Miguel Àngel; Rajewsky, Nikolaus; Smith, Kenneth Gc; Sterk, Peter J.; Villoslada, Pablo; Benson, Mikael

    2014-01-01

    Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data

  2. Obesity and addiction: neurobiological overlaps.

    Volkow, N D; Wang, G-J; Tomasi, D; Baler, R D

    2013-01-01

    Drug addiction and obesity appear to share several properties. Both can be defined as disorders in which the saliency of a specific type of reward (food or drug) becomes exaggerated relative to, and at the expense of others rewards. Both drugs and food have powerful reinforcing effects, which are in part mediated by abrupt dopamine increases in the brain reward centres. The abrupt dopamine increases, in vulnerable individuals, can override the brain's homeostatic control mechanisms. These parallels have generated interest in understanding the shared vulnerabilities between addiction and obesity. Predictably, they also engendered a heated debate. Specifically, brain imaging studies are beginning to uncover common features between these two conditions and delineate some of the overlapping brain circuits whose dysfunctions may underlie the observed deficits. The combined results suggest that both obese and drug-addicted individuals suffer from impairments in dopaminergic pathways that regulate neuronal systems associated not only with reward sensitivity and incentive motivation, but also with conditioning, self-control, stress reactivity and interoceptive awareness. In parallel, studies are also delineating differences between them that centre on the key role that peripheral signals involved with homeostatic control exert on food intake. Here, we focus on the shared neurobiological substrates of obesity and addiction. © 2012 The Authors. obesity reviews © 2012 International Association for the Study of Obesity.

  3. Uplink capacity of multi-class IEEE 802.16j relay networks with adaptive modulation and coding

    Wang, Hua; Xiong, C; Iversen, Villy Bæk

    2009-01-01

    The emerging IEEE 802.16j mobile multi-hop relay (MMR) network is currently being developed to increase the user throughput and extend the service coverage as an enhancement of existing 802.16e standard. In 802.16j, the intermediate relay stations (RSs) help the base station (BS) communicate...... with those mobile stations (MSs) that are either too far away from the BS or placed in an area where direct communication with BS experiences unsatisfactory level of service. In this paper, we investigate the uplink Erlang capacity of a two-hop 802.16j relay system supporting both voice and data traffics...... with adaptive modulation and coding (AMC) scheme applied in the physical layer. We first develop analytical models to calculate the blocking probability in the access zone and the outage probability in the relay zone, respectively. Then a joint algorithm is proposed to determine the bandwidth distribution...

  4. Performance analysis of two-way amplify and forward relaying with adaptive modulation over multiple relay network

    Hwang, Kyusung

    2011-02-01

    In this letter, we propose two-way amplify-and-forward relaying in conjunction with adaptive modulation in order to improve spectral efficiency of relayed communication systems while monitoring the required error performance. We also consider a multiple relay network where only the best relay node is utilized so that the diversity order increases while maintaining a low complexity of implementation as the number of relays increases. Based on the best relay selection criterion, we offer an upper bound on the signal-to-noise ratio to keep the performance analysis tractable. Our numerical examples show that the proposed system offers a considerable gain in spectral efficiency while satisfying the error rate requirements. © 2011 IEEE.

  5. Performance analysis of two-way amplify and forward relaying with adaptive modulation over multiple relay network

    Hwang, Kyusung; Ko, Youngchai; Alouini, Mohamed-Slim

    2011-01-01

    In this letter, we propose two-way amplify-and-forward relaying in conjunction with adaptive modulation in order to improve spectral efficiency of relayed communication systems while monitoring the required error performance. We also consider a multiple relay network where only the best relay node is utilized so that the diversity order increases while maintaining a low complexity of implementation as the number of relays increases. Based on the best relay selection criterion, we offer an upper bound on the signal-to-noise ratio to keep the performance analysis tractable. Our numerical examples show that the proposed system offers a considerable gain in spectral efficiency while satisfying the error rate requirements. © 2011 IEEE.

  6. Globes from global data: Charting international research networks with the GRASS GIS r.out.polycones add-on module.

    Löwe, Peter

    2015-04-01

    Many Free and Open Source Software (FOSS) tools have been created for the various application fields within geoscience. While FOSS allows re-implementation of functionalities in new environments by access to the original codebase, the easiest approach to build new software solutions for new problems is the combination or merging of existing software tools. Such mash-ups are implemented by embedding and encapsulating FOSS tools within each another, effectively focusing the use of the embedded software to the specific role it needs to perform in the given scenario, while ignoring all its other capabilities. GRASS GIS is a powerful and established FOSS GIS for raster, vector and volume data processing while the Generic Mapping Tools (GMT) are a suite of powerful Open Source mapping tools, which exceed the mapping capabilities of GRASS GIS. This poster reports on the new GRASS GIS add-on module r.out.polycones. It enables users to utilize non-continuous projections for map production within the GRASS production environment. This is implemented on the software level by encapsulating a subset of GMT mapping capabilities into a GRASS GIS (Version 6.x) add-on module. The module was developed at the German National Library of Science and Technology (TIB) to provide custom global maps of scientific collaboration networks, such as the DataCite consortium, the registration agency for Digital Object Identifiers (DOI) for research data. The GRASS GIS add-on module can be used for global mapping of raster data into a variety of non continuous sinosoidal projections, allowing the creation of printable biangles (gores) to be used for globe making. Due to the well structured modular nature of GRASS modules, technical follow-up work will focus on API-level Python-based integration in GRASS 7 [1]. Based on this, GMT based mapping capabilities in GRASS will be extended beyond non-continuous sinosoidal maps and advanced from raster-layers to content GRASS display monitors. References

  7. Review of overlap between thermoregulation and pain modulation in fibromyalgia

    Larson, Alice A.; Pardo, José V.; Pasley, Jeffrey D.

    2013-01-01

    Fibromyalgia syndrome is characterized by widespread pain that is exacerbated by cold and stress but relieved by warmth. We review the points along thermal and pain pathways where temperature may influence pain. We also present evidence addressing the possibility that brown adipose tissue activity is linked to the pain of fibromyalgia given that cold initiates thermogenesis in brown adipose tissue via adrenergic activity, while warmth suspends thermogenesis. Although females have a higher incidence of fibromyalgia as well as more resting thermogenesis, they are less able to recruit brown adipose tissue in response to chronic stress than males. In addition, conditions that are frequently comorbid with fibromyalgia compromise brown adipose activity making it less responsive to sympathetic stimulation. This results in lower body temperatures, lower metabolic rates, and lower circulating cortisol/corticosterone in response to stress - characteristics of fibromyalgia. In the periphery, sympathetic nerves to brown adipose also project to surrounding tissues, including tender points characterizing fibromyalgia. As a result, the musculoskeletal hyperalgesia associated with conditions like fibromyalgia may result from referred pain in the adjacent muscle and skin. PMID:23887348

  8. Convergent optical wired and wireless long-reach access network using high spectral-efficient modulation.

    Chow, C W; Lin, Y H

    2012-04-09

    To provide broadband services in a single and low cost perform, the convergent optical wired and wireless access network is promising. Here, we propose and demonstrate a convergent optical wired and wireless long-reach access networks based on orthogonal wavelength division multiplexing (WDM). Both the baseband signal and the radio-over-fiber (ROF) signal are multiplexed and de-multiplexed in optical domain, hence it is simple and the operation speed is not limited by the electronic bottleneck caused by the digital signal processing (DSP). Error-free de-multiplexing and down-conversion can be achieved for all the signals after 60 km (long-reach) fiber transmission. The scalability of the system for higher bit-rate (60 GHz) is also simulated and discussed.

  9. Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis.

    Poorebrahim, Mansour; Salarian, Ali; Najafi, Saeideh; Abazari, Mohammad Foad; Aleagha, Maryam Nouri; Dadras, Mohammad Nasr; Jazayeri, Seyed Mohammad; Ataei, Atousa; Poortahmasebi, Vahdat

    2017-05-01

    Epstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) - a hub gene with the highest centrality score - appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation.

  10. The Mechanism Research of Qishen Yiqi Formula by Module-Network Analysis

    Zheng, Shichao; Zhang, Yanling; Qiao, Yanjiang

    2015-01-01

    Qishen Yiqi formula (QSYQ) has the effect of tonifying Qi and promoting blood circulation, which is widely used to treat the cardiovascular diseases with Qi deficiency and blood stasis syndrome. However, the mechanism of QSYQ to tonify Qi and promote blood circulation is rarely reported at molecular or systems level. This study aimed to elucidate the mechanism of QSYQ based on the protein interaction network (PIN) analysis. The targets’ information of the active components was obtained from C...

  11. Modulation of cortical-subcortical networks in Parkinson’s disease by applied field effects

    Hess, Christopher W.

    2013-01-01

    Studies suggest that endogenous field effects may play a role in neuronal oscillations and communication. Non-invasive transcranial electrical stimulation with low-intensity currents can also have direct effects on the underlying cortex as well as distant network effects. While Parkinson’s disease (PD) is amenable to invasive neuromodulation in the basal ganglia by deep brain stimulation (DBS), techniques of non-invasive neuromodulation like transcranial direct current stimulation (tDCS) and ...

  12. Relationship Reciprocation Modulates Resource Allocation in Adolescent Social Networks: Developmental Effects

    Burnett Heyes, Stephanie; Jih, Yeou?Rong; Block, Per; Hiu, Chii?Fen; Holmes, Emily A.; Lau, Jennifer Y. F.

    2015-01-01

    Adolescence is characterized as a period of social reorientation toward peer relationships, entailing the emergence of sophisticated social abilities. Two studies (Study 1: N?=?42, ages 13?17; Study 2: N?=?81, ages 13?16) investigated age group differences in the impact of relationship reciprocation within school?based social networks on an experimental measure of cooperation behavior. Results suggest development between mid? and late adolescence in the extent to which reciprocation of social...

  13. Space station common module power system network topology and hardware development

    Landis, D. M.

    1985-01-01

    Candidate power system newtork topologies for the space station common module are defined and developed and the necessary hardware for test and evaluation is provided. Martin Marietta's approach to performing the proposed program is presented. Performance of the tasks described will assure systematic development and evaluation of program results, and will provide the necessary management tools, visibility, and control techniques for performance assessment. The plan is submitted in accordance with the data requirements given and includes a comprehensive task logic flow diagram, time phased manpower requirements, a program milestone schedule, and detailed descriptions of each program task.

  14. Abnormal dopaminergic modulation of striato-cortical networks underlies levodopa-induced dyskinesias in humans

    Herz, Damian M.; Haagensen, Brian N.; Christensen, Mark S.

    2015-01-01

    of levodopa-induced dyskinesias. Twenty-six patients with Parkinson's disease (age range: 51–84 years; 11 females) received a single dose of levodopa and then performed a task in which they had to produce or suppress a movement in response to visual cues. Task-related activity was continuously mapped...... with functional magnetic resonance imaging. Dynamic causal modelling was applied to assess levodopa-induced modulation of effective connectivity between the pre-supplementary motor area, primary motor cortex and putamen when patients suppressed a motor response. Bayesian model selection revealed that patients who...

  15. Water diffusion reveals networks that modulate multiregional morphological plasticity after repetitive brain stimulation.

    Abe, Mitsunari; Fukuyama, Hidenao; Mima, Tatsuya

    2014-03-25

    Repetitive brain stimulation protocols induce plasticity in the stimulated site in brain slice models. Recent evidence from network models has indicated that additional plasticity-related changes occur in nonstimulated remote regions. Despite increasing use of brain stimulation protocols in experimental and clinical settings, the neural substrates underlying the additional effects in remote regions are unknown. Diffusion-weighted MRI (DWI) probes water diffusion and can be used to estimate morphological changes in cortical tissue that occur with the induction of plasticity. Using DWI techniques, we estimated morphological changes induced by application of repetitive transcranial magnetic stimulation (rTMS) over the left primary motor cortex (M1). We found that rTMS altered water diffusion in multiple regions including the left M1. Notably, the change in water diffusion was retained longest in the left M1 and remote regions that had a correlation of baseline fluctuations in water diffusion before rTMS. We conclude that synchronization of water diffusion at rest between stimulated and remote regions ensures retention of rTMS-induced changes in water diffusion in remote regions. Synchronized fluctuations in the morphology of cortical microstructures between stimulated and remote regions might identify networks that allow retention of plasticity-related morphological changes in multiple regions after brain stimulation protocols. These results increase our understanding of the effects of brain stimulation-induced plasticity on multiregional brain networks. DWI techniques could provide a tool to evaluate treatment effects of brain stimulation protocols in patients with brain disorders.

  16. Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli.

    Elisa M Tartaglia

    2015-02-01

    Full Text Available Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming sensory information. The mechanistic and functional relationship between these two basic neurophysiological signatures of working memory remains elusive. We propose that match signals are generated as a result of transient changes in local network excitability brought about by persistent activity. Neurons more active will be more excitable, and thus more responsive to external inputs. Accordingly, network responses are jointly determined by the incoming stimulus and the ongoing pattern of persistent activity. Using a spiking model network, we show that this mechanism is able to reproduce most of the experimental phenomenology of match effects as exposed by single-cell recordings during delayed-response tasks. The model provides a unified, parsimonious mechanistic account of the main neuronal correlates of working memory, makes several experimentally testable predictions, and demonstrates a new functional role for persistent activity.

  17. A Conserved Circular Network of Coregulated Lipids Modulates Innate Immune Responses.

    Köberlin, Marielle S; Snijder, Berend; Heinz, Leonhard X; Baumann, Christoph L; Fauster, Astrid; Vladimer, Gregory I; Gavin, Anne-Claude; Superti-Furga, Giulio

    2015-07-02

    Lipid composition affects the biophysical properties of membranes that provide a platform for receptor-mediated cellular signaling. To study the regulatory role of membrane lipid composition, we combined genetic perturbations of sphingolipid metabolism with the quantification of diverse steps in Toll-like receptor (TLR) signaling and mass spectrometry-based lipidomics. Membrane lipid composition was broadly affected by these perturbations, revealing a circular network of coregulated sphingolipids and glycerophospholipids. This evolutionarily conserved network architecture simultaneously reflected membrane lipid metabolism, subcellular localization, and adaptation mechanisms. Integration of the diverse TLR-induced inflammatory phenotypes with changes in lipid abundance assigned distinct functional roles to individual lipid species organized across the network. This functional annotation accurately predicted the inflammatory response of cells derived from patients suffering from lipid storage disorders, based solely on their altered membrane lipid composition. The analytical strategy described here empowers the understanding of higher-level organization of membrane lipid function in diverse biological systems. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  18. Measuring the extent of overlaps in protected area designations.

    Deguignet, Marine; Arnell, Andy; Juffe-Bignoli, Diego; Shi, Yichuan; Bingham, Heather; MacSharry, Brian; Kingston, Naomi

    2017-01-01

    Over the past decades, a number of national policies and international conventions have been implemented to promote the expansion of the world's protected area network, leading to a diversification of protected area strategies, types and designations. As a result, many areas are protected by more than one convention, legal instrument, or other effective means which may result in a lack of clarity around the governance and management regimes of particular locations. We assess the degree to which different designations overlap at global, regional and national levels to understand the extent of this phenomenon at different scales. We then compare the distribution and coverage of these multi-designated areas in the terrestrial and marine realms at the global level and among different regions, and we present the percentage of each county's protected area extent that is under more than one designation. Our findings show that almost a quarter of the world's protected area network is protected through more than one designation. In fact, we have documented up to eight overlapping designations. These overlaps in protected area designations occur in every region of the world, both in the terrestrial and marine realms, but are more common in the terrestrial realm and in some regions, notably Europe. In the terrestrial realm, the most common overlap is between one national and one international designation. In the marine realm, the most common overlap is between any two national designations. Multi-designations are therefore a widespread phenomenon but its implications are not well understood. This analysis identifies, for the first time, multi-designated areas across all designation types. This is a key step to understand how these areas are managed and governed to then move towards integrated and collaborative approaches that consider the different management and conservation objectives of each designation.

  19. Integer-linear-programing optimization in scalable video multicast with adaptive modulation and coding in wireless networks.

    Lee, Dongyul; Lee, Chaewoo

    2014-01-01

    The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

  20. Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

    Dongyul Lee

    2014-01-01

    Full Text Available The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC with adaptive modulation and coding (AMC provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

  1. Cognitive emotion regulation in children: Reappraisal of emotional faces modulates neural source activity in a frontoparietal network.

    Wessing, Ida; Rehbein, Maimu A; Romer, Georg; Achtergarde, Sandra; Dobel, Christian; Zwitserlood, Pienie; Fürniss, Tilman; Junghöfer, Markus

    2015-06-01

    Emotion regulation has an important role in child development and psychopathology. Reappraisal as cognitive regulation technique can be used effectively by children. Moreover, an ERP component known to reflect emotional processing called late positive potential (LPP) can be modulated by children using reappraisal and this modulation is also related to children's emotional adjustment. The present study seeks to elucidate the neural generators of such LPP effects. To this end, children aged 8-14 years reappraised emotional faces, while neural activity in an LPP time window was estimated using magnetoencephalography-based source localization. Additionally, neural activity was correlated with two indexes of emotional adjustment and age. Reappraisal reduced activity in the left dorsolateral prefrontal cortex during down-regulation and enhanced activity in the right parietal cortex during up-regulation. Activity in the visual cortex decreased with increasing age, more adaptive emotion regulation and less anxiety. Results demonstrate that reappraisal changed activity within a frontoparietal network in children. Decreasing activity in the visual cortex with increasing age is suggested to reflect neural maturation. A similar decrease with adaptive emotion regulation and less anxiety implies that better emotional adjustment may be associated with an advance in neural maturation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. Spatial light modulators for full cross-connections in optical networks

    Juday, Richard D. (Inventor)

    2004-01-01

    A polarization-independent optical switch is disclosed for switching at least one incoming beam from at least one input source to at least one output drain. The switch includes a polarizing beam splitter to split each of the at least one incoming beam into a first input beam and a second input beam, wherein the first input beam and the second input beams are independently polarized; a wave plate optically coupled to the second input beam for converting the polarization of the second input beam to an appropriately polarized second input beam; a beam combiner optically coupled to the first input beam and the modified second input beam, wherein the beam combiner accepts the first input beam and the modified second input beam to produce a combined beam; the combined beam is invariant to the polarization state of the input source's polarization; and a controllable spatial light modulator optically coupled to the combined beam, wherein the combined beam is diffracted by the controllable spatial light modulator to place light at a plurality of output locations.

  3. Different Brain Network Activations Induced by Modulation and Nonmodulation Laser Acupuncture

    Chang-Wei Hsieh

    2011-01-01

    Full Text Available The aim of this study is to compare the distinct cerebral activation with continued wave (CW and 10 Hz-modulated wave (MW stimulation during low-level laser acupuncture. Functional magnetic resonance imaging (fMRI studies were performed to investigate the possible mechanism during laser acupuncture stimulation at the left foot's yongquan (K1 acupoint. There are 12 healthy right-handed volunteers for each type of laser stimulation (10-Hz-Modulated wave: 8 males and 4 females; continued wave: 9 males and 3 females. The analysis of multisubjects in this experiment was applied by random-effect (RFX analysis. In CW groups, significant activations were found within the inferior parietal lobule, the primary somatosensory cortex, and the precuneus of left parietal lobe. Medial and superior frontal gyrus of left frontal lobe were also aroused. In MW groups, significant activations were found within the primary motor cortex and middle temporal gyrus of left hemisphere and bilateral cuneus. Placebo stimulation did not show any activation. Most activation areas were involved in the functions of memory, attention, and self-consciousness. The results showed the cerebral hemodynamic responses of two laser acupuncture stimulation modes and implied that its mechanism was not only based upon afferent sensory information processing, but that it also had the hemodynamic property altered during external stimulation.

  4. A Greedy Algorithm for Neighborhood Overlap-Based Community Detection

    Natarajan Meghanathan

    2016-01-01

    Full Text Available The neighborhood overlap (NOVER of an edge u-v is defined as the ratio of the number of nodes who are neighbors for both u and v to that of the number of nodes who are neighbors of at least u or v. In this paper, we hypothesize that an edge u-v with a lower NOVER score bridges two or more sets of vertices, with very few edges (other than u-v connecting vertices from one set to another set. Accordingly, we propose a greedy algorithm of iteratively removing the edges of a network in the increasing order of their neighborhood overlap and calculating the modularity score of the resulting network component(s after the removal of each edge. The network component(s that have the largest cumulative modularity score are identified as the different communities of the network. We evaluate the performance of the proposed NOVER-based community detection algorithm on nine real-world network graphs and compare the performance against the multi-level aggregation-based Louvain algorithm, as well as the original and time-efficient versions of the edge betweenness-based Girvan-Newman (GN community detection algorithm.

  5. Modulation of VEGF-induced migration and network formation by lymphatic endothelial cells: Roles of platelets and podoplanin.

    Langan, Stacey A; Navarro-Núñez, Leyre; Watson, Steve P; Nash, Gerard B

    2017-07-20

    Lymphatic endothelial cells (LEC) express the transmembrane receptor podoplanin whose only known endogenous ligand CLEC-2 is found on platelets. Both podoplanin and CLEC-2 are required for normal lymphangiogenesis as mice lacking either protein develop a blood-lymphatic mixing phenotype. We investigated the roles of podoplanin and its interaction with platelets in migration and tube formation by LEC. Addition of platelets or antibody-mediated crosslinking of podoplanin inhibited LEC migration induced by vascular endothelial growth factors (VEGF-A or VEGF-C), but did not modify basal migration or the response to basic fibroblast growth factor or epidermal growth factor. In addition, platelets and podoplanin crosslinking disrupted networks of LEC formed in co-culture with fibroblasts. Depletion of podoplanin in LEC using siRNA negated the pro-migratory effect of VEGF-A and VEGF-C. Inhibition of RhoA or Rho-kinase reduced LEC migration induced by VEGF-C, but had no further effect after crosslinking of podoplanin, suggesting that podoplanin is required for signaling downstream of VEGF-receptors but upstream of RhoA. Together, these data reveal for the first time that podoplanin is an intrinsic specific regulator of VEGF-mediated migration and network formation in LEC and identify crosslinking of podoplanin by platelets or antibodies as mechanisms to modulate this pathway.

  6. Development of efficiency module of organization of Arctic sea cargo transportation with application of neural network technologies

    Sobolevskaya, E. Yu; Glushkov, S. V.; Levchenko, N. G.; Orlov, A. P.

    2018-05-01

    The analysis of software intended for organizing and managing the processes of sea cargo transportation has been carried out. The shortcomings of information resources are presented, for the organization of work in the Arctic and Subarctic regions of the Far East: the lack of decision support systems, the lack of factor analysis to calculate the time and cost of delivery. The architecture of the module for calculating the effectiveness of the organization of sea cargo transportation has been developed. The simulation process has been considered, which is based on the neural network. The main classification factors with their weighting coefficients have been identified. The architecture of the neural network has been developed to calculate the efficiency of the organization of sea cargo transportation in Arctic conditions. The architecture of the intellectual system of organization of sea cargo transportation has been developed, taking into account the difficult navigation conditions in the Arctic. Its implementation will allow one to provide the management of the shipping company with predictive analytics; to support decision-making; to calculate the most efficient delivery route; to provide on demand online transportation forecast, to minimize the shipping cost, delays in transit, and risks to cargo safety.

  7. All-optical virtual private network system in OFDM based long-reach PON using RSOA re-modulation technique

    Kim, Chang-Hun; Jung, Sang-Min; Kang, Su-Min; Han, Sang-Kook

    2015-01-01

    We propose an all-optical virtual private network (VPN) system in an orthogonal frequency division multiplexing (OFDM) based long reach PON (LR-PON). In the optical access network field, technologies based on fundamental upstream (U/S) and downstream (D/S) have been actively researched to accommodate explosion of data capacity. However, data transmission among the end users which is arisen from cloud computing, file-sharing and interactive game takes a large weight inside of internet traffic. Moreover, this traffic is predicted to increase more if Internet of Things (IoT) services are activated. In a conventional PON, VPN data is transmitted through ONU-OLT-ONU via U/S and D/S carriers. It leads to waste of bandwidth and energy due to O-E-O conversion in the OLT and round-trip propagation between OLT and remote node (RN). Also, it causes inevitable load to the OLT for electrical buffer, scheduling and routing. The network inefficiency becomes more critical in a LR-PON which has been researched as an effort to reduce CAPEX and OPEX through metro-access consolidation. In the proposed system, the VPN data is separated from conventional U/S and re-modulated on the D/S carrier by using RSOA in the ONUs to avoid bandwidth consumption of U/S and D/S unlike in previously reported system. Moreover, the transmitted VPN data is re-directed to the ONUs by wavelength selective reflector device in the RN without passing through the OLT. Experimental demonstration for the VPN communication system in an OFDM based LR-PON has been verified.

  8. H.264 Layered Coded Video over Wireless Networks: Channel Coding and Modulation Constraints

    Ghandi MM

    2006-01-01

    Full Text Available This paper considers the prioritised transmission of H.264 layered coded video over wireless channels. For appropriate protection of video data, methods such as prioritised forward error correction coding (FEC or hierarchical quadrature amplitude modulation (HQAM can be employed, but each imposes system constraints. FEC provides good protection but at the price of a high overhead and complexity. HQAM is less complex and does not introduce any overhead, but permits only fixed data ratios between the priority layers. Such constraints are analysed and practical solutions are proposed for layered transmission of data-partitioned and SNR-scalable coded video where combinations of HQAM and FEC are used to exploit the advantages of both coding methods. Simulation results show that the flexibility of SNR scalability and absence of picture drift imply that SNR scalability as modelled is superior to data partitioning in such applications.

  9. Two-user opportunistic scheduling using hierarchical modulations in wireless networks with heterogenous average link gains

    Hossain, Md Jahangir

    2010-03-01

    Our contribution, in this paper, is two-fold. First, we analyze the performance of a hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) scheme, which was proposed by the authors, in a fading environment where different users have different average link gains. Specifically, we present a new expression for the spectral efficiency (SE) of the users and using this expression, we compare the degrees of fairness (DOF) of the TBS scheme with that of classical single user opportunistic scheduling schemes, namely, absolute carrier-to-noise ratio (CNR) based single-best user scheduling (SBS) and normalized CNR based proportional fair scheduling (PFS) schemes. The second contribution is that we propose a new hybrid two-user opportunistic scheduling (HTS) scheme based on our earlier proposed TBS scheme. This HTS scheme selects the first user based on the largest absolute CNR value among all the users while the second user is selected based on the ratios of the absolute CNRs to the corresponding average CNRs of the remaining users. The total transmission rate i.e., the constellation size is selected according to the absolute CNR of the first best user. The total transmission rate is then allocated among these selected users by joint consideration of their absolute CNRs and allocated number of information bit(s) are transmitted to them using hierarchical modulations. Numerical results are presented for a fading environment where different users experience independent but non-identical (i.n.d.) channel fading. These selected numerical results show that the proposed HTS scheme can considerably increase the system\\'s fairness without any degradation of the link spectral efficiency (LSE) i.e., the multiuser diversity gain compared to the classical SBS scheme. These results also show that the proposed HTS scheme has a lower fairness in comparison to the PFS scheme which suffers from a considerable degradation in LSE. © 2010 IEEE.

  10. Persistency and flexibility of complex brain networks underlie dual-task interference.

    Alavash, Mohsen; Hilgetag, Claus C; Thiel, Christiane M; Gießing, Carsten

    2015-09-01

    Previous studies on multitasking suggest that performance decline during concurrent task processing arises from interfering brain modules. Here, we used graph-theoretical network analysis to define functional brain modules and relate the modular organization of complex brain networks to behavioral dual-task costs. Based on resting-state and task fMRI we explored two organizational aspects potentially associated with behavioral interference when human subjects performed a visuospatial and speech task simultaneously: the topological overlap between persistent single-task modules, and the flexibility of single-task modules in adaptation to the dual-task condition. Participants showed a significant decline in visuospatial accuracy in the dual-task compared with single visuospatial task. Global analysis of topological similarity between modules revealed that the overlap between single-task modules significantly correlated with the decline in visuospatial accuracy. Subjects with larger overlap between single-task modules showed higher behavioral interference. Furthermore, lower flexible reconfiguration of single-task modules in adaptation to the dual-task condition significantly correlated with larger decline in visuospatial accuracy. Subjects with lower modular flexibility showed higher behavioral interference. At the regional level, higher overlap between single-task modules and less modular flexibility in the somatomotor cortex positively correlated with the decline in visuospatial accuracy. Additionally, higher modular flexibility in cingulate and frontal control areas and lower flexibility in right-lateralized nodes comprising the middle occipital and superior temporal gyri supported dual-tasking. Our results suggest that persistency and flexibility of brain modules are important determinants of dual-task costs. We conclude that efficient dual-tasking benefits from a specific balance between flexibility and rigidity of functional brain modules. © 2015 Wiley

  11. Efficient methods for overlapping group lasso.

    Yuan, Lei; Liu, Jun; Ye, Jieping

    2013-09-01

    The group Lasso is an extension of the Lasso for feature selection on (predefined) nonoverlapping groups of features. The nonoverlapping group structure limits its applicability in practice. There have been several recent attempts to study a more general formulation where groups of features are given, potentially with overlaps between the groups. The resulting optimization is, however, much more challenging to solve due to the group overlaps. In this paper, we consider the efficient optimization of the overlapping group Lasso penalized problem. We reveal several key properties of the proximal operator associated with the overlapping group Lasso, and compute the proximal operator by solving the smooth and convex dual problem, which allows the use of the gradient descent type of algorithms for the optimization. Our methods and theoretical results are then generalized to tackle the general overlapping group Lasso formulation based on the l(q) norm. We further extend our algorithm to solve a nonconvex overlapping group Lasso formulation based on the capped norm regularization, which reduces the estimation bias introduced by the convex penalty. We have performed empirical evaluations using both a synthetic and the breast cancer gene expression dataset, which consists of 8,141 genes organized into (overlapping) gene sets. Experimental results show that the proposed algorithm is more efficient than existing state-of-the-art algorithms. Results also demonstrate the effectiveness of the nonconvex formulation for overlapping group Lasso.

  12. Relationship Reciprocation Modulates Resource Allocation in Adolescent Social Networks: Developmental Effects.

    Burnett Heyes, Stephanie; Jih, Yeou-Rong; Block, Per; Hiu, Chii-Fen; Holmes, Emily A; Lau, Jennifer Y F

    2015-01-01

    Adolescence is characterized as a period of social reorientation toward peer relationships, entailing the emergence of sophisticated social abilities. Two studies (Study 1: N = 42, ages 13-17; Study 2: N = 81, ages 13-16) investigated age group differences in the impact of relationship reciprocation within school-based social networks on an experimental measure of cooperation behavior. Results suggest development between mid- and late adolescence in the extent to which reciprocation of social ties predicted resource allocation. With increasing age group, investment decisions increasingly reflected the degree to which peers reciprocated feelings of friendship. This result may reflect social-cognitive development, which could facilitate the ability to navigate an increasingly complex social world in adolescence and promote positive and enduring relationships into adulthood. © 2015 The Authors. Child Development published by Wiley Periodicals, Inc. on behalf of Society for Research in Child Development.

  13. Improving ECG classification accuracy using an ensemble of neural network modules.

    Mehrdad Javadi

    Full Text Available This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization.

  14. Probabilistic monitoring in intrusion detection module for energy efficiency in mobile ad hoc networks

    De Rango, Floriano; Lupia, Andrea

    2016-05-01

    MANETs allow mobile nodes communicating to each other using the wireless medium. A key aspect of these kind of networks is the security, because their setup is done without an infrastructure, so external nodes could interfere in the communication. Mobile nodes could be compromised, misbehaving during the multi-hop transmission of data, or they could have a selfish behavior to save energy, which is another important constraint in MANETs. The detection of these behaviors need a framework that takes into account the latest interactions among nodes, so malicious or selfish nodes could be detected also if their behavior is changed over time. The monitoring activity increases the energy consumption, so our proposal takes into account this issue reducing the energy required by the monitoring system, keeping the effectiveness of the intrusion detection system. The results show an improvement in the saved energy, improving the detection performance too.

  15. Targeting polyelectrolyte networks in purulent body fluids to modulate bactericidal properties of some antibiotics

    Bucki R

    2018-01-01

    Full Text Available Robert Bucki,1,* Bonita Durnaś,2,* Marzena Wątek,2,3 Ewelina Piktel,1 Katrina Cruz,4 Przemysław Wolak,2 Paul B Savage,5 Paul A Janmey4 1Department of Microbiological and Nanobiomedical Engineering, Medical University of Białystok, Białystok, 2Department of Microbiology and Immunology, The Faculty of Health Sciences of the Jan Kochanowski University in Kielce, 3Holy Cross Oncology Center of Kielce, Kielce, Kielce, Poland; 4Department of Physiology, Institute for Medicine and Engineering, University of Pennsylvania, Philadelphia, PA, 5Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA *These authors contributed equally to this work Abstract: The response of the human immune system to most bacterial infections results in accumulation of neutrophils at infection sites that release a significant quantity of DNA and F-actin. Both are negatively charged polyelectrolytes that can interact with positively charged host defense molecules such as cathelicidin-delivered LL-37 peptide or other cationic antibiotic agents. Evaluation of the ability of bacterial outgrowth (using luminescence measurements or counting colony-forming units to form a biofilm (quantified by crystal violet staining and analysis of the structure of DNA/F-actin network by optical microscopy in human pus samples treated with different antibiotics in combination with plasma gelsolin, DNAse 1, and/or poly-aspartic acid revealed that bactericidal activity of most tested antibacterial agents increases in the presence of DNA/F-actin depolymerizing factors. Keywords: antibiotic activity, polyelectrolyte network, depolymerizing factors, cathelicidin, ceragenins, DNase 1, cystic fibrosis

  16. Neural overlap in processing music and speech.

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

    2015-03-19

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  17. Neural overlap in processing music and speech

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.

    2015-01-01

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513

  18. Overlapping communities from dense disjoint and high total degree clusters

    Zhang, Hongli; Gao, Yang; Zhang, Yue

    2018-04-01

    Community plays an important role in the field of sociology, biology and especially in domains of computer science, where systems are often represented as networks. And community detection is of great importance in the domains. A community is a dense subgraph of the whole graph with more links between its members than between its members to the outside nodes, and nodes in the same community probably share common properties or play similar roles in the graph. Communities overlap when nodes in a graph belong to multiple communities. A vast variety of overlapping community detection methods have been proposed in the literature, and the local expansion method is one of the most successful techniques dealing with large networks. The paper presents a density-based seeding method, in which dense disjoint local clusters are searched and selected as seeds. The proposed method selects a seed by the total degree and density of local clusters utilizing merely local structures of the network. Furthermore, this paper proposes a novel community refining phase via minimizing the conductance of each community, through which the quality of identified communities is largely improved in linear time. Experimental results in synthetic networks show that the proposed seeding method outperforms other seeding methods in the state of the art and the proposed refining method largely enhances the quality of the identified communities. Experimental results in real graphs with ground-truth communities show that the proposed approach outperforms other state of the art overlapping community detection algorithms, in particular, it is more than two orders of magnitude faster than the existing global algorithms with higher quality, and it obtains much more accurate community structure than the current local algorithms without any priori information.

  19. Femtosecond resolved diagnostics for electron beam and XUV seed temporal overlap at sFLASH

    Tarkeshian, Roxana

    2012-02-01

    sFLASH is a seeded experiment at the Free-Electron Laser FLASH in Hamburg. It uses a 38 nm High-Harmonic-Generation (HHG) scheme to seed the FEL-process in a 10m long variable-gap undulator. The temporal overlap between the electron and HHG pulses is critical to the seeding process. The use of a 3 rd harmonic accelerating module provides a high current electron beam with ∝ (400 fs) FWHM bunch duration. The duration of the HHG laser pulse is ≤ (30 fs) FWHM . The desired overlap is achieved in two steps. Firstly, the HHG drive laser is brought to temporal overlap with the incoherent spontaneous radiation from an upstream undulator with picosecond resolution. The temporal overlap is periodically monitored using a streak camera installed in the linear accelerator tunnel. Next, the coherent radiation from an undulator is used to determine the exact overlap of the electron beam in a modulator-radiator set-up with sub-picosecond resolution. The physical and technical principles of the setup providing the temporal overlap are described. Results of the system are analyzed. An analytical approach and simulation results for the performance of the seeding experiment are presented. First attempts at demonstration of seeding are discussed. Strategies for optimizing overlap conditions are presented. (orig.)

  20. Femtosecond resolved diagnostics for electron beam and XUV seed temporal overlap at sFLASH

    Tarkeshian, Roxana

    2012-02-15

    sFLASH is a seeded experiment at the Free-Electron Laser FLASH in Hamburg. It uses a 38 nm High-Harmonic-Generation (HHG) scheme to seed the FEL-process in a 10m long variable-gap undulator. The temporal overlap between the electron and HHG pulses is critical to the seeding process. The use of a 3{sup rd} harmonic accelerating module provides a high current electron beam with {proportional_to} (400 fs){sub FWHM} bunch duration. The duration of the HHG laser pulse is {<=} (30 fs){sub FWHM}. The desired overlap is achieved in two steps. Firstly, the HHG drive laser is brought to temporal overlap with the incoherent spontaneous radiation from an upstream undulator with picosecond resolution. The temporal overlap is periodically monitored using a streak camera installed in the linear accelerator tunnel. Next, the coherent radiation from an undulator is used to determine the exact overlap of the electron beam in a modulator-radiator set-up with sub-picosecond resolution. The physical and technical principles of the setup providing the temporal overlap are described. Results of the system are analyzed. An analytical approach and simulation results for the performance of the seeding experiment are presented. First attempts at demonstration of seeding are discussed. Strategies for optimizing overlap conditions are presented. (orig.)

  1. Modulation of phytochrome signaling networks for improved biomass accumulation using a bioenergy crop model

    Mockler, Todd C. [Donald Danforth Plant Science Center, Saint Louis, MO (United States)

    2016-11-07

    Plant growth and development, including stem elongation, flowering time, and shade-avoidance habits, are affected by wavelength composition (i.e., light quality) of the light environment. the molecular mechanisms underlying light perception and signaling pathways in plants have been best characterized in Arabidopsis thaliana where dozens of genes have been implicated in converging, complementary, and antagonistic pathways communicating light quality cues perceived by the phytochrome (red/far-red) cryptochrome (blue) and phototropin (blue) photorecptors. Light perception and signaling have been studied in grasses, including rice and sorghum but in much less detail than in Arabidopsis. During the course of the Mocker lab's DOE-funded wrok generating a gene expression atlas in Brachypodium distachyon we observed that Brachypodium plants grown in continuous monochromatic red light or continuous white light enriched in far-red light accumulated significantly more biomass and exhibited significantly greater seed yield than plants grown in monochromatic blue light or white light. This phenomenon was also observed in two other grasses, switchgrass and rice. We will systematically manipulate the expression of genes predicted to function in Brachypodium phytochrome signaling and assess the phenotypic consequences in transgenic Brachypodium plants in terms of morphology, stature, biomass accumulation, and cell wall composition. We will also interrogate direct interactions between candidate phytochrome signaling transcription factors and target promoters using a high-throughput yeast one-hybrid system. Brachypodium distachyon has emerged as a model grass species and is closely related to candidate feedstock crops for bioethanol production. Identification of genes capable of modifying growth characteristics of Brachypodium, when misexpressed, in particular increasing biomass accumulation, by modulating photoreceptor signaling will provide valuable candidates for

  2. Extraversion modulates functional connectivity hubs of resting-state brain networks.

    Pang, Yajing; Cui, Qian; Duan, Xujun; Chen, Heng; Zeng, Ling; Zhang, Zhiqiang; Lu, Guangming; Chen, Huafu

    2017-09-01

    Personality dimension extraversion describes individual differences in social behaviour and socio-emotional functioning. The intrinsic functional connectivity patterns of the brain are reportedly associated with extraversion. However, whether or not extraversion is associated with functional hubs warrants clarification. Functional hubs are involved in the rapid integration of neural processing, and their dysfunction contributes to the development of neuropsychiatric disorders. In this study, we employed the functional connectivity density (FCD) method for the first time to distinguish the energy-efficient hubs associated with extraversion. The resting-state functional magnetic resonance imaging data of 71 healthy subjects were used in the analysis. Short-range FCD was positively correlated with extraversion in the left cuneus, revealing a link between the local functional activity of this region and extraversion in risk-taking. Long-range FCD was negatively correlated with extraversion in the right superior frontal gyrus and the inferior frontal gyrus. Seed-based resting-state functional connectivity (RSFC) analyses revealed that a decreased long-range FCD in individuals with high extraversion scores showed a low long-range functional connectivity pattern between the medial and dorsolateral prefrontal cortex, middle temporal gyrus, and anterior cingulate cortex. This result suggests that decreased RSFC patterns are responsible for self-esteem, self-evaluation, and inhibitory behaviour system that account for the modulation and shaping of extraversion. Overall, our results emphasize specific brain hubs, and reveal long-range functional connections in relation to extraversion, thereby providing a neurobiological basis of extraversion. © 2015 The British Psychological Society.

  3. Auditing Complex Concepts in Overlapping Subsets of SNOMED

    Wang, Yue; Wei, Duo; Xu, Junchuan; Elhanan, Gai; Perl, Yehoshua; Halper, Michael; Chen, Yan; Spackman, Kent A.; Hripcsak, George

    2008-01-01

    Limited resources and the sheer volume of concepts make auditing a large terminology, such as SNOMED CT, a daunting task. It is essential to devise techniques that can aid an auditor by automatically identifying concepts that deserve attention. A methodology for this purpose based on a previously introduced abstraction network (called the p-area taxonomy) for a SNOMED CT hierarchy is presented. The methodology algorithmically gathers concepts appearing in certain overlapping subsets, defined exclusively with respect to the p-area taxonomy, for review. The results of applying the methodology to SNOMED’s Specimen hierarchy are presented. These results are compared against a control sample composed of concepts residing in subsets without the overlaps. With the use of the double bootstrap, the concept group produced by our methodology is shown to yield a statistically significant higher proportion of error discoveries. PMID:18998838

  4. Optimization of control bank overlap for SMART

    Song, Jae Seung; Cho, Byung Oh; Zee, Sung Quun

    1998-07-01

    In the pressurized water reactor, control banks are operated by 40% effective core height overlap to avoid decrease of differential rod worth. This overlap does not effect on the core depletion history because the pressurized water reactor core operated at all rod out condition for the most of the operation time. For the boron free reactor SMART, however, one or more control banks are always inserted in the core to maintain critical condition, and the control bank overlap effects on the core depletion history. Since the cycle length of SMART is limited by three-dimensional core peaking factor at EOC, at which the control bank located at the core center is withdrawn, the cycle length of SMART is affected by the control bank overlap. In this report, the effect of control bank overlap on the core depletion history was evaluated. It is concluded that 60 cm control bank overlap corresponding to 30% effective core height was selected not to increase maximum peaking factor at EOC so that the control bank overlap does not affect the cycle length of the core. (author). 8 refs., 2 tabs., 19 figs

  5. Prediction of peak overlap in NMR spectra

    Hefke, Frederik; Schmucki, Roland; Güntert, Peter

    2013-01-01

    Peak overlap is one of the major factors complicating the analysis of biomolecular NMR spectra. We present a general method for predicting the extent of peak overlap in multidimensional NMR spectra and its validation using both, experimental data sets and Monte Carlo simulation. The method is based on knowledge of the magnetization transfer pathways of the NMR experiments and chemical shift statistics from the Biological Magnetic Resonance Data Bank. Assuming a normal distribution with characteristic mean value and standard deviation for the chemical shift of each observable atom, an analytic expression was derived for the expected overlap probability of the cross peaks. The analytical approach was verified to agree with the average peak overlap in a large number of individual peak lists simulated using the same chemical shift statistics. The method was applied to eight proteins, including an intrinsically disordered one, for which the prediction results could be compared with the actual overlap based on the experimentally measured chemical shifts. The extent of overlap predicted using only statistical chemical shift information was in good agreement with the overlap that was observed when the measured shifts were used in the virtual spectrum, except for the intrinsically disordered protein. Since the spectral complexity of a protein NMR spectrum is a crucial factor for protein structure determination, analytical overlap prediction can be used to identify potentially difficult proteins before conducting NMR experiments. Overlap predictions can be tailored to particular classes of proteins by preparing statistics from corresponding protein databases. The method is also suitable for optimizing recording parameters and labeling schemes for NMR experiments and improving the reliability of automated spectra analysis and protein structure determination.

  6. Comparison of various HFB overlap formulae

    Oi, M.

    2015-01-01

    The nuclear many-body approach beyond the mean-field approximation demands overlap calculations of different many-body states. Norm overlaps between two different Hartree-Fock-Bogoliubov states can be calculated by means of the Onishi formula. However, the formula leaves the sign of the norm overlap undetermined. Several approaches have been proposed by Hara-Hayashi-Ring, Neergård-Wüst, and Robledo. In the present paper, the Neergård-Wüst formula is examined whether it is applicable to practical numerical calculations, although the formula was dismissed by many nuclear theoreticians so far for unknown reasons

  7. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease.

    Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir; Brown, Peter

    2016-05-01

    Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the

  8. Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

    Yuan-Chieh Lo

    2018-02-01

    Full Text Available Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe. Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t| °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR technique and implemented into the real-time embedded system.

  9. Using time-to-contact information to assess potential collision modulates both visual and temporal prediction networks

    Jennifer T Coull

    2008-09-01

    Full Text Available Accurate estimates of the time-to-contact (TTC of approaching objects are crucial for survival. We used an ecologically valid driving simulation to compare and contrast the neural substrates of egocentric (head-on approach and allocentric (lateral approach TTC tasks in a fully factorial, event-related fMRI design. Compared to colour control tasks, both egocentric and allocentric TTC tasks activated left ventral premotor cortex/frontal operculum and inferior parietal cortex, the same areas that have previously been implicated in temporal attentional orienting. Despite differences in visual and cognitive demands, both TTC and temporal orienting paradigms encourage the use of temporally predictive information to guide behaviour, suggesting these areas may form a core network for temporal prediction. We also demonstrated that the temporal derivative of the perceptual index tau (tau-dot held predictive value for making collision judgements and varied inversely with activity in primary visual cortex (V1. Specifically, V1 activity increased with the increasing likelihood of reporting a collision, suggesting top-down attentional modulation of early visual processing areas as a function of subjective collision. Finally, egocentric viewpoints provoked a response bias for reporting collisions, rather than no-collisions, reflecting increased caution for head-on approaches. Associated increases in SMA activity suggest motor preparation mechanisms were engaged, despite the perceptual nature of the task.

  10. Numerical properties of staggered overlap fermions

    de Forcrand, Philippe; Panero, Marco

    2010-01-01

    We report the results of a numerical study of staggered overlap fermions, following the construction of Adams which reduces the number of tastes from 4 to 2 without fine-tuning. We study the sensitivity of the operator to the topology of the gauge field, its locality and its robustness to fluctuations of the gauge field. We make a first estimate of the computing cost of a quark propagator calculation, and compare with Neuberger's overlap.

  11. Transiting topological sectors with the overlap

    Creutz, Michael

    2003-01-01

    The overlap operator provides an elegant definition for the winding number of lattice gauge field configurations. Only for a set of configurations of measure zero is this procedure undefined. Without restrictions on the lattice fields, however, the space of gauge fields is simply connected. I present a simple low dimensional illustration of how the eigenvalues of a truncated overlap operator flow as one travels between different topological sectors

  12. Transcriptional regulation by competing transcription factor modules.

    Rutger Hermsen

    2006-12-01

    Full Text Available Gene regulatory networks lie at the heart of cellular computation. In these networks, intracellular and extracellular signals are integrated by transcription factors, which control the expression of transcription units by binding to cis-regulatory regions on the DNA. The designs of both eukaryotic and prokaryotic cis-regulatory regions are usually highly complex. They frequently consist of both repetitive and overlapping transcription factor binding sites. To unravel the design principles of these promoter architectures, we have designed in silico prokaryotic transcriptional logic gates with predefined input-output relations using an evolutionary algorithm. The resulting cis-regulatory designs are often composed of modules that consist of tandem arrays of binding sites to which the transcription factors bind cooperatively. Moreover, these modules often overlap with each other, leading to competition between them. Our analysis thus identifies a new signal integration motif that is based upon the interplay between intramodular cooperativity and intermodular competition. We show that this signal integration mechanism drastically enhances the capacity of cis-regulatory domains to integrate signals. Our results provide a possible explanation for the complexity of promoter architectures and could be used for the rational design of synthetic gene circuits.

  13. Capacity upgrade in short-reach optical fibre networks: simultaneous 4-PAM 20 Gbps data and polarization-modulated PPS clock signal using a single VCSEL carrier

    Isoe, G. M.; Wassin, S.; Gamatham, R. R. G.; Leitch, A. W. R.; Gibbon, T. B.

    2017-11-01

    In this work, a four-level pulse amplitude modulation (4-PAM) format with a polarization-modulated pulse per second (PPS) clock signal using a single vertical cavity surface emitting laser (VCSEL) carrier is for the first time experimentally demonstrated. We propose uncomplex alternative technique for increasing capacity and flexibility in short-reach optical communication links through multi-signal modulation onto a single VCSEL carrier. A 20 Gbps 4-PAM data signal is directly modulated onto a single mode 10 GHz bandwidth VCSEL carrier at 1310 nm, therefore, doubling the network bit rate. Carrier spectral efficiency is further maximized by exploiting the inherent orthogonal polarization switching of the VCSEL carrier with changing bias in transmission of a PPS clock signal. We, therefore, simultaneously transmit a 20 Gbps 4-PAM data signal and a polarization-based PPS clock signal using a single VCSEL carrier. It is the first time a signal VCSEL carrier is reported to simultaneously transmit a directly modulated 20 Gbps 4-PAM data signal and a polarization-based PPS clock signal. We further demonstrate on the design of a software-defined digital signal processing (DSP)-assisted receiver as an alternative to costly receiver hardware. Experimental results show that a 3.21 km fibre transmission with simultaneous 20 Gbps 4-PAM data signal and polarization-based PPS clock signal introduced a penalty of 3.76 dB. The contribution of polarization-based PPS clock signal to this penalty was found out to be 0.41 dB. Simultaneous distribution of data and timing clock signals over shared network infrastructure significantly increases the aggregated data rate at different optical network units (ONUs), without costly investment.

  14. Noise-induced modulation of the relaxation kinetics around a non-equilibrium steady state of non-linear chemical reaction networks.

    Rajesh Ramaswamy

    2011-01-01

    Full Text Available Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confinement increases the lifetimes of all species that are involved in any non-linear reaction as a reactant. Burst monotonically increases or decreases lifetimes. Competition between burst-induced and confinement-induced modulation may hence lead to a non-monotonic modulation. We quantify lifetime as the integral of the time autocorrelation function (ACF of concentration fluctuations around a non-equilibrium steady state of the reaction network. Furthermore, we look at the first and second derivatives of the ACF, each of which is affected in opposite ways by burst and confinement. This allows discriminating between these two noise sources. We analytically derive the ACF from the linear Fokker-Planck approximation of the chemical master equation in order to establish a baseline for the burst-induced modulation at low confinement. Effects of higher confinement are then studied using a partial-propensity stochastic simulation algorithm. The results presented here may help understand the mechanisms that deviate stochastic kinetics from its deterministic counterpart. In addition, they may be instrumental when using fluorescence-lifetime imaging microscopy (FLIM or fluorescence-correlation spectroscopy (FCS to measure confinement and burst in systems with known reaction rates, or, alternatively, to correct for the effects of confinement and burst when experimentally measuring reaction rates.

  15. Noise-induced modulation of the relaxation kinetics around a non-equilibrium steady state of non-linear chemical reaction networks.

    Ramaswamy, Rajesh; Sbalzarini, Ivo F; González-Segredo, Nélido

    2011-01-28

    Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confinement increases the lifetimes of all species that are involved in any non-linear reaction as a reactant. Burst monotonically increases or decreases lifetimes. Competition between burst-induced and confinement-induced modulation may hence lead to a non-monotonic modulation. We quantify lifetime as the integral of the time autocorrelation function (ACF) of concentration fluctuations around a non-equilibrium steady state of the reaction network. Furthermore, we look at the first and second derivatives of the ACF, each of which is affected in opposite ways by burst and confinement. This allows discriminating between these two noise sources. We analytically derive the ACF from the linear Fokker-Planck approximation of the chemical master equation in order to establish a baseline for the burst-induced modulation at low confinement. Effects of higher confinement are then studied using a partial-propensity stochastic simulation algorithm. The results presented here may help understand the mechanisms that deviate stochastic kinetics from its deterministic counterpart. In addition, they may be instrumental when using fluorescence-lifetime imaging microscopy (FLIM) or fluorescence-correlation spectroscopy (FCS) to measure confinement and burst in systems with known reaction rates, or, alternatively, to correct for the effects of confinement and burst when experimentally measuring reaction rates.

  16. Community detection for networks with unipartite and bipartite structure

    Chang, Chang; Tang, Chao

    2014-09-01

    Finding community structures in networks is important in network science, technology, and applications. To date, most algorithms that aim to find community structures only focus either on unipartite or bipartite networks. A unipartite network consists of one set of nodes and a bipartite network consists of two nonoverlapping sets of nodes with only links joining the nodes in different sets. However, a third type of network exists, defined here as the mixture network. Just like a bipartite network, a mixture network also consists of two sets of nodes, but some nodes may simultaneously belong to two sets, which breaks the nonoverlapping restriction of a bipartite network. The mixture network can be considered as a general case, with unipartite and bipartite networks viewed as its limiting cases. A mixture network can represent not only all the unipartite and bipartite networks, but also a wide range of real-world networks that cannot be properly represented as either unipartite or bipartite networks in fields such as biology and social science. Based on this observation, we first propose a probabilistic model that can find modules in unipartite, bipartite, and mixture networks in a unified framework based on the link community model for a unipartite undirected network [B Ball et al (2011 Phys. Rev. E 84 036103)]. We test our algorithm on synthetic networks (both overlapping and nonoverlapping communities) and apply it to two real-world networks: a southern women bipartite network and a human transcriptional regulatory mixture network. The results suggest that our model performs well for all three types of networks, is competitive with other algorithms for unipartite or bipartite networks, and is applicable to real-world networks.

  17. Polarization-multiplexed rate-adaptive non-binary-quasi-cyclic-LDPC-coded multilevel modulation with coherent detection for optical transport networks.

    Arabaci, Murat; Djordjevic, Ivan B; Saunders, Ross; Marcoccia, Roberto M

    2010-02-01

    In order to achieve high-speed transmission over optical transport networks (OTNs) and maximize its throughput, we propose using a rate-adaptive polarization-multiplexed coded multilevel modulation with coherent detection based on component non-binary quasi-cyclic (QC) LDPC codes. Compared to prior-art bit-interleaved LDPC-coded modulation (BI-LDPC-CM) scheme, the proposed non-binary LDPC-coded modulation (NB-LDPC-CM) scheme not only reduces latency due to symbol- instead of bit-level processing but also provides either impressive reduction in computational complexity or striking improvements in coding gain depending on the constellation size. As the paper presents, compared to its prior-art binary counterpart, the proposed NB-LDPC-CM scheme addresses the needs of future OTNs, which are achieving the target BER performance and providing maximum possible throughput both over the entire lifetime of the OTN, better.

  18. Inferring modules from human protein interactome classes

    Chaurasia Gautam

    2010-07-01

    Full Text Available Abstract Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features. Results We examined this issue based on the analysis of modules detected by network clustering methods applied to both integrated and individual (disaggregated data sources, which we call interactome classes. Due to class diversity, we deal with variable dependencies of data features arising from structural specificities and biases, but also from possible overlaps. Since highly connected regions of the human interactome may point to potential protein complexes, we have focused on the concept of modularity, and elucidated the detection power of module extraction algorithms by independent validations based on GO, MIPS and KEGG. From the combination of protein interactions with gene expressions, a confidence scoring scheme has been proposed before proceeding via GO with further classification in permanent and transient modules. Conclusions Disaggregated interactomes are shown to be informative for inferring modularity, thus contributing to perform an effective integrative analysis. Validation of the extracted modules by multiple annotation allows for the assessment of confidence measures assigned to the modules in a protein pathway context. Notably, the proposed multilayer confidence scheme can be used for network calibration by enabling a transition from unweighted to weighted interactomes based on biological evidence.

  19. Arrays of microLEDs and astrocytes: biological amplifiers to optogenetically modulate neuronal networks reducing light requirement.

    Rolando Berlinguer-Palmini

    Full Text Available In the modern view of synaptic transmission, astrocytes are no longer confined to the role of merely supportive cells. Although they do not generate action potentials, they nonetheless exhibit electrical activity and can influence surrounding neurons through gliotransmitter release. In this work, we explored whether optogenetic activation of glial cells could act as an amplification mechanism to optical neural stimulation via gliotransmission to the neural network. We studied the modulation of gliotransmission by selective photo-activation of channelrhodopsin-2 (ChR2 and by means of a matrix of individually addressable super-bright microLEDs (μLEDs with an excitation peak at 470 nm. We combined Ca2+ imaging techniques and concurrent patch-clamp electrophysiology to obtain subsequent glia/neural activity. First, we tested the μLEDs efficacy in stimulating ChR2-transfected astrocyte. ChR2-induced astrocytic current did not desensitize overtime, and was linearly increased and prolonged by increasing μLED irradiance in terms of intensity and surface illumination. Subsequently, ChR2 astrocytic stimulation by broad-field LED illumination with the same spectral profile, increased both glial cells and neuronal calcium transient frequency and sEPSCs suggesting that few ChR2-transfected astrocytes were able to excite surrounding not-ChR2-transfected astrocytes and neurons. Finally, by using the μLEDs array to selectively light stimulate ChR2 positive astrocytes we were able to increase the synaptic activity of single neurons surrounding it. In conclusion, ChR2-transfected astrocytes and μLEDs system were shown to be an amplifier of synaptic activity in mixed corticalneuronal and glial cells culture.

  20. Arrays of microLEDs and astrocytes: biological amplifiers to optogenetically modulate neuronal networks reducing light requirement.

    Berlinguer-Palmini, Rolando; Narducci, Roberto; Merhan, Kamyar; Dilaghi, Arianna; Moroni, Flavio; Masi, Alessio; Scartabelli, Tania; Landucci, Elisa; Sili, Maria; Schettini, Antonio; McGovern, Brian; Maskaant, Pleun; Degenaar, Patrick; Mannaioni, Guido

    2014-01-01

    In the modern view of synaptic transmission, astrocytes are no longer confined to the role of merely supportive cells. Although they do not generate action potentials, they nonetheless exhibit electrical activity and can influence surrounding neurons through gliotransmitter release. In this work, we explored whether optogenetic activation of glial cells could act as an amplification mechanism to optical neural stimulation via gliotransmission to the neural network. We studied the modulation of gliotransmission by selective photo-activation of channelrhodopsin-2 (ChR2) and by means of a matrix of individually addressable super-bright microLEDs (μLEDs) with an excitation peak at 470 nm. We combined Ca2+ imaging techniques and concurrent patch-clamp electrophysiology to obtain subsequent glia/neural activity. First, we tested the μLEDs efficacy in stimulating ChR2-transfected astrocyte. ChR2-induced astrocytic current did not desensitize overtime, and was linearly increased and prolonged by increasing μLED irradiance in terms of intensity and surface illumination. Subsequently, ChR2 astrocytic stimulation by broad-field LED illumination with the same spectral profile, increased both glial cells and neuronal calcium transient frequency and sEPSCs suggesting that few ChR2-transfected astrocytes were able to excite surrounding not-ChR2-transfected astrocytes and neurons. Finally, by using the μLEDs array to selectively light stimulate ChR2 positive astrocytes we were able to increase the synaptic activity of single neurons surrounding it. In conclusion, ChR2-transfected astrocytes and μLEDs system were shown to be an amplifier of synaptic activity in mixed corticalneuronal and glial cells culture.

  1. CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

    Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

    2017-08-31

    Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

  2. SAGE: String-overlap Assembly of GEnomes.

    Ilie, Lucian; Haider, Bahlul; Molnar, Michael; Solis-Oba, Roberto

    2014-09-15

    De novo genome assembly of next-generation sequencing data is one of the most important current problems in bioinformatics, essential in many biological applications. In spite of significant amount of work in this area, better solutions are still very much needed. We present a new program, SAGE, for de novo genome assembly. As opposed to most assemblers, which are de Bruijn graph based, SAGE uses the string-overlap graph. SAGE builds upon great existing work on string-overlap graph and maximum likelihood assembly, bringing an important number of new ideas, such as the efficient computation of the transitive reduction of the string overlap graph, the use of (generalized) edge multiplicity statistics for more accurate estimation of read copy counts, and the improved use of mate pairs and min-cost flow for supporting edge merging. The assemblies produced by SAGE for several short and medium-size genomes compared favourably with those of existing leading assemblers. SAGE benefits from innovations in almost every aspect of the assembly process: error correction of input reads, string-overlap graph construction, read copy counts estimation, overlap graph analysis and reduction, contig extraction, and scaffolding. We hope that these new ideas will help advance the current state-of-the-art in an essential area of research in genomics.

  3. FPGA based data-flow injection module at 10 Gbit/s reading data from network exported storage and using standard protocols

    Lemouzy, B; Garnier, J-C; Neufeld, N

    2011-01-01

    The goal of the LHCb readout upgrade is to accelerate the DAQ to 40 MHz. Such a DAQ system will certainly employ 10 Gigabit or similar technologies and might also need new networking protocols such as a customized, light-weight TCP or more specialized protocols. A test module is being implemented to be integrated in the existing LHCb infrastructure. It is a multiple 10-Gigabit traffic generator, driven by a Stratix IV FPGA, and flexible enough to generate LHCb's raw data packets. Traffic data are either internally generated or read from external storage via the network. We have implemented a light-weight industry standard protocol ATA over Ethernet (AoE) and we present an outlook of using a file-system on these network-exported disk-drivers.

  4. LHCb: FPGA based data-flow injection module at 10 Gbit/s reading data from network exported storage and using standard protocols

    Lemouzy, B; Garnier, J-C

    2010-01-01

    The goal of the LHCb readout upgrade is to speed up the DAQ to 40 MHz. Such a DAQ system will certainly employ 10 Gigabit or similar technologies and might also need new networking protocols such as a customized, light-weight TCP or more specialised protocols. A test module is being implemented, which integrates in the existing LHCb infrastructure. It is a multiple 10-Gigabit traffic generator, driven by a Stratix IV FPGA, which is flexibile enough to either generate LHCb's raw data packets internally or read them from external storage via the network. For reading the data we have implemented a light-weight industry standard protocol ATA over Ethernet (AoE) and we present an outlook of using a filesystem on these network-exported disk-drivers.

  5. FLIC-overlap fermions and topology

    Kamleh, W.; Kusterer, D.J.; Leinweber, D.B.; Williams, A.G.

    2003-01-01

    APE smearing the links in the irrelevant operators of clover fermions (Fat-Link Irrelevant Clover (FLIC) fermions) provides significant improvement in the condition number of the Hermitian-Dirac operator and gives rise to a factor of two savings in computing the overlap operator. This report investigates the effects of using a highly-improved definition of the lattice field-strength tensor F μν in the fermion action, made possible through the use of APE-smeared fat links in the construction of the irrelevant operators. Spurious double-zero crossings in the spectral flow of the Hermitian-Wilson Dirac operator associated with lattice artifacts at the scale of the lattice spacing are removed with FLIC fermions composed with an O(α 4 )-improved lattice field strength tensor. Hence, FLIC-Overlap fermions provide an additional benefit to the overlap formalism: a correct realization of topology in the fermion sector on the lattice

  6. Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine.

    Palma, Jesse; Grossberg, Stephen; Versace, Massimiliano

    2012-01-01

    Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM). Theorems in the 1970's showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP) currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh) can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 ms or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all (WTA) stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners when the network

  7. Persistence and storage of activity patterns in spiking recurrent cortical networks:Modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

    Jesse ePalma

    2012-06-01

    Full Text Available Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM. Theorems in the 1970’s showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 milliseconds or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners

  8. Additional file 5: Figure S1. of Uncovering co-expression gene network modules regulating fruit acidity in diverse apples

    Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Zhong, Gan-Yuan; Xu, Kenong

    2015-01-01

    Analysis of modules Black, Brown, Blue and Yellow. (A) Module eigengene values across the 29 samples, including 17 in Ma_ on left and 12 in mama on right. Samples are represented by the combination of a letter (abbreviated cultivar name) and a number (replicate) (see legends in Fig. 1, 4 for keys). (B) Correlation between module membership (MM) and gene significance (GS) for malate. (PPTX 75 kb)

  9. Chironomidae larvae (Diptera) of Neotropical floodplain: overlap niche in different habitats.

    Butakka, C M M; Ragonha, F H; Takeda, A M

    2014-05-01

    The niche overlap between trophic groups of Chironomidae larvae in different habitats was observed between trophic groups and between different environments in Neotropical floodplain. For the evaluation we used the index of niche overlap (CXY) and analysis of trophic networks, both from the types and amount of food items identified in the larval alimentary canal. In all environments, the larvae fed on mainly organic matter such as plants fragments and algae, but there were many omnivore larvae. Species that have high values of food items occurred in diverse environments as generalists with great overlap niche and those with a low amount of food items with less overlap niche were classified as specialists. The largest number of trophic niche overlap was observed among collector-gatherers in connected floodplain lakes. The lower values of index niche overlap were predators. The similarity in the diet of different taxa in the same niche does not necessarily imply competition between them, but coexistence when the food resource is not scarce in the environment even in partially overlapping niches.

  10. Targeted Memory Reactivation during Sleep Adaptively Promotes the Strengthening or Weakening of Overlapping Memories.

    Oyarzún, Javiera P; Morís, Joaquín; Luque, David; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

    2017-08-09

    System memory consolidation is conceptualized as an active process whereby newly encoded memory representations are strengthened through selective memory reactivation during sleep. However, our learning experience is highly overlapping in content (i.e., shares common elements), and memories of these events are organized in an intricate network of overlapping associated events. It remains to be explored whether and how selective memory reactivation during sleep has an impact on these overlapping memories acquired during awake time. Here, we test in a group of adult women and men the prediction that selective memory reactivation during sleep entails the reactivation of associated events and that this may lead the brain to adaptively regulate whether these associated memories are strengthened or pruned from memory networks on the basis of their relative associative strength with the shared element. Our findings demonstrate the existence of efficient regulatory neural mechanisms governing how complex memory networks are shaped during sleep as a function of their associative memory strength. SIGNIFICANCE STATEMENT Numerous studies have demonstrated that system memory consolidation is an active, selective, and sleep-dependent process in which only subsets of new memories become stabilized through their reactivation. However, the learning experience is highly overlapping in content and thus events are encoded in an intricate network of related memories. It remains to be explored whether and how memory reactivation has an impact on overlapping memories acquired during awake time. Here, we show that sleep memory reactivation promotes strengthening and weakening of overlapping memories based on their associative memory strength. These results suggest the existence of an efficient regulatory neural mechanism that avoids the formation of cluttered memory representation of multiple events and promotes stabilization of complex memory networks. Copyright © 2017 the authors 0270-6474/17/377748-11$15.00/0.

  11. Autism and ADHD: Overlapping and Discriminating Symptoms

    Mayes, Susan Dickerson; Calhoun, Susan L.; Mayes, Rebecca D.; Molitoris, Sarah

    2012-01-01

    Children with ADHD and autism have some similar features, complicating a differential diagnosis. The purpose of our study was to determine the degree to which core ADHD and autistic symptoms overlap in and discriminate between children 2-16 years of age with autism and ADHD. Our study demonstrated that 847 children with autism were easily…

  12. Improving Inversions of the Overlap Operator

    Krieg, S.; Cundy, N.; Eshof, J. van den; Frommer, A.; Lippert, Th.; Schaefer, K.

    2005-01-01

    We present relaxation and preconditioning techniques which accelerate the inversion of the overlap operator by a factor of four on small lattices, with larger gains as the lattice size increases. These improvements can be used in both propagator calculations and dynamical simulations

  13. Electroabsorption modulator laser for cost-effective 40 Gbit/s networks with low drive voltage, chirp and temperature dependence

    Aubin, G.; Seoane, Jorge; Merghem, K.

    2009-01-01

    The performances of a novel low-chirp electroabsorption modulator laser module are presented. Transmission is analysed in standard singlermode fibre at 40 Gbit/s. Propagation without chromatic dispersion compensation up to 2 km exhibits a low penalty variation over a wide temperature range. A pro....... A propagation scheme with compensation leads to negligible impairment at 88 km....

  14. Apparel Research Network (ARN) Apparel Order Processing Module (AOPM). Application Program for Management of Special Measurement Clothing Orders

    1997-09-30

    Screen, abandoning changes. APPAREL ORDER PROCESSING MODULE FIELD USER MANUAL Ordering Official Screens The Ordering Official Screens are provided for...currendy selected Ordering Official will appear on the Ordering Official Information Screen. APPAREL ORDER PROCESSING MODULE FIELD USER MANUAL Ordering Official

  15. New tools to analyze overlapping coding regions.

    Bayegan, Amir H; Garcia-Martin, Juan Antonio; Clote, Peter

    2016-12-13

    Retroviruses transcribe messenger RNA for the overlapping Gag and Gag-Pol polyproteins, by using a programmed -1 ribosomal frameshift which requires a slippery sequence and an immediate downstream stem-loop secondary structure, together called frameshift stimulating signal (FSS). It follows that the molecular evolution of this genomic region of HIV-1 is highly constrained, since the retroviral genome must contain a slippery sequence (sequence constraint), code appropriate peptides in reading frames 0 and 1 (coding requirements), and form a thermodynamically stable stem-loop secondary structure (structure requirement). We describe a unique computational tool, RNAsampleCDS, designed to compute the number of RNA sequences that code two (or more) peptides p,q in overlapping reading frames, that are identical (or have BLOSUM/PAM similarity that exceeds a user-specified value) to the input peptides p,q. RNAsampleCDS then samples a user-specified number of messenger RNAs that code such peptides; alternatively, RNAsampleCDS can exactly compute the position-specific scoring matrix and codon usage bias for all such RNA sequences. Our software allows the user to stipulate overlapping coding requirements for all 6 possible reading frames simultaneously, even allowing IUPAC constraints on RNA sequences and fixing GC-content. We generalize the notion of codon preference index (CPI) to overlapping reading frames, and use RNAsampleCDS to generate control sequences required in the computation of CPI. Moreover, by applying RNAsampleCDS, we are able to quantify the extent to which the overlapping coding requirement in HIV-1 [resp. HCV] contribute to the formation of the stem-loop [resp. double stem-loop] secondary structure known as the frameshift stimulating signal. Using our software, we confirm that certain experimentally determined deleterious HCV mutations occur in positions for which our software RNAsampleCDS and RNAiFold both indicate a single possible nucleotide. We

  16. Detection of protein complex from protein-protein interaction network using Markov clustering

    Ochieng, P J; Kusuma, W A; Haryanto, T

    2017-01-01

    Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

  17. The modular organization of human anatomical brain networks: Accounting for the cost of wiring

    Richard F. Betzel

    2017-02-01

    Full Text Available Brain networks are expected to be modular. However, existing techniques for estimating a network’s modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.

  18. Development of module for neural network identification of attacks on applications and services in multi-cloud platforms

    Parfenov, D. I.; Bolodurina, I. P.

    2018-05-01

    The article presents the results of developing an approach to detecting and protecting against network attacks on the corporate infrastructure deployed on the multi-cloud platform. The proposed approach is based on the combination of two technologies: a softwareconfigurable network and virtualization of network functions. The approach for searching for anomalous traffic is to use a hybrid neural network consisting of a self-organizing Kohonen network and a multilayer perceptron. The study of the work of the prototype of the system for detecting attacks, the method of forming a learning sample, and the course of experiments are described. The study showed that using the proposed approach makes it possible to increase the effectiveness of the obfuscation of various types of attacks and at the same time does not reduce the performance of the network

  19. Overlapping Clinical Features Between NAFLD and Metabolic Syndrome in Children

    Anna Alisi

    2014-05-01

    Full Text Available Non-alcoholic fatty liver disease (NAFLD is a cluster of pathological liver conditions of emerging importance in overweight and obese children. NAFLD is associated with central obesity, insulin resistance, and dyslipidaemia, which are considered to be the main features of metabolic syndrome (MetS. Prevention of the adverse outcomes of NAFLD, as well as the risk of MetS, depends on the identification of genetic background and environmental factors that modulate susceptibility to these diseases. However, several lines of evidence highlight the strong correlation and co-currency of these two chronic diseases, both in children and in adults. In the present review, we provide an overview of the current clinical proofs on the link between NAFLD and MetS in children, with particular focus on all the possible overlapping features that connect them at paediatric age.

  20. On the overlap prescription for lattice regularization of chiral fermions

    Randjbar-Daemi, S; Strathdee, J

    1995-12-01

    Feynman rules for the vacuum amplitude of fermions coupled to external gauge and Higgs fields in a domain wall lattice model are derived using time-dependent perturbation theory. They have a clear and simple structure corresponding to 1-loop vacuum graphs. Their continuum approximations are extracted by isolating the infrared singularities and it is shown that, in each order, they reduce to vacuum contributions for chiral fermions. In this sense the lattice model is seen to constitute a valid regularization of the continuum theory of chiral fermions coupled to weak and slowly varying gauge and Higgs fields. The overlap amplitude, while not gauge invariant, exhibits a well defined (module phase conventions) response to gauge transformations of the background fields. This response reduces in the continuum limit to the expected chiral anomaly, independently of the phase convention. (author). 20 refs.

  1. On the overlap prescription for lattice regularization of chiral fermions

    Randjbar-Daemi, S.; Strathdee, J.

    1995-12-01

    Feynman rules for the vacuum amplitude of fermions coupled to external gauge and Higgs fields in a domain wall lattice model are derived using time-dependent perturbation theory. They have a clear and simple structure corresponding to 1-loop vacuum graphs. Their continuum approximations are extracted by isolating the infrared singularities and it is shown that, in each order, they reduce to vacuum contributions for chiral fermions. In this sense the lattice model is seen to constitute a valid regularization of the continuum theory of chiral fermions coupled to weak and slowly varying gauge and Higgs fields. The overlap amplitude, while not gauge invariant, exhibits a well defined (module phase conventions) response to gauge transformations of the background fields. This response reduces in the continuum limit to the expected chiral anomaly, independently of the phase convention. (author). 20 refs

  2. The FPAX fastbus module

    Barlag, S.; Bouquet, B.; Lavigne, B.; Rypko, J.

    1989-07-01

    The FPAX is a Fastbus module with 4 independent, 2 slave and 2 master, ports on two segments. It operates as a normal master on either segment or as a Block-Mover on both. The processor board is based on a 68020 microprocessor. A local/network switch allows operation as a host or as a normal module on the Fastbus network

  3. On the acoustics of overlapping laughter in conversational speech

    Truong, Khiet Phuong; Trouvain, Jürgen

    The social nature of laughter invites people to laugh together. This joint vocal action often results in overlapping laughter. In this paper, we show that the acoustics of overlapping laughs are different from non-overlapping laughs. We found that overlapping laughs are stronger prosodically marked

  4. Transcriptome analysis of an apple (Malus × domestica) yellow fruit somatic mutation identifies a gene network module highly associated with anthocyanin and epigenetic regulation.

    El-Sharkawy, Islam; Liang, Dong; Xu, Kenong

    2015-12-01

    Using RNA-seq, this study analysed an apple (Malus×domestica) anthocyanin-deficient yellow-skin somatic mutant 'Blondee' (BLO) and its red-skin parent 'Kidd's D-8' (KID), the original name of 'Gala', to understand the molecular mechanisms underlying the mutation. A total of 3299 differentially expressed genes (DEGs) were identified between BLO and KID at four developmental stages and/or between two adjacent stages within BLO and/or KID. A weighted gene co-expression network analysis (WGCNA) of the DEGs uncovered a network module of 34 genes highly correlated (r=0.95, P=9.0×10(-13)) with anthocyanin contents. Although 12 of the 34 genes in the WGCNA module were characterized and known of roles in anthocyanin, the remainder 22 appear to be novel. Examining the expression of ten representative genes in the module in 14 diverse apples revealed that at least eight were significantly correlated with anthocyanin variation. MdMYB10 (MDP0000259614) and MdGST (MDP0000252292) were among the most suppressed module member genes in BLO despite being undistinguishable in their corresponding sequences between BLO and KID. Methylation assay of MdMYB10 and MdGST in fruit skin revealed that two regions (MR3 and MR7) in the MdMYB10 promoter exhibited remarkable differences between BLO and KID. In particular, methylation was high and progressively increased alongside fruit development in BLO while was correspondingly low and constant in KID. The methylation levels in both MR3 and MR7 were negatively correlated with anthocyanin content as well as the expression of MdMYB10 and MdGST. Clearly, the collective repression of the 34 genes explains the loss-of-colour in BLO while the methylation in MdMYB10 promoter is likely causal for the mutation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  5. Apparel Research Network (ARN) Apparel Order Processing Module (AOPM). Application Program for Management of Special Measurement Clothing Orders

    Brekhus, Dennis

    1997-01-01

    ..., to the defense apparel manufacturers. The Apparel Order Processing Module (AOPM) is designed to respond to the critical need for an ability to order clothing expeditiously for military recruits and for other military personnel...

  6. Networking

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  7. Solving Person Re-identification in Non-overlapping Camera using Efficient Gibbs Sampling

    John, V.; Englebienne, G.; Krose, B.; Burghardt, T.; Damen, D.; Mayol-Cuevas, W.; Mirmehdi, M.

    2013-01-01

    This paper proposes a novel probabilistic approach for appearance-based person reidentification in non-overlapping camera networks. It accounts for varying illumination, varying camera gain and has low computational complexity. More specifically, we present a graphical model where we model the

  8. Reactively loaded arrays based on overlapping sub-arrays with flat-top radiation pattern

    Maximidis, R. T.; Smolders, A. B.; Toso, G.; Caratelli, D.

    2017-01-01

    The design of reactively-loaded antenna arrays featuring a pulse-shaped radiation pattern for limited scan-angle applications is presented. The use of the reactive loading allows reducing the complexity of the feeding structure, eliminating the need for complex overlapping beam-forming networks and

  9. Extracting attosecond delays from spectrally overlapping interferograms

    Jordan, Inga; Wörner, Hans Jakob

    2018-02-01

    Attosecond interferometry is becoming an increasingly popular technique for measuring the dynamics of photoionization in real time. Whereas early measurements focused on atomic systems with very simple photoelectron spectra, the technique is now being applied to more complex systems including isolated molecules and solids. The increase in complexity translates into an augmented spectral congestion, unavoidably resulting in spectral overlap in attosecond interferograms. Here, we discuss currently used methods for phase retrieval and introduce two new approaches for determining attosecond photoemission delays from spectrally overlapping photoelectron spectra. We show that the previously used technique, consisting in the spectral integration of the areas of interest, does in general not provide reliable results. Our methods resolve this problem, thereby opening the technique of attosecond interferometry to complex systems and fully exploiting its specific advantages in terms of spectral resolution compared to attosecond streaking.

  10. Optimization of overlap uniformness for ptychography.

    Huang, Xiaojing; Yan, Hanfei; Harder, Ross; Hwu, Yeukuang; Robinson, Ian K; Chu, Yong S

    2014-05-19

    We demonstrate the advantages of imaging with ptychography scans that follow a Fermat spiral trajectory. This scan pattern provides a more uniform coverage and a higher overlap ratio with the same number of scan points over the same area than the presently used mesh and concentric [13] patterns. Under realistically imperfect measurement conditions, numerical simulations show that the quality of the reconstructed image is improved significantly with a Fermat spiral compared with a concentric scan pattern. The result is confirmed by the performance enhancement with experimental data, especially under low-overlap conditions. These results suggest that the Fermat spiral pattern increases the quality of the reconstructed image and tolerance to data with imperfections.

  11. Flavylium network of chemical reactions in confined media: modulation of 3',4',7-trihydroxyflavilium reactions by host-guest interactions with cucurbit[7]uril.

    Basílio, Nuno; Pina, Fernando

    2014-08-04

    In moderately acidic aqueous solutions, flavylium compounds undergo a pH-, and in some cases, light-dependent array of reversible chemical reactions. This network can be described as a single acid-base reaction involving a flavylium cation (acidic form) and a mixture of basic forms (quinoidal base, hemiketal and cis and trans chalcones). The apparent pK'a of the system and the relative mole fractions of the basic forms can be modulated by the interaction with cucurbit[7]uril. The system is studied by using (1) H NMR spectroscopy, UV/Vis spectroscopy, flash photolysis, and steady-state irradiation. Of all the network species, the flavylium cation possesses the highest affinity for cucurbit[7]uril. The rate of interconversion between flavylium cation and the basic species (where trans-chalcone is dominant) is approximately nine times lower inside the cucurbit[7]uril. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Constructing a two bands optical code-division multiple-access network of bipolar optical access codecs using Walsh-coded liquid crystal modulators

    Yen, Chih-Ta; Huang, Jen-Fa; Chih, Ping-En

    2014-08-01

    We propose and experimentally demonstrated the two bands optical code-division multiple-access (OCDMA) network over bipolar Walsh-coded liquid-crystal modulators (LCMs) and driven by green light and red light lasers. Achieving system performance depends on the construction of a decoder that implements a true bipolar correlation using only unipolar signals and intensity detection for each band. We took advantage of the phase delay characteristics of LCMs to construct a prototype optical coder/decoder (codec). Matched and unmatched Walsh signature codes were evaluated to detect correlations among multiuser data in the access network. By using LCMs, a red and green laser light source was spectrally encoded and the summed light dots were complementary decoded. Favorable contrast on auto- and cross-correlations indicates that binary information symbols can be properly recovered using a balanced photodetector.

  13. The overlap between cyberbullying and traditional bullying.

    Waasdorp, Tracy E; Bradshaw, Catherine P

    2015-05-01

    Cyberbullying appears to be on the rise among adolescents due in part to increased access to electronic devices and less online supervision. Less is known about how cyberbullying differs from traditional bullying which occurs in person and the extent to which these two forms overlap. Our first aim was to examine the overlap of traditional bullying (relational, verbal, and physical) with cyberbullying. The second aim examined student- and school-level correlates of cyber victimization as compared to traditional victims. The final aim explored details of the cyberbullying experience (e.g., who sent the message, how was the message sent, and what was the message about). Data came from 28,104 adolescents (grades, 9-12) attending 58 high schools. Approximately 23% of the youth reported being victims of any form of bullying (cyber, relational, physical, and verbal) within the last month, with 25.6% of those victims reporting being cyberbullied. The largest proportion (50.3%) of victims reported they were victimized by all four forms, whereas only 4.6% reported being only cyberbullied. Multilevel analyses indicated that as compared to those who were only traditionally bullied, those who were cyberbullied were more likely to have externalizing (odds ratio = 1.44) and internalizing symptoms (odds ratio = 1.25). Additional analyses examined detailed characteristics of the cyberbullying experiences, indicating a relatively high level of overlap between cyber and traditional bullying. Implications for preventive interventions targeting youth involved with cyberbullying and its overlap with other forms of bullying are discussed. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  14. Vacuum structure as seen by overlap fermions

    Ilgenfritz, E.M.

    2006-11-01

    Three complementary views on the QCD vacuum structure, all based on eigenmodes of the overlap operator, are reported in their interrelation: (i) spectral density, localization and chiral properties of the modes, (ii) the possibility of filtering the field strength with the aim to detect selfdual and antiselfdual domains and (iii) the various faces of the topological charge density, with and without a cutoff λ cut = O(Λ QCD ). The techniques are tested on quenched SU(3) configurations. (orig.)

  15. A module of human peripheral blood mononuclear cell transcriptional network containing primitive and differentiation markers is related to specific cardiovascular health variables.

    Leni Moldovan

    Full Text Available Peripheral blood mononuclear cells (PBMCs, including rare circulating stem and progenitor cells (CSPCs, have important yet poorly understood roles in the maintenance and repair of blood vessels and perfused organs. Our hypothesis was that the identities and functions of CSPCs in cardiovascular health could be ascertained by analyzing the patterns of their co-expressed markers in unselected PBMC samples. Because gene microarrays had failed to detect many stem cell-associated genes, we performed quantitative real-time PCR to measure the expression of 45 primitive and tissue differentiation markers in PBMCs from healthy and hypertensive human subjects. We compared these expression levels to the subjects' demographic and cardiovascular risk factors, including vascular stiffness. The tested marker genes were expressed in all of samples and organized in hierarchical transcriptional network modules, constructed by a bottom-up approach. An index of gene expression in one of these modules (metagene, defined as the average standardized relative copy numbers of 15 pluripotency and cardiovascular differentiation markers, was negatively correlated (all p<0.03 with age (R2 = -0.23, vascular stiffness (R2 = -0.24, and central aortic pressure (R2 = -0.19 and positively correlated with body mass index (R2 = 0.72, in women. The co-expression of three neovascular markers was validated at the single-cell level using mRNA in situ hybridization and immunocytochemistry. The overall gene expression in this cardiovascular module was reduced by 72±22% in the patients compared with controls. However, the compactness of both modules was increased in the patients' samples, which was reflected in reduced dispersion of their nodes' degrees of connectivity, suggesting a more primitive character of the patients' CSPCs. In conclusion, our results show that the relationship between CSPCs and vascular function is encoded in modules of the PBMCs transcriptional

  16. Fresh Prime Codes Evaluation for Synchronous PPM and OPPM Signaling for Optical CDMA Networks

    Karbassian, M. Massoud; Ghafouri-Shiraz, H.

    2007-06-01

    In this paper, we have proposed a novel prime spreading sequence family hereby referred to as “Double-Padded Modified Prime Code (DPMPC)” for direct-detection synchronous optical code-division multiple-access (OCDMA) networks. The new code is applied to both pulse-position and overlapping pulse-position modulation CDMA networks, and their performances were evaluated and compared with existing prime codes family. In addition, we have analyzed the system throughput and also introduced a new interference cancellation technique which significantly improves the bit error probability of OCDMA networks.

  17. Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

    Xiao, Xiaolin; Moreno-Moral, Aida; Rotival, Maxime; Bottolo, Leonardo; Petretto, Enrico

    2014-01-01

    Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co

  18. Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

    Xiaolin Xiao

    2014-01-01

    Full Text Available Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states. Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based and humans (mRNA-sequencing-based and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi

  19. Overlapping neural systems represent cognitive effort and reward anticipation.

    Vassena, Eliana; Silvetti, Massimo; Boehler, Carsten N; Achten, Eric; Fias, Wim; Verguts, Tom

    2014-01-01

    Anticipating a potential benefit and how difficult it will be to obtain it are valuable skills in a constantly changing environment. In the human brain, the anticipation of reward is encoded by the Anterior Cingulate Cortex (ACC) and Striatum. Naturally, potential rewards have an incentive quality, resulting in a motivational effect improving performance. Recently it has been proposed that an upcoming task requiring effort induces a similar anticipation mechanism as reward, relying on the same cortico-limbic network. However, this overlapping anticipatory activity for reward and effort has only been investigated in a perceptual task. Whether this generalizes to high-level cognitive tasks remains to be investigated. To this end, an fMRI experiment was designed to investigate anticipation of reward and effort in cognitive tasks. A mental arithmetic task was implemented, manipulating effort (difficulty), reward, and delay in reward delivery to control for temporal confounds. The goal was to test for the motivational effect induced by the expectation of bigger reward and higher effort. The results showed that the activation elicited by an upcoming difficult task overlapped with higher reward prospect in the ACC and in the striatum, thus highlighting a pivotal role of this circuit in sustaining motivated behavior.

  20. Finding Hierarchical and Overlapping Dense Subgraphs using Nucleus Decompositions

    Seshadhri, Comandur [The Ohio State Univ., Columbus, OH (United States); Pinar, Ali [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sariyuce, Ahmet Erdem [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Catalyurek, Umit [The Ohio State Univ., Columbus, OH (United States)

    2014-11-01

    Finding dense substructures in a graph is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasiclique, k-densest subgraph) are NP-hard. Furthermore, the goal is rarely to nd the \\true optimum", but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine a hierarchical structure among them. Current dense subgraph nding algorithms usually optimize some objective, and only nd a few such subgraphs without providing any hierarchy. It is also not clear how to account for overlaps in dense substructures. We de ne the nucleus decomposition of a graph, which represents the graph as a forest of nuclei. Each nucleus is a subgraph where smaller cliques are present in many larger cliques. The forest of nuclei is a hierarchy by containment, where the edge density increases as we proceed towards leaf nuclei. Sibling nuclei can have limited intersections, which allows for discovery of overlapping dense subgraphs. With the right parameters, the nuclear decomposition generalizes the classic notions of k-cores and k-trusses. We give provable e cient algorithms for nuclear decompositions, and empirically evaluate their behavior in a variety of real graphs. The tree of nuclei consistently gives a global, hierarchical snapshot of dense substructures, and outputs dense subgraphs of higher quality than other state-of-theart solutions. Our algorithm can process graphs with tens of millions of edges in less than an hour.

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

    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.

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

    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)

  3. Human tracking over camera networks: a review

    Hou, Li; Wan, Wanggen; Hwang, Jenq-Neng; Muhammad, Rizwan; Yang, Mingyang; Han, Kang

    2017-12-01

    In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and health care. This review paper surveys the most widely used techniques and recent advances for human tracking over camera networks. Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across non-overlapping cameras. The core techniques of human tracking within a camera are discussed based on two aspects, i.e., generative trackers and discriminative trackers. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking and graph model-based tracking. Our survey aims to address existing problems, challenges, and future research directions based on the analyses of the current progress made toward human tracking techniques over camera networks.

  4. Small-Molecule Inhibition of Rho/MKL/SRF Transcription in Prostate Cancer Cells: Modulation of Cell Cycle, ER Stress, and Metastasis Gene Networks

    Chris R. Evelyn

    2016-05-01

    Full Text Available Metastasis is the major cause of cancer deaths and control of gene transcription has emerged as a critical contributing factor. RhoA- and RhoC-induced gene transcription via the actin-regulated transcriptional co-activator megakaryocytic leukemia (MKL and serum response factor (SRF drive metastasis in breast cancer and melanoma. We recently identified a compound, CCG-1423, which blocks Rho/MKL/SRF-mediated transcription and inhibits PC-3 prostate cancer cell invasion. Here, we undertook a genome-wide expression study in PC-3 cells to explore the mechanism and function of this compound. There was significant overlap in the genes modulated by CCG-1423 and Latrunculin B (Lat B, which blocks the Rho/MKL/SRF pathway by preventing actin polymerization. In contrast, the general transcription inhibitor 5,6-dichloro-1-β-d-ribofuranosyl-1H-benzimidazole (DRB showed a markedly different pattern. Effects of CCG-1423 and Lat B on gene expression correlated with literature studies of MKL knock-down. Gene sets involved in DNA synthesis and repair, G1/S transition, and apoptosis were modulated by CCG-1423. It also upregulated genes involved in endoplasmic reticulum stress. Targets of the known Rho target transcription factor family E2F and genes related to melanoma progression and metastasis were strongly suppressed by CCG-1423. These results confirm the ability of our compound to inhibit expression of numerous Rho/MKL-dependent genes and show effects on stress pathways as well. This suggests a novel approach to targeting aggressive cancers and metastasis.

  5. Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations

    Proddutur, Archana; Yu, Jiandong; Elgammal, Fatima S. [Department of Neurology and Neurosciences, New Jersey Medical School, Rutgers, Newark, New Jersey 07103 (United States); Santhakumar, Vijayalakshmi, E-mail: santhavi@njms.rutgers.edu [Department of Neurology and Neurosciences, New Jersey Medical School, Rutgers, Newark, New Jersey 07103 (United States); Department of Pharmacology and Physiology, New Jersey Medical School, Rutgers, Newark, New Jersey 07103 (United States)

    2013-12-15

    FS-BC frequency when E{sub GABA} was depolarizing (−54 mV). When FS-BCs were activated by biologically based dendritic synaptic inputs, enhancing g{sub GABA-extra} reduced the frequency and coherence of FS-BC firing when E{sub GABA} was shunting and increased average FS-BC firing when E{sub GABA} was depolarizing. Shifting E{sub GABA} from shunting to depolarizing potentials consistently increased network frequency to and above high gamma frequencies (>80 Hz). Since gamma oscillations may contribute to learning and memory processing [Fell et al., Nat. Neurosci. 4, 1259 (2001); Jutras et al., J. Neurosci. 29, 12521 (2009); Wang, Physiol. Rev. 90, 1195 (2010)], our demonstration that network oscillations are modulated by extrasynaptic inhibition in FS-BCs suggests that neuroactive compounds that act on extrasynaptic GABA receptors could impact memory formation by modulating hippocampal gamma oscillations. The simulation results indicate that the depolarized FS-BC GABA reversal, observed after experimental seizures, together with enhanced spillover extrasynaptic GABA currents are likely to promote generation of focal high frequency activity associated with epileptic networks.

  6. Seizure-induced alterations in fast-spiking basket cell GABA currents modulate frequency and coherence of gamma oscillation in network simulations

    Proddutur, Archana; Yu, Jiandong; Elgammal, Fatima S.; Santhakumar, Vijayalakshmi

    2013-01-01

    was depolarizing (−54 mV). When FS-BCs were activated by biologically based dendritic synaptic inputs, enhancing g GABA-extra reduced the frequency and coherence of FS-BC firing when E GABA was shunting and increased average FS-BC firing when E GABA was depolarizing. Shifting E GABA from shunting to depolarizing potentials consistently increased network frequency to and above high gamma frequencies (>80 Hz). Since gamma oscillations may contribute to learning and memory processing [Fell et al., Nat. Neurosci. 4, 1259 (2001); Jutras et al., J. Neurosci. 29, 12521 (2009); Wang, Physiol. Rev. 90, 1195 (2010)], our demonstration that network oscillations are modulated by extrasynaptic inhibition in FS-BCs suggests that neuroactive compounds that act on extrasynaptic GABA receptors could impact memory formation by modulating hippocampal gamma oscillations. The simulation results indicate that the depolarized FS-BC GABA reversal, observed after experimental seizures, together with enhanced spillover extrasynaptic GABA currents are likely to promote generation of focal high frequency activity associated with epileptic networks

  7. Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

    Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

    2017-11-13

    The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly

  8. Birth and death of gene overlaps in vertebrates

    Makałowska Izabela

    2007-10-01

    Full Text Available Abstract Background Between five and fourteen per cent of genes in the vertebrate genomes do overlap sharing some intronic and/or exonic sequence. It was observed that majority of these overlaps are not conserved among vertebrate lineages. Although several mechanisms have been proposed to explain gene overlap origination the evolutionary basis of these phenomenon are still not well understood. Here, we present results of the comparative analysis of several vertebrate genomes. The purpose of this study was to examine overlapping genes in the context of their evolution and mechanisms leading to their origin. Results Based on the presence and arrangement of human overlapping genes orthologs in rodent and fish genomes we developed 15 theoretical scenarios of overlapping genes evolution. Analysis of these theoretical scenarios and close examination of genomic sequences revealed new mechanisms leading to the overlaps evolution and confirmed that many of the vertebrate gene overlaps are not conserved. This study also demonstrates that repetitive elements contribute to the overlapping genes origination and, for the first time, that evolutionary events could lead to the loss of an ancient overlap. Conclusion Birth as well as most probably death of gene overlaps occurred over the entire time of vertebrate evolution and there wasn't any rapid origin or 'big bang' in the course of overlapping genes evolution. The major forces in the gene overlaps origination are transposition and exaptation. Our results also imply that origin of overlapping genes is not an issue of saving space and contracting genomes size.

  9. xHeinz: an algorithm for mining cross-species network modules under a flexible conservation model

    El-Kebir, Mohammed; Soueidan, Hayssam; Hume, Thomas; Beisser, Daniela; Dittrich, Marcus; Müller, Tobias; Blin, Guillaume; Heringa, Jaap; Nikolski, Macha; Wessels, Lodewyk F.A.; Klau, G.W.

    2015-01-01

    Motivation: Integrative network analysis methods provide robust interpretations of differential high-throughput molecular profile measurements. They are often used in a biomedical context - to generate novel hypotheses about the underlying cellular processes or to derive biomarkers for

  10. The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness

    Huskey, Richard; Mangus, J Michael; Turner, Benjamin O; Weber, René

    2017-01-01

    Abstract While a persuasion network has been proposed, little is known about how network connections between brain regions contribute to attitude change. Two possible mechanisms have been advanced. One hypothesis predicts that attitude change results from increased connectivity between structures implicated in affective and executive processing in response to increases in argument strength. A second functional perspective suggests that highly arousing messages reduce connectivity between stru...

  11. Influence of slice overlap on positron emission tomography image quality

    McKeown, Clare; Gillen, Gerry; Dempsey, Mary Frances; Findlay, Caroline

    2016-01-01

    PET scans use overlapping acquisition beds to correct for reduced sensitivity at bed edges. The optimum overlap size for the General Electric (GE) Discovery 690 has not been established. This study assesses how image quality is affected by slice overlap. Efficacy of 23% overlaps (recommended by GE) and 49% overlaps (maximum possible overlap) were specifically assessed. European Association of Nuclear Medicine (EANM) guidelines for calculating minimum injected activities based on overlap size were also reviewed. A uniform flood phantom was used to assess noise (coefficient of variation, (COV)) and voxel accuracy (activity concentrations, Bq ml −1 ). A NEMA (National Electrical Manufacturers Association) body phantom with hot/cold spheres in a background activity was used to assess contrast recovery coefficients (CRCs) and signal to noise ratios (SNR). Different overlap sizes and sphere-to-background ratios were assessed. COVs for 49% and 23% overlaps were 9% and 13% respectively. This increased noise was difficult to visualise on the 23% overlap images. Mean voxel activity concentrations were not affected by overlap size. No clinically significant differences in CRCs were observed. However, visibility and SNR of small, low contrast spheres (⩽13 mm diameter, 2:1 sphere to background ratio) may be affected by overlap size in low count studies if they are located in the overlap area. There was minimal detectable influence on image quality in terms of noise, mean activity concentrations or mean CRCs when comparing 23% overlap with 49% overlap. Detectability of small, low contrast lesions may be affected in low count studies—however, this is a worst-case scenario. The marginal benefits of increasing overlap from 23% to 49% are likely to be offset by increased patient scan times. A 23% overlap is therefore appropriate for clinical use. An amendment to EANM guidelines for calculating injected activities is also proposed which better reflects the effect overlap size

  12. Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

    Zhang, Zhen; Ma, Cheng; Zhu, Rong

    2016-10-14

    High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

  13. Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules

    Zhen Zhang

    2016-10-01

    Full Text Available High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial–temporal complexity. This paper presents a multi-input multi-output (MIMO self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional–integral–derivative (PID neural network (FCPIDNN and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

  14. Protein Networks in Alzheimer's Disease

    Carlsen, Eva Meier; Rasmussen, Rune

    2017-01-01

    Overlap of RNA and protein networks reveals glia cells as key players for the development of symptomatic Alzheimer’s disease in humans......Overlap of RNA and protein networks reveals glia cells as key players for the development of symptomatic Alzheimer’s disease in humans...

  15. Development and Comparative Study of Effects of Training Algorithms on Performance of Artificial Neural Network Based Analog and Digital Automatic Modulation Recognition

    Jide Julius Popoola

    2015-11-01

    Full Text Available This paper proposes two new classifiers that automatically recognise twelve combined analog and digital modulated signals without any a priori knowledge of the modulation schemes and the modulation parameters. The classifiers are developed using pattern recognition approach. Feature keys extracted from the instantaneous amplitude, instantaneous phase and the spectrum symmetry of the simulated signals are used as inputs to the artificial neural network employed in developing the classifiers. The two developed classifiers are trained using scaled conjugate gradient (SCG and conjugate gradient (CONJGRAD training algorithms. Sample results of the two classifiers show good success recognition performance with an average overall recognition rate above 99.50% at signal-to-noise ratio (SNR value from 0 dB and above with the two training algorithms employed and an average overall recognition rate slightly above 99.00% and 96.40% respectively at - 5 dB SNR value for SCG and CONJGRAD training algorithms. The comparative performance evaluation of the two developed classifiers using the two training algorithms shows that the two training algorithms have different effects on both the response rate and efficiency of the two developed artificial neural networks classifiers. In addition, the result of the performance evaluation carried out on the overall success recognition rates between the two developed classifiers in this study using pattern recognition approach with the two training algorithms and one reported classifier in surveyed literature using decision-theoretic approach shows that the classifiers developed in this study perform favourably with regard to accuracy and performance probability as compared to classifier presented in previous study.

  16. Granular neural networks, pattern recognition and bioinformatics

    Pal, Sankar K; Ganivada, Avatharam

    2017-01-01

    This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinf...

  17. Novel overlapping coding sequences in Chlamydia trachomatis

    Jensen, Klaus Thorleif; Petersen, Lise; Falk, Søren

    2006-01-01

    that are in agreement with the primary annotation. Forty two genes from the primary annotation are not predicted by EasyGene. The majority of these genes are listed as hypothetical in the primary annotation. The 15 novel predicted genes all overlap with genes on the complementary strand. We find homologues of several...... of the novel genes in C. trachomatis Serovar A and Chlamydia muridarum. Several of the genes have typical gene-like and protein-like features. Furthermore, we confirm transcriptional activity from 10 of the putative genes. The combined evidence suggests that at least seven of the 15 are protein coding genes...

  18. Overlapping constraint for variational surface reconstruction

    Aanæs, Henrik; Solem, J.E.

    2005-01-01

    In this paper a counter example, illustrating a shortcoming in most variational formulations for 3D surface estimation, is presented. The nature of this shortcoming is a lack of an overlapping constraint. A remedy for this shortcoming is presented in the form of a penalty function with an analysi...... of the effects of this function on surface motion. For practical purposes, this will only have minor influence on current methods. However, the insight provided in the analysis is likely to influence future developments in the field of variational surface reconstruction....

  19. Technology initiatives with government/business overlap

    Knapp, Robert H., Jr.

    2015-03-01

    Three important present-day technology development settings involve significant overlap between government and private sectors. The Advanced Research Project Agency for Energy (ARPA-E) supports a wide range of "high risk, high return" projects carried out in academic, non-profit or private business settings. The Materials Genome Initiative (MGI), based in the White House, aims at radical acceleration of the development process for advanced materials. California public utilities such as Pacific Gas & Electric operate under a structure of financial returns and political program mandates that make them arms of public policy as much as independent businesses.

  20. Reconfigurable Digital Coherent Receiver for Metro-Access Networks Supporting Mixed Modulation Formats and Bit-rates

    Caballero Jambrina, Antonio; Guerrero Gonzalez, Neil; Arlunno, Valeria

    2013-01-01

    A single, reconfigurable, digital coherent receiver is proposed and experimentally demonstrated for converged wireless and optical fiber transport. The capacity of reconstructing the full transmitted optical field allows for the demodulation of mixed modulation formats and bit-rates. We performed...

  1. Emotional and cognitive processing of narratives and individual appraisal styles: recruitment of cognitive control networks vs. modulation of deactivations

    Enrico eBenelli

    2012-08-01

    Full Text Available Research in psychotherapy has shown that the frequency of use of specific classes of words (such as terms with emotional valence in descriptions of scenes of affective relevance is a possible indicator of psychological affective functioning. Using functional magnetic resonance imaging, we investigated the neural correlates of these linguistic markers in narrative texts depicting core aspects of emotional experience in human interaction, and their modulation by individual differences in the propensity to use these markers. Emotional words activated both lateral and medial aspects of the prefrontal cortex, as in previous studies of instructed emotion regulation and in consistence with recruitment of effortful control processes. However, individual differences in the spontaneous use of emotional terms in characterizing the stimulus material were prevalently associated with modulation of the signal in the perigenual cortex, in the retrosplenial cortex and precuneus, and the anterior insula/ventrolateral prefrontal cortex. Modulation of signal by the presence of these textual markers or individual differences mostly involved areas deactivated by the main task, thus further differentiating neural correlates of these appraisal styles from those associated with effortful control. These findings are discussed in the context of reports in the literature of modulations of deactivations, which suggest their importance in orienting attention and generation of response in the presence of emotional information. These findings suggest that deactivations may play a functional role in emotional appraisal and may contribute to characterizing different appraisal styles.

  2. Accessing the mental space - Spatial working memory processes for language and vision overlap in precuneus

    Wallentin, Mikkel; Weed, Ethan; Østergaard, Leif

    2008-01-01

    , strikingly overlapping a network previously shown to be involved in recall of spatial aspects of images depicting similar scenarios. This supports a neurocognitive model of language function, where sentences establish meaning by interacting with the perceptual and working memory networks of the brain.......Abstract: The ‘‘overlapping systems'' theory of language function argues that linguistic meaning construction crucially relies on contextual information provided by ‘‘nonlinguistic'' cognitive systems, such as perception and memory. This study examines whether linguistic processing of spatial.......g., ‘‘Was he turned towards her?'') and equally concrete nonspatial content (e.g., ‘‘Was he older than her?''). We found that recall of the spatial content relative to the nonspatial content resulted in higher BOLD response in a dorsoposterior network of brain regions, most significantly in precuneus...

  3. Visibility graphs for fMRI data: Multiplex temporal graphs and their modulations across resting-state networks

    Speranza Sannino

    2017-10-01

    Full Text Available Visibility algorithms are a family of methods that map time series into graphs, such that the tools of graph theory and network science can be used for the characterization of time series. This approach has proved a convenient tool, and visibility graphs have found applications across several disciplines. Recently, an approach has been proposed to extend this framework to multivariate time series, allowing a novel way to describe collective dynamics. Here we test their application to fMRI time series, following two main motivations, namely that (a this approach allows vs to simultaneously capture and process relevant aspects of both local and global dynamics in an easy and intuitive way, and (b this provides a suggestive bridge between time series and network theory that nicely fits the consolidating field of network neuroscience. Our application to a large open dataset reveals differences in the similarities of temporal networks (and thus in correlated dynamics across resting-state networks, and gives indications that some differences in brain activity connected to psychiatric disorders could be picked up by this approach. Here we present the first application of multivariate visibility graphs to fMRI data. Visibility graphs are a way to represent a time series as a temporal network, evidencing specific aspects of its dynamics, such as extreme events. Multivariate time series, as those encountered in neuroscience, and in fMRI in particular, can be seen as a multiplex network, in which each layer represents a time series (a region of interest in the brain in our case. Here we report the method, we describe some relevant aspects of its application to BOLD time series, and we discuss the analogies and differences with existing methods. Finally, we present an application to a high-quality, publicly available dataset, containing healthy subjects and psychotic patients, and we discuss our findings. All the code to reproduce the analyses and the

  4. The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness

    Mangus, J Michael; Turner, Benjamin O

    2017-01-01

    Abstract While a persuasion network has been proposed, little is known about how network connections between brain regions contribute to attitude change. Two possible mechanisms have been advanced. One hypothesis predicts that attitude change results from increased connectivity between structures implicated in affective and executive processing in response to increases in argument strength. A second functional perspective suggests that highly arousing messages reduce connectivity between structures implicated in the encoding of sensory information, which disrupts message processing and thereby inhibits attitude change. However, persuasion is a multi-determined construct that results from both message features and audience characteristics. Therefore, persuasive messages should lead to specific functional connectivity patterns among a priori defined structures within the persuasion network. The present study exposed 28 subjects to anti-drug public service announcements where arousal, argument strength, and subject drug-use risk were systematically varied. Psychophysiological interaction analyses provide support for the affective-executive hypothesis but not for the encoding-disruption hypothesis. Secondary analyses show that video-level connectivity patterns among structures within the persuasion network predict audience responses in independent samples (one college-aged, one nationally representative). We propose that persuasion neuroscience research is best advanced by considering network-level effects while accounting for interactions between message features and target audience characteristics. PMID:29140500

  5. The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness.

    Huskey, Richard; Mangus, J Michael; Turner, Benjamin O; Weber, René

    2017-12-01

    While a persuasion network has been proposed, little is known about how network connections between brain regions contribute to attitude change. Two possible mechanisms have been advanced. One hypothesis predicts that attitude change results from increased connectivity between structures implicated in affective and executive processing in response to increases in argument strength. A second functional perspective suggests that highly arousing messages reduce connectivity between structures implicated in the encoding of sensory information, which disrupts message processing and thereby inhibits attitude change. However, persuasion is a multi-determined construct that results from both message features and audience characteristics. Therefore, persuasive messages should lead to specific functional connectivity patterns among a priori defined structures within the persuasion network. The present study exposed 28 subjects to anti-drug public service announcements where arousal, argument strength, and subject drug-use risk were systematically varied. Psychophysiological interaction analyses provide support for the affective-executive hypothesis but not for the encoding-disruption hypothesis. Secondary analyses show that video-level connectivity patterns among structures within the persuasion network predict audience responses in independent samples (one college-aged, one nationally representative). We propose that persuasion neuroscience research is best advanced by considering network-level effects while accounting for interactions between message features and target audience characteristics. © The Author (2017). Published by Oxford University Press.

  6. Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males.

    Deza Araujo, Yacila I; Nebe, Stephan; Neukam, Philipp T; Pooseh, Shakoor; Sebold, Miriam; Garbusow, Maria; Heinz, Andreas; Smolka, Michael N

    2018-06-01

    Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.

  7. A Novel Adaptive Modulation Based on Nondata-Aided Error Vector Magnitude in Non-Line-Of-Sight Condition of Wireless Sensor Network.

    Yang, Fan; Zeng, Xiaoping; Mao, Haiwei; Jian, Xin; Tan, Xiaoheng; Du, Derong

    2018-01-15

    The high demand for multimedia applications in environmental monitoring, invasion detection, and disaster aid has led to the rise of wireless sensor network (WSN). With the increase of reliability and diversity of information streams, the higher requirements on throughput and quality of service (QoS) have been put forward in data transmission between two sensor nodes. However, lower spectral efficiency becomes a bottleneck in non-line-of-sight (NLOS) transmission of WSN. This paper proposes a novel nondata-aided error vector magnitude based adaptive modulation (NDA-EVM-AM) to solve the problem. NDA-EVM is considered as a new metric to evaluate the quality of NLOS link for adaptive modulation in WSN. By modeling the NLOS scenario as the η - μ fading channel, a closed-form expression for the NDA-EVM of multilevel quadrature amplitude modulation (MQAM) signals over the η - μ fading channel is derived, and the relationship between SER and NDA-EVM is also formulated. Based on these results, NDA-EVM state machine is designed for adaptation strategy. The algorithmic complexity of NDA-EVM-AM is analyzed and the outage capacity of NDA-EVM-AM in an NLOS scenario is also given. The performances of NDA-EVM-AM are compared by simulation, and the results show that NDA-EVM-AM is an effective technique to be used in the NLOS scenarios of WSN. This technique can accurately reflect the channel variations and efficiently adjust modulation order to better match the channel conditions, hence, obtaining better performance in average spectral efficiency.

  8. Hypochondriasis and panic disorder. Boundary and overlap.

    Barsky, A J; Barnett, M C; Cleary, P D

    1994-11-01

    To determine the nosological and phenomenological overlap and boundaries between panic disorder and hypochondriasis, we compared the symptoms, disability, comorbidity, and medical care of primary care patients with each diagnosis. Patients with DSM-III-R panic disorder were recruited by screening consecutive primary care clinic attenders and then administering a structured diagnostic interview for panic disorder. Patients also completed self-report questionnaires, and their primary care physicians completed questionnaires about them. They were then compared with patients with DSM-III-R hypochondriasis from the same setting who had been studied previously. One thousand six hundred thirty-four patients were screened; 135 (71.0% of the 190 eligible patients) completed the research battery; 100 met lifetime panic disorder criteria. Twenty-five of these had comorbid hypochondriasis. Those without comorbid hypochondriasis (n = 75) were then compared with patients with hypochondriasis without comorbid panic disorder (n = 51). Patients with panic disorder were less hypochondriacal (P somatized less (P somatization disorder symptoms (P hypochondriasis. While hypochondriasis and panic disorder co-occur to some extent in a primary care population, the overlap is by no means complete. These patients are phenomenologically and functionally differentiable and distinct and are viewed differently by their primary care physicians.

  9. Symptom overlap in anxiety and multiple sclerosis.

    O Donnchadha, Seán

    2013-02-14

    BACKGROUND: The validity of self-rated anxiety inventories in people with multiple sclerosis (pwMS) is unclear. However, the appropriateness of self-reported depression scales has been widely examined. Given somatic symptom overlap between depression and MS, research emphasises caution when using such scales. OBJECTIVE: This study evaluates symptom overlap between anxiety and MS in a group of 33 individuals with MS, using the Beck Anxiety Inventory (BAI). METHODS: Participants underwent a neurological examination and completed the BAI. RESULTS: A novel procedure using hierarchical cluster analysis revealed three distinct symptom clusters. Cluster one (\\'wobbliness\\' and \\'unsteady\\') grouped separately from all other BAI items. These symptoms are well-recognised MS-related symptoms and we question whether their endorsement in pwMS can be considered to reflect anxiety. A modified 19-item BAI (mBAI) was created which excludes cluster one items. This removal reduced the number of MS participants considered \\'anxious\\' by 21.21% (low threshold) and altered the level of anxiety severity for a further 27.27%. CONCLUSION: Based on these data, it is suggested that, as with depression measures, researchers and clinicians should exercise caution when using brief screening measures for anxiety in pwMS.

  10. Activation of words with phonological overlap

    Claudia K. Friedrich

    2013-08-01

    Full Text Available Multiple lexical representations overlapping with the input (cohort neighbors are temporarily activated in the listener’s mental lexicon when speech unfolds in time. Activation for cohort neighbors appears to rapidly decline as soon as there is mismatch with the input. However, it is a matter of debate whether or not they are completely excluded from further processing. We recorded behavioral data and event-related brain potentials (ERPs in auditory-visual word onset priming during a lexical decision task. As primes we used the first two syllables of spoken German words. In a carrier word condition, the primes were extracted from spoken versions of the target words (ano-ANORAK 'anorak'. In a cohort neighbor condition, the primes were taken from words that overlap with the target word up to the second nucleus (ana- taken from ANANAS 'pineapple'. Relative to a control condition, where primes and targets were unrelated, lexical decision responses for cohort neighbors were delayed. This reveals that cohort neighbors are disfavored by the decision processes at the behavioral front end. In contrast, left-anterior ERPs reflected long-lasting facilitated processing of cohort neighbors. We interpret these results as evidence for extended parallel processing of cohort neighbors. That is, in parallel to the preparation and elicitation of delayed lexical decision responses to cohort neighbors, aspects of the processing system appear to keep track of those less efficient candidates.

  11. Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis

    Zhou X

    2018-05-01

    Full Text Available Xian-guo Zhou,1,2,* Xiao-liang Huang,1,2,* Si-yuan Liang,1–3 Shao-mei Tang,1,2 Si-kao Wu,1,2 Tong-tong Huang,1,2 Zeng-nan Mo,1,2,4 Qiu-yan Wang1,2,5 1Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 2Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 3Department of Colorectal Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 4Department of Urology and Nephrology, The First Affiliated Hospital of Guangxi, Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China; 5Guangxi Colleges and Universities Key Laboratory of Biological Molecular Medicine Research, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China *These authors contributed equally to this work Introduction: Colorectal cancer (CRC is the fourth most common cause of cancer-related mortality worldwide. The tumor, node, metastasis (TNM stage remains the standard for CRC prognostication. Identification of meaningful microRNA (miRNA and gene modules or representative biomarkers related to the pathological stage of colon cancer helps to predict prognosis and reveal the mechanisms behind cancer progression.Materials and methods: We applied a systems biology approach by combining differential expression analysis and weighted gene co-expression network analysis (WGCNA to detect the pathological stage-related miRNA and gene modules and construct a miRNA–gene network. The Cancer Genome Atlas (TCGA colon adenocarcinoma (CAC RNA-sequencing data and miRNA-sequencing data were subjected to WGCNA analysis, and the GSE29623, GSE35602 and GSE39396 were utilized to validate and

  12. Superharmonic imaging with chirp coded excitation: filtering spectrally overlapped harmonics.

    Harput, Sevan; McLaughlan, James; Cowell, David M J; Freear, Steven

    2014-11-01

    Superharmonic imaging improves the spatial resolution by using the higher order harmonics generated in tissue. The superharmonic component is formed by combining the third, fourth, and fifth harmonics, which have low energy content and therefore poor SNR. This study uses coded excitation to increase the excitation energy. The SNR improvement is achieved on the receiver side by performing pulse compression with harmonic matched filters. The use of coded signals also introduces new filtering capabilities that are not possible with pulsed excitation. This is especially important when using wideband signals. For narrowband signals, the spectral boundaries of the harmonics are clearly separated and thus easy to filter; however, the available imaging bandwidth is underused. Wideband excitation is preferable for harmonic imaging applications to preserve axial resolution, but it generates spectrally overlapping harmonics that are not possible to filter in time and frequency domains. After pulse compression, this overlap increases the range side lobes, which appear as imaging artifacts and reduce the Bmode image quality. In this study, the isolation of higher order harmonics was achieved in another domain by using the fan chirp transform (FChT). To show the effect of excitation bandwidth in superharmonic imaging, measurements were performed by using linear frequency modulated chirp excitation with varying bandwidths of 10% to 50%. Superharmonic imaging was performed on a wire phantom using a wideband chirp excitation. Results were presented with and without applying the FChT filtering technique by comparing the spatial resolution and side lobe levels. Wideband excitation signals achieved a better resolution as expected, however range side lobes as high as -23 dB were observed for the superharmonic component of chirp excitation with 50% fractional bandwidth. The proposed filtering technique achieved >50 dB range side lobe suppression and improved the image quality without

  13. Depression, anxiety and somatization in primary care: syndrome overlap and functional impairment.

    Löwe, Bernd; Spitzer, Robert L; Williams, Janet B W; Mussell, Monika; Schellberg, Dieter; Kroenke, Kurt

    2008-01-01

    To determine diagnostic overlap of depression, anxiety and somatization as well as their unique and overlapping contribution to functional impairment. Two thousand ninety-one consecutive primary care clinic patients participated in a multicenter cross-sectional survey in 15 primary care clinics in the United States (participation rate, 92%). Depression, anxiety, somatization and functional impairment were assessed using validated scales from the Patient Health Questionnaire (PHQ) (PHQ-8, eight-item depression module; GAD-7, seven-item Generalized Anxiety Disorder Scale; and PHQ-15, 15-item somatic symptom scale) and the Short-Form General Health Survey (SF-20). Multiple linear regression analyses were used to investigate unique and overlapping associations of depression, anxiety and somatization with functional impairment. In over 50% of cases, comorbidities existed between depression, anxiety and somatization. The contribution of the commonalities of depression, anxiety and somatization to functional impairment substantially exceeded the contribution of their independent parts. Nevertheless, depression, anxiety and somatization did have important and individual effects (i.e., separate from their overlap effect) on certain areas of functional impairment. Given the large syndrome overlap, a potential consideration for future diagnostic classification would be to describe basic diagnostic criteria for a single overarching disorder and to optionally code additional diagnostic features that allow a more detailed classification into specific depressive, anxiety and somatoform subtypes.

  14. A new energy-efficient MAC protocol with noise-based transmitted-reference modulation for wireless sensor network

    Morshed, S.; Heijenk, Geert; Meijerink, Arjan; Ye, D.; van der Zee, Ronan A.R.; Bentum, Marinus Jan

    2013-01-01

    Energy-constrained behavior of sensor nodes is one of the most important criteria for successful deployment of wireless sensor networks. The medium access control (MAC) protocol determines to a large extent the time a sensor node transceiver spends listening or transmitting, and hence the energy

  15. Grid adaptation using chimera composite overlapping meshes

    Kao, Kai-Hsiung; Liou, Meng-Sing; Chow, Chuen-Yen

    1994-01-01

    The objective of this paper is to perform grid adaptation using composite overlapping meshes in regions of large gradient to accurately capture the salient features during computation. The chimera grid scheme, a multiple overset mesh technique, is used in combination with a Navier-Stokes solver. The numerical solution is first converged to a steady state based on an initial coarse mesh. Solution-adaptive enhancement is then performed by using a secondary fine grid system which oversets on top of the base grid in the high-gradient region, but without requiring the mesh boundaries to join in any special way. Communications through boundary interfaces between those separated grids are carried out using trilinear interpolation. Application to the Euler equations for shock reflections and to shock wave/boundary layer interaction problem are tested. With the present method, the salient features are well-resolved.

  16. Grid adaption using Chimera composite overlapping meshes

    Kao, Kai-Hsiung; Liou, Meng-Sing; Chow, Chuen-Yen

    1993-01-01

    The objective of this paper is to perform grid adaptation using composite over-lapping meshes in regions of large gradient to capture the salient features accurately during computation. The Chimera grid scheme, a multiple overset mesh technique, is used in combination with a Navier-Stokes solver. The numerical solution is first converged to a steady state based on an initial coarse mesh. Solution-adaptive enhancement is then performed by using a secondary fine grid system which oversets on top of the base grid in the high-gradient region, but without requiring the mesh boundaries to join in any special way. Communications through boundary interfaces between those separated grids are carried out using tri-linear interpolation. Applications to the Euler equations for shock reflections and to a shock wave/boundary layer interaction problem are tested. With the present method, the salient features are well resolved.

  17. Overlap-free symmetric D 0 Lwords

    Anna Frid

    2001-12-01

    Full Text Available A D0L word on an alphabet Σ={0,1,…,q-1} is called symmetric if it is a fixed point w=φ(w of a morphism φ:Σ * → Σ * defined by φ(i= t 1 + i t 2 + i … t m + i for some word t 1 t 2 … t m (equal to φ(0 and every i ∈ Σ; here a means a mod q. We prove a result conjectured by J. Shallit: if all the symbols in φ(0 are distinct (i.e., if t i ≠ t j for i ≠ j, then the symmetric D0L word w is overlap-free, i.e., contains no factor of the form axaxa for any x ∈ Σ * and a ∈ Σ.

  18. Locating overlap information in quantum systems

    Albrecht, A.

    1994-01-01

    When discussing the black hole information problem the term ''information flow'' is frequently used in a rather loose fashion. In this paper I attempt to make this notion more concrete. I consider a Hilbert space which is constructed as a tensor product of two subspaces (representing, for example, inside and outside the black hole). I discuss how the system has the capacity to contain information which is in neither of the subspaces. I attempt to quantify the amount of information located in each of the two subspaces, and elsewere, and analyze the exent to which unitary evolution can correspond to ''information flow.'' I define the notion of ''overlap information'' which appears to be well suited to the problem

  19. Efficacy analysis of LDPC coded APSK modulated differential space-time-frequency coded for wireless body area network using MB-pulsed OFDM UWB technology.

    Manimegalai, C T; Gauni, Sabitha; Kalimuthu, K

    2017-12-04

    Wireless body area network (WBAN) is a breakthrough technology in healthcare areas such as hospital and telemedicine. The human body has a complex mixture of different tissues. It is expected that the nature of propagation of electromagnetic signals is distinct in each of these tissues. This forms the base for the WBAN, which is different from other environments. In this paper, the knowledge of Ultra Wide Band (UWB) channel is explored in the WBAN (IEEE 802.15.6) system. The measurements of parameters in frequency range from 3.1-10.6 GHz are taken. The proposed system, transmits data up to 480 Mbps by using LDPC coded APSK Modulated Differential Space-Time-Frequency Coded MB-OFDM to increase the throughput and power efficiency.

  20. Continuous theta-burst stimulation may improve visuospatial neglect via modulating the attention network: a randomized controlled study.

    Fu, Wei; Cao, Lei; Zhang, Yanming; Huo, Su; Du, JuBao; Zhu, Lin; Song, Weiqun

    2017-05-01

    Visuospatial neglect (VSN) is devastating and common after stroke, and is thought to involve functional disturbance of the attention network. Non-invasive theta-burst stimulation (TBS) may help restore the normal function of attention network, therefore facilitating recovery from VSN. This study investigated the effects of continuous TBS on resting-state functional connectivity (RSFC) in the attention network, and behavioral performances of patients with VSN after stroke. Twelve patients were randomly assigned to receive 10-day cTBS of the left posterior parietal cortex delivered at 80% (the cTBS group), or 40% (the active control group) of the resting motor threshold. Both groups received daily visual scanning training and motor function treatment. Resting-state functional MRI (fMRI) and behavioral tests including line bisection test and star cancelation test were conducted at baseline and after the treatment. At baseline, the two groups showed comparable results in the resting-state fMRI experiments and behavioral tests. After treatment, the cTBS group showed lower functional connectivity between right temporoparietal junction (TPJ) and right anterior insula, and between right superior temporal sulcus and right anterior insula, as compared with the active control group; both groups showed improvement in the behavioral tests, with the cTBS group showing larger changes from baseline than the active control group. cTBS of the left posterior parietal cortex in patients with VSN may induce changes in inter-regional RSFC in the right ventral attention network. These changes may be associated with improved recovery of behavioral deficits after behavioral training. The TPJ and superior temporal sulcus may play crucial roles in recovery from VSN.

  1. Perception of social networking benefits in the support of a PBL module according to students' performance levels.

    Ekarattanawong, Sophapun; Thuppia, Amornnat; Chamod, Pholasit; Pattharanitima, Pattharawin; Suealek, Nuchanart; Rojpibulstit, Panadda

    2015-03-01

    The use ofsocial networking to all levels of medical teaching as a communication tool between instructors and students has drawn much interest and increased usage. As Facebook is one of the most popular social networking sites among students, a Facebook page has been used in the Genitourinary System problem-based learning (PBL) course at the Faculty of Medicine, Thammasat University in the year 2014. The objective of this work is to study the perception ofusing a Facebook page to support PBL in an integrated pre- clinical year course. The Genitourinary System course committee introduced Facebook page to the 2"d year medical students who enrolled and instructors involved in the course. At the beginning ofthe course, the objectives ofFacebook page setting were informed as follows: 1) public relations, 2) channelfor questions and responses to address curiosities between students and instructors, 3) learning stimulation and 4) supporting good relationship between course coordinators and students. The participants consisted of 177 students who voluntarily allowed their opinion to be used in analysis and dissemination after completing a questionnaire about using the Facebook page in PBL at the end. A Likert scale was used to determine satisfaction scores for nine questions. Finally, the mean satisfaction was compared for each question and for students with different academic performances (great, good, fine, weak). The students liked the page (averaged satisfaction score 4.64) and wanted it to continue to be used in coursework (4.63), especiallyfor students at mid-level when compared to students with great performances (psocial networking, particularly Facebook pages, achieved all the four the stated objectives. Since this was the first time social networking was applied, some of faculty members had concern that their personal information would be disseminated to the public. Moreover there was still minimal knowledge of sharing among students. The Facebook "closed group

  2. Additional file 10: Figure S3. of Uncovering co-expression gene network modules regulating fruit acidity in diverse apples

    Bai, Yang; Dougherty, Laura; Cheng, Lailiang; Zhong, Gan-Yuan; Xu, Kenong

    2015-01-01

    Other regulators from modules Turquoise and Brown and their assigned tight clusters. Elements and their contents, formats and messages are same as those noted in Fig. 8a. (A) Regulator M239684 and Cluster 41 of 68 genes. (B) Regulator M239684 and Cluster 5 of 14 genes. (C) Regulator M239684 and Cluster 7 of 14 genes. (D) Regulator M753318 and Cluster 23 of 11 genes. (E) Regulator M753318 and Cluster 32 of 11 genes. (F) Regulator M175481 and Cluster 2 of 16 genes. (G) Regulator M134341 and Cl...

  3. Prospects of engineering thermotolerance in crops through modulation of heat stress transcription factor and heat shock protein networks.

    Fragkostefanakis, Sotirios; Röth, Sascha; Schleiff, Enrico; Scharf, Klaus-Dieter

    2015-09-01

    Cell survival under high temperature conditions involves the activation of heat stress response (HSR), which in principle is highly conserved among different organisms, but shows remarkable complexity and unique features in plant systems. The transcriptional reprogramming at higher temperatures is controlled by the activity of the heat stress transcription factors (Hsfs). Hsfs allow the transcriptional activation of HSR genes, among which heat shock proteins (Hsps) are best characterized. Hsps belong to multigene families encoding for molecular chaperones involved in various processes including maintenance of protein homeostasis as a requisite for optimal development and survival under stress conditions. Hsfs form complex networks to activate downstream responses, but are concomitantly subjected to cell-type-dependent feedback regulation through factor-specific physical and functional interactions with chaperones belonging to Hsp90, Hsp70 and small Hsp families. There is increasing evidence that the originally assumed specialized function of Hsf/chaperone networks in the HSR turns out to be a complex central stress response system that is involved in the regulation of a broad variety of other stress responses and may also have substantial impact on various developmental processes. Understanding in detail the function of such regulatory networks is prerequisite for sustained improvement of thermotolerance in important agricultural crops. © 2014 John Wiley & Sons Ltd.

  4. Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

    Naushad, Shaik Mohammad; Ramaiah, M Janaki; Pavithrakumari, Manickam; Jayapriya, Jaganathan; Hussain, Tajamul; Alrokayan, Salman A; Gottumukkala, Suryanarayana Raju; Digumarti, Raghunadharao; Kutala, Vijay Kumar

    2016-04-15

    In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how micronutrients modulate susceptibility to breast cancer. The developed ANN model explained 94.2% variability in breast cancer prediction. Fixed effect models of folate (400 μg/day) and B12 (6 μg/day) showed 33.3% and 11.3% risk reduction, respectively. Multifactor dimensionality reduction analysis showed the following interactions in responders to folate: RFC1 G80A × MTHFR C677T (primary), COMT H108L × CYP1A1 m2 (secondary), MTR A2756G (tertiary). The interactions among responders to B12 were RFC1G80A × cSHMT C1420T and CYP1A1 m2 × CYP1A1 m4. ANN simulations revealed that increased folate might restore ER and PR expression and reduce the promoter CpG island methylation of extra cellular superoxide dismutase and BRCA1. Dietary intake of folate appears to confer protection against breast cancer through its modulating effects on ER and PR expression and methylation of EC-SOD and BRCA1. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Development of field programmable gate array–based encryption module to mitigate man-in-the-middle attack for nuclear power plant data communication network

    Mohamed Abdallah Elakrat

    2018-06-01

    Full Text Available This article presents a security module based on a field programmable gate array (FPGA to mitigate man-in-the-middle cyber attacks. Nowadays, the FPGA is considered to be the state of the art in nuclear power plants I&C systems due to its flexibility, reconfigurability, and maintainability of the FPGA technology; it also provides acceptable solutions for embedded computing applications that require cybersecurity. The proposed FPGA-based security module is developed to mitigate information-gathering attacks, which can be made by gaining physical access to the network, e.g., a man-in-the-middle attack, using a cryptographic process to ensure data confidentiality and integrity and prevent injecting malware or malicious data into the critical digital assets of a nuclear power plant data communication system. A model-based system engineering approach is applied. System requirements analysis and enhanced function flow block diagrams are created and simulated using CORE9 to compare the performance of the current and developed systems. Hardware description language code for encryption and serial communication is developed using Vivado Design Suite 2017.2 as a programming tool to run the system synthesis and implementation for performance simulation and design verification. Simple windows are developed using Java for physical testing and communication between a personal computer and the FPGA. Keywords: AES-128, Cyber Security, Encryption, Field Programmable Gate Array, I&C

  6. A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis.

    Taroni, Jaclyn N; Greene, Casey S; Martyanov, Viktor; Wood, Tammara A; Christmann, Romy B; Farber, Harrison W; Lafyatis, Robert A; Denton, Christopher P; Hinchcliff, Monique E; Pioli, Patricia A; Mahoney, J Matthew; Whitfield, Michael L

    2017-03-23

    Systemic sclerosis (SSc) is a multi-organ autoimmune disease characterized by skin fibrosis. Internal organ involvement is heterogeneous. It is unknown whether disease mechanisms are common across all involved affected tissues or if each manifestation has a distinct underlying pathology. We used consensus clustering to compare gene expression profiles of biopsies from four SSc-affected tissues (skin, lung, esophagus, and peripheral blood) from patients with SSc, and the related conditions pulmonary fibrosis (PF) and pulmonary arterial hypertension, and derived a consensus disease-associate signature across all tissues. We used this signature to query tissue-specific functional genomic networks. We performed novel network analyses to contrast the skin and lung microenvironments and to assess the functional role of the inflammatory and fibrotic genes in each organ. Lastly, we tested the expression of macrophage activation state-associated gene sets for enrichment in skin and lung using a Wilcoxon rank sum test. We identified a common pathogenic gene expression signature-an immune-fibrotic axis-indicative of pro-fibrotic macrophages (MØs) in multiple tissues (skin, lung, esophagus, and peripheral blood mononuclear cells) affected by SSc. While the co-expression of these genes is common to all tissues, the functional consequences of this upregulation differ by organ. We used this disease-associated signature to query tissue-specific functional genomic networks to identify common and tissue-specific pathologies of SSc and related conditions. In contrast to skin, in the lung-specific functional network we identify a distinct lung-resident MØ signature associated with lipid stimulation and alternative activation. In keeping with our network results, we find distinct MØ alternative activation transcriptional programs in SSc-associated PF lung and in the skin of patients with an "inflammatory" SSc gene expression signature. Our results suggest that the innate immune

  7. Norm overlap between many-body states: Uncorrelated overlap between arbitrary Bogoliubov product states

    Bally, B.; Duguet, T.

    2018-02-01

    Background: State-of-the-art multi-reference energy density functional calculations require the computation of norm overlaps between different Bogoliubov quasiparticle many-body states. It is only recently that the efficient and unambiguous calculation of such norm kernels has become available under the form of Pfaffians [L. M. Robledo, Phys. Rev. C 79, 021302 (2009), 10.1103/PhysRevC.79.021302]. Recently developed particle-number-restored Bogoliubov coupled-cluster (PNR-BCC) and particle-number-restored Bogoliubov many-body perturbation (PNR-BMBPT) ab initio theories [T. Duguet and A. Signoracci, J. Phys. G 44, 015103 (2017), 10.1088/0954-3899/44/1/015103] make use of generalized norm kernels incorporating explicit many-body correlations. In PNR-BCC and PNR-BMBPT, the Bogoliubov states involved in the norm kernels differ specifically via a global gauge rotation. Purpose: The goal of this work is threefold. We wish (i) to propose and implement an alternative to the Pfaffian method to compute unambiguously the norm overlap between arbitrary Bogoliubov quasiparticle states, (ii) to extend the first point to explicitly correlated norm kernels, and (iii) to scrutinize the analytical content of the correlated norm kernels employed in PNR-BMBPT. Point (i) constitutes the purpose of the present paper while points (ii) and (iii) are addressed in a forthcoming paper. Methods: We generalize the method used in another work [T. Duguet and A. Signoracci, J. Phys. G 44, 015103 (2017), 10.1088/0954-3899/44/1/015103] in such a way that it is applicable to kernels involving arbitrary pairs of Bogoliubov states. The formalism is presently explicated in detail in the case of the uncorrelated overlap between arbitrary Bogoliubov states. The power of the method is numerically illustrated and benchmarked against known results on the basis of toy models of increasing complexity. Results: The norm overlap between arbitrary Bogoliubov product states is obtained under a closed

  8. Computational exploration of cis-regulatory modules in rhythmic expression data using the "Exploration of Distinctive CREs and CRMs" (EDCC) and "CRM Network Generator" (CNG) programs.

    Bekiaris, Pavlos Stephanos; Tekath, Tobias; Staiger, Dorothee; Danisman, Selahattin

    2018-01-01

    Understanding the effect of cis-regulatory elements (CRE) and clusters of CREs, which are called cis-regulatory modules (CRM), in eukaryotic gene expression is a challenge of computational biology. We developed two programs that allow simple, fast and reliable analysis of candidate CREs and CRMs that may affect specific gene expression and that determine positional features between individual CREs within a CRM. The first program, "Exploration of Distinctive CREs and CRMs" (EDCC), correlates candidate CREs and CRMs with specific gene expression patterns. For pairs of CREs, EDCC also determines positional preferences of the single CREs in relation to each other and to the transcriptional start site. The second program, "CRM Network Generator" (CNG), prioritizes these positional preferences using a neural network and thus allows unbiased rating of the positional preferences that were determined by EDCC. We tested these programs with data from a microarray study of circadian gene expression in Arabidopsis thaliana. Analyzing more than 1.5 million pairwise CRE combinations, we found 22 candidate combinations, of which several contained known clock promoter elements together with elements that had not been identified as relevant to circadian gene expression before. CNG analysis further identified positional preferences of these CRE pairs, hinting at positional information that may be relevant for circadian gene expression. Future wet lab experiments will have to determine which of these combinations confer daytime specific circadian gene expression.

  9. Electro-optical time gating based on Mach-Zehnder modulator for multiple access interference elimination in optical code-division multiple access networks

    Chen, Yinfang; Wang, Rong; Fang, Tao; Pu, Tao; Xiang, Peng; Zheng, Jilin; Zhu, Huatao

    2014-05-01

    An electro-optical time gating technique, which is based on an electrical return-to-zero (RZ) pulse driven Mach-Zehnder modulator (MZM) for eliminating multiple access interference (MAI) in optical code-division multiple access (OCDMA) networks is proposed. This technique is successfully simulated in an eight-user two-dimensional wavelength-hopping time-spreading system, as well as in a three-user temporal phase encoding system. Results show that in both systems the MAI noise is efficiently removed and the average received power penalty improved. Both achieve error-free transmissions at a bit rate of 2.5 Gb/s. In addition, we also individually discuss effects of parameters in two systems, such as the extinction ratio of the MZM, the duty cycle of the driven RZ pulse, and the time misalignment between the driven pulse and the decoded autocorrelation peak, on the output bit error rate performance. Our work shows that employing a common MZM as a thresholder provides another probability and an interesting cost-effective choice for a smart size, low energy, and less complex thresholding technique for integrated detection in OCDMA networks.

  10. Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

    Havemann, Frank; Heinz, Michael; Struck, Alexander; Gläser, Jochen

    2011-01-01

    We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily expands natural communities of seeds until the whole graph is covered. The hierarchy of communities is obtained analytically by calculating resolution levels at which communities grow rather than numerically by testing different resolution levels. This analytic procedure is not only more exact than its numerical alternatives such as LFM and GCE but also much faster. Critical resolution levels can be identified by searching for intervals in which large changes of the resolution do not lead to growth of communities. We tested our algorithm on benchmark graphs and on a network of 492 papers in information science. Combined with a specific post-processing, the algorithm gives much more precise results on LFR benchmarks with high overlap compared to other algorithms and performs very similarly to GCE

  11. Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

    Havemann, Frank; Heinz, Michael; Struck, Alexander; Gläser, Jochen

    2011-01-01

    We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily expands natural communities of seeds until the whole graph is covered. The hierarchy of communities is obtained analytically by calculating resolution levels at which communities grow rather than numerically by testing different resolution levels. This analytic procedure is not only more exact than its numerical alternatives such as LFM and GCE but also much faster. Critical resolution levels can be identified by searching for intervals in which large changes of the resolution do not lead to growth of communities. We tested our algorithm on benchmark graphs and on a network of 492 papers in information science. Combined with a specific post-processing, the algorithm gives much more precise results on LFR benchmarks with high overlap compared to other algorithms and performs very similarly to GCE.

  12. Depression-Burnout Overlap in Physicians

    Wurm, Walter; Vogel, Katrin; Holl, Anna; Ebner, Christoph; Bayer, Dietmar; Mörkl, Sabrina; Szilagyi, Istvan-Szilard; Hotter, Erich; Kapfhammer, Hans-Peter; Hofmann, Peter

    2016-01-01

    Background Whether burnout is a distinct phenomenon rather than a type of depression and whether it is a syndrome, limited to three “core” components (emotional exhaustion, depersonalization and low personal accomplishment) are subjects of current debate. We investigated the depression-burnout overlap, and the pertinence of these three components in a large, representative sample of physicians. Methods In a cross-sectional study, all Austrian physicians were invited to answer a questionnaire that included the Major Depression Inventory (MDI), the Hamburg Burnout Inventory (HBI), as well as demographic and job-related parameters. Of the 40093 physicians who received an invitation, a total of 6351 (15.8%) participated. The data of 5897 participants were suitable for analysis. Results Of the participants, 10.3% were affected by major depression. Our study results suggest that potentially 50.7% of the participants were affected by symptoms of burnout. Compared to physicians unaffected by burnout, the odds ratio of suffering from major depression was 2.99 (95% CI 2.21–4.06) for physicians with mild, 10.14 (95% CI 7.58–13.59) for physicians with moderate, 46.84 (95% CI 35.25–62.24) for physicians with severe burnout and 92.78 (95% CI 62.96–136.74) for the 3% of participants with the highest HBI_sum (sum score of all ten HBI components). The HBI components Emotional Exhaustion, Personal Accomplishment and Detachment (representing depersonalization) tend to correlate more highly with the main symptoms of major depression (sadness, lack of interest and lack of energy) than with each other. A combination of the HBI components Emotional Exhaustion, Helplessness, Inner Void and Tedium (adj.R2 = 0.92) explained more HBI_sum variance than the three “core” components (adj.R2 = 0.85) of burnout combined. Cronbach’s alpha for Emotional Exhaustion, Helplessness, Inner Void and Tedium combined was 0.90 compared to α = 0.54 for the combination of the three

  13. Depression-Burnout Overlap in Physicians.

    Walter Wurm

    Full Text Available Whether burnout is a distinct phenomenon rather than a type of depression and whether it is a syndrome, limited to three "core" components (emotional exhaustion, depersonalization and low personal accomplishment are subjects of current debate. We investigated the depression-burnout overlap, and the pertinence of these three components in a large, representative sample of physicians.In a cross-sectional study, all Austrian physicians were invited to answer a questionnaire that included the Major Depression Inventory (MDI, the Hamburg Burnout Inventory (HBI, as well as demographic and job-related parameters. Of the 40093 physicians who received an invitation, a total of 6351 (15.8% participated. The data of 5897 participants were suitable for analysis.Of the participants, 10.3% were affected by major depression. Our study results suggest that potentially 50.7% of the participants were affected by symptoms of burnout. Compared to physicians unaffected by burnout, the odds ratio of suffering from major depression was 2.99 (95% CI 2.21-4.06 for physicians with mild, 10.14 (95% CI 7.58-13.59 for physicians with moderate, 46.84 (95% CI 35.25-62.24 for physicians with severe burnout and 92.78 (95% CI 62.96-136.74 for the 3% of participants with the highest HBI_sum (sum score of all ten HBI components. The HBI components Emotional Exhaustion, Personal Accomplishment and Detachment (representing depersonalization tend to correlate more highly with the main symptoms of major depression (sadness, lack of interest and lack of energy than with each other. A combination of the HBI components Emotional Exhaustion, Helplessness, Inner Void and Tedium (adj.R2 = 0.92 explained more HBI_sum variance than the three "core" components (adj.R2 = 0.85 of burnout combined. Cronbach's alpha for Emotional Exhaustion, Helplessness, Inner Void and Tedium combined was 0.90 compared to α = 0.54 for the combination of the three "core" components.This study demonstrates the

  14. Reality = Relevance? Insights from Spontaneous Modulations of the Brain's Default Network when Telling Apart Reality from Fiction

    Abraham, Anna; von Cramon, D. Yves

    2009-01-01

    Background Although human beings regularly experience fictional worlds through activities such as reading novels and watching movies, little is known about what mechanisms underlie our implicit knowledge of the distinction between reality and fiction. The first neuroimaging study to address this issue revealed that the mere exposure to contexts involving real entities compared to fictional characters led to engagement of regions in the anterior medial prefrontal and posterior cingulate cortices (amPFC, PCC). As these core regions of the brain's default network are involved during self-referential processing and autobiographical memory retrieval, it was hypothesized that real entities may be conceptually coded as being more personally relevant to us than fictional characters. Methodology/Principal Findings In the present functional magnetic resonance imaging (fMRI) study, we directly test the hypothesis that entity-associated personal relevance is the critical factor underlying the differential engagement of these brain regions by comparing the brain's response when processing contexts involving family or friends (high relevance), famous people (medium relevance), or fictional characters (low relevance). In line with predictions, a gradient pattern of activation was observed such that higher entity-associated personal relevance was associated with stronger activation in the amPFC and the PCC. Conclusions/Significance The results of the study have several important implications. Firstly, they provide informed grounds for characterizing the dynamics of reality-fiction distinction. Secondly, they provide further insights into the functions of the amPFC and the PCC. Thirdly, in view of the current debate related to the functional relevance and specificity of brain's default network, they reveal a novel approach by which the functions of this network can be further explored. PMID:19277108

  15. Reality = relevance? Insights from spontaneous modulations of the brain's default network when telling apart reality from fiction.

    Anna Abraham

    Full Text Available BACKGROUND: Although human beings regularly experience fictional worlds through activities such as reading novels and watching movies, little is known about what mechanisms underlie our implicit knowledge of the distinction between reality and fiction. The first neuroimaging study to address this issue revealed that the mere exposure to contexts involving real entities compared to fictional characters led to engagement of regions in the anterior medial prefrontal and posterior cingulate cortices (amPFC, PCC. As these core regions of the brain's default network are involved during self-referential processing and autobiographical memory retrieval, it was hypothesized that real entities may be conceptually coded as being more personally relevant to us than fictional characters. METHODOLOGY/PRINCIPAL FINDINGS: In the present functional magnetic resonance imaging (fMRI study, we directly test the hypothesis that entity-associated personal relevance is the critical factor underlying the differential engagement of these brain regions by comparing the brain's response when processing contexts involving family or friends (high relevance, famous people (medium relevance, or fictional characters (low relevance. In line with predictions, a gradient pattern of activation was observed such that higher entity-associated personal relevance was associated with stronger activation in the amPFC and the PCC. CONCLUSIONS/SIGNIFICANCE: The results of the study have several important implications. Firstly, they provide informed grounds for characterizing the dynamics of reality-fiction distinction. Secondly, they provide further insights into the functions of the amPFC and the PCC. Thirdly, in view of the current debate related to the functional relevance and specificity of brain's default network, they reveal a novel approach by which the functions of this network can be further explored.

  16. High pressure and [Ca2+] produce an inverse modulation of synaptic input strength, network excitability and frequency response in the rat dentate gyrus

    Thomas I Talpalar

    2016-09-01

    Full Text Available Hyperbaric environments induce the high pressure neurological syndrome (HPNS characterized by hyperexcitability of the central nervous system and memory impairment. Human divers and other animals experience the HPNS at pressures beyond 1.1 MPa. High pressure depresses synaptic transmission and alters its dynamics in various animal models. Medial perforant path (MPP synapses connecting the medial entorhinal cortex with the hippocampal formation are suppressed by 50% at 10.1MPa. Reduction of synaptic inputs is paradoxically associated with enhanced ability of dentate gyrus’ granule cells to generate spikes at high pressure. This mechanism allows MPP inputs to elicit standard granule cell outputs at 0.1 -25 Hz frequencies under hyperbaric conditions. An increased postsynaptic gain of MPP inputs probably allows diving animals to perform in hyperbaric environments, but makes them vulnerable to high intensity/frequency stimuli producing hyperexcitability. Increasing extracellular Ca2+ (Ca2+o partially reverted pressure-mediated depression of MPP inputs and increased MPP’s low-pass filter properties. We postulated that raising Ca2+o in addition to increase synaptic inputs may reduce network excitability in the dentate gyrus potentially improving its function and reducing sensitivity to high intensity and pathologic stimuli. For this matter, we activated the MPP with single and 50 Hz frequency stimuli that simulated physiologic and deleterious conditions, while assessing the granule cell’s output under various conditions of pressure and Ca2+o. Our results reveal that pressure and Ca2+o produce an inverse modulation on synaptic input strength and network excitability. These coincident phenomena suggest a potential general mechanism of networks that adjusts gain as an inverse function of synaptic inputs’ strength. Such mechanism may serve for adaptation to variable pressure and other physiological and pathological conditions and may explain the

  17. Identification of overlapping communities and their hierarchy by locally calculating community-changing resolution levels

    Havemann, Frank; Heinz, Michael; Struck, Alexander; Gläser, Jochen

    2010-01-01

    We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily expands natural communities of seeds until the whole graph is covered. The hierarchy of communities is obtained analytically by calculating resolution levels at which communities grow rather than numerically by testing different resolution levels. This ana...

  18. Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation.

    De Cegli, Rossella; Iacobacci, Simona; Flore, Gemma; Gambardella, Gennaro; Mao, Lei; Cutillo, Luisa; Lauria, Mario; Klose, Joachim; Illingworth, Elizabeth; Banfi, Sandro; di Bernardo, Diego

    2013-01-01

    Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology 'reverse engineering' approaches. We 'reverse engineered' an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression ('hubs'). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central 'hub' of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation.

  19. Spin with two snakes and overlapping resonances

    Lee, S.Y.; Zhao, X.F.

    1987-01-01

    We study the effect of multiple spin depolarization resonances on the spin of the particles with two snakes. When two resonances are well separated, the polarization can be restored in passing through these resonances provided that the snake resonances are avoided. When two resonances are overlapping, the beam particles may be depolarized depending on the spacing between these two resonances. If the spacing between these two resonances is an odd number for two snakes, the beam particles may be depolarized depending on the strength of the resonance. When the spacing becomes an even number, the spin can tolerate a much larger resonance strength without depolarization. Numerical simulations can be shown to agree well with the analytic formula. However, the spin is susceptible to the combination of an intrinsic and an imperfection resonances even in the presence of the snakes. Numerical simulation indicates that the spin can be restored after the resonances provided that imperfection strength is less than 0.1 if intrinsic strength is fixed at 0.745

  20. Vulval lichen planus-lichen sclerosus overlap.

    Howard, Matthew; Hall, Anthony

    2018-01-01

    Vulval lichen planus-lichen sclerosus overlap is an emerging observation. Few clinical reports exist with no reviews of literature. We present a focused update of this phenomenon and discuss a clinical case. We report a 63-year-old woman with a 20-year history of ulcerative vulvo-vaginitis, initially diagnosed as benign mucous membrane (cicatricial) pemphigoid. This led to prolonged treatment with oral corticosteroids with minimal improvement in symptoms. Subsequent complications of long-term use of systemic corticosteroid ensued. A clinico-pathological diagnosis of severe erosive lichen planus was made on clinical findings and on non-specific biopsy changes of ulceration and inflammation. Treatment with topical clobetasol propionate 0.05% ointment twice daily led to dramatic improvement of ulceration, easing of discomfort and marked improvement in quality of life. Clinical examination revealed Wickham's striae on the labia majora supporting the diagnosis. Six years after commencement of topical clobetasol, white plaques were noticed on the labia majora, perineum and peri-anal region consistent with lichen sclerosus, confirmed by repeat vulval skin biopsy and on vulvectomy. This case highlights the challenge of diagnosis of extensive vulvo-vaginal ulceration and the necessity to re-examine a previous diagnosis if there is poor response to treatment.

  1. External pallidal stimulation improves parkinsonian motor signs and modulates neuronal activity throughout the basal ganglia thalamic network.

    Vitek, Jerrold L; Zhang, Jianyu; Hashimoto, Takao; Russo, Gary S; Baker, Kenneth B

    2012-01-01

    Deep brain stimulation (DBS) of the internal segment of the globus pallidus (GPi) and the subthalamic nucleus (STN) are effective for the treatment of advanced Parkinson's disease (PD). We have shown previously that DBS of the external segment of the globus pallidus (GPe) is associated with improvements in parkinsonian motor signs; however, the mechanism of this effect is not known. In this study, we extend our findings on the effect of STN and GPi DBS on neuronal activity in the basal ganglia thalamic network to include GPe DBS using the 1-methyl-4-phenyl-1.2.3.6-tetrahydropyridine (MPTP) monkey model. Stimulation parameters that improved bradykinesia were associated with changes in the pattern and mean discharge rate of neuronal activity in the GPi, STN, and the pallidal [ventralis lateralis pars oralis (VLo) and ventralis anterior (VA)] and cerebellar [ventralis lateralis posterior pars oralis (VPLo)] receiving areas of the motor thalamus. Population post-stimulation time histograms revealed a complex pattern of stimulation-related inhibition and excitation for the GPi and VA/VLo, with a more consistent pattern of inhibition in STN and excitation in VPLo. Mean discharge rate was reduced in the GPi and STN and increased in the VPLo. Effective GPe DBS also reduced bursting in the STN and GPi. These data support the hypothesis that therapeutic DBS activates output from the stimulated structure and changes the temporal pattern of neuronal activity throughout the basal ganglia thalamic network and provide further support for GPe as a potential therapeutic target for DBS in the treatment of PD. Copyright © 2011 Elsevier Inc. All rights reserved.

  2. Scaling vectors of attoJoule per bit modulators

    Sorger, Volker J.; Amin, Rubab; Khurgin, Jacob B.; Ma, Zhizhen; Dalir, Hamed; Khan, Sikandar

    2018-01-01

    Electro-optic modulation performs the conversion between the electrical and optical domain with applications in data communication for optical interconnects, but also for novel optical computing algorithms such as providing nonlinearity at the output stage of optical perceptrons in neuromorphic analog optical computing. While resembling an optical transistor, the weak light-matter-interaction makes modulators 105 times larger compared to their electronic counterparts. Since the clock frequency for photonics on-chip has a power-overhead sweet-spot around tens of GHz, ultrafast modulation may only be required in long-distance communication, not for short on-chip links. Hence, the search is open for power-efficient on-chip modulators beyond the solutions offered by foundries to date. Here, we show scaling vectors towards atto-Joule per bit efficient modulators on-chip as well as some experimental demonstrations of novel plasmonic modulators with sub-fJ/bit efficiencies. Our parametric study of placing different actively modulated materials into plasmonic versus photonic optical modes shows that 2D materials overcompensate their miniscule modal overlap by their unity-high index change. Furthermore, we reveal that the metal used in plasmonic-based modulators not only serves as an electrical contact, but also enables low electrical series resistances leading to near-ideal capacitors. We then discuss the first experimental demonstration of a photon-plasmon-hybrid graphene-based electro-absorption modulator on silicon. The device shows a sub-1 V steep switching enabled by near-ideal electrostatics delivering a high 0.05 dB V-1 μm-1 performance requiring only 110 aJ/bit. Improving on this demonstration, we discuss a plasmonic slot-based graphene modulator design, where the polarization of the plasmonic mode aligns with graphene’s in-plane dimension; where a push-pull dual-gating scheme enables 2 dB V-1 μm-1 efficient modulation allowing the device to be just 770 nm

  3. Inflammatory biomarkers in asthma-COPD overlap syndrome

    Kobayashi S

    2016-09-01

    Full Text Available Seiichi Kobayashi, Masakazu Hanagama, Shinsuke Yamanda, Masatsugu Ishida, Masaru YanaiDepartment of Respiratory Medicine, Japanese Red Cross Ishinomaki Hospital, Ishinomaki, JapanBackground: The clinical phenotypes and underlying mechanisms of asthma-COPD overlap syndrome (ACOS remain elusive. This study aimed to investigate a comparison of COPD patients with and without ACOS, focusing on inflammatory biomarkers, in an outpatient COPD cohort.Methods: We conducted a cross-sectional study analyzing prospectively collected data from the Ishinomaki COPD Network registry. All participants were diagnosed with COPD, confirmed by using spirometry, and were aged 40–90 years and former smokers. Patients with features of asthma including both variable respiratory symptoms and variable expiratory airflow limitation were identified and defined as having ACOS. Then, the inflammatory biomarkers such as fractional exhaled nitric oxide level, blood eosinophil count and percentage, total immunoglobulin E (IgE level, and presence of antigen-specific IgE were evaluated.Results: A total of 257 patients with COPD were identified, including 37 (14.4% with ACOS. Patients with ACOS tended to be younger, have a shorter smoking history, and use more respiratory medications, especially inhaled corticosteroids and theophylline. Mean fractional exhaled nitric oxide level was significantly higher in those with ACOS than in those without ACOS (38.5 parts per billion [ppb] vs 20.3 ppb, P<0.001. Blood eosinophil count and percentage were significantly increased in those with ACOS (295/mm3 vs 212/mm3, P=0.032; 4.7% vs 3.2%, P=0.003, respectively. Total IgE level was also significantly higher, and presence of antigen-specific IgE was observed more frequently in patients with ACOS. Receiver operating characteristic curve analysis indicated that the sensitivity and specificity of these biomarkers were relatively low, but combinations of these biomarkers showed high specificity for

  4. Sticking with the nice guy: trait warmth information impairs learning and modulates person perception brain network activity.

    Lee, Victoria K; Harris, Lasana T

    2014-12-01

    Social learning requires inferring social information about another person, as well as evaluating outcomes. Previous research shows that prior social information biases decision making and reduces reliance on striatal activity during learning (Delgado, Frank, & Phelps, Nature Neuroscience 8 (11): 1611-1618, 2005). A rich literature in social psychology on person perception demonstrates that people spontaneously infer social information when viewing another person (Fiske & Taylor, 2013) and engage a network of brain regions, including the medial prefrontal cortex, temporal parietal junction, superior temporal sulcus, and precuneus (Amodio & Frith, Nature Reviews Neuroscience, 7(4), 268-277, 2006; Haxby, Gobbini, & Montgomery, 2004; van Overwalle Human Brain Mapping, 30, 829-858, 2009). We investigate the role of these brain regions during social learning about well-established dimensions of person perception-trait warmth and trait competence. We test the hypothesis that activity in person perception brain regions interacts with learning structures during social learning. Participants play an investment game where they must choose an agent to invest on their behalf. This choice is guided by cues signaling trait warmth or trait competence based on framing of monetary returns. Trait warmth information impairs learning about human but not computer agents, while trait competence information produces similar learning rates for human and computer agents. We see increased activation to warmth information about human agents in person perception brain regions. Interestingly, activity in person perception brain regions during the decision phase negatively predicts activity in the striatum during feedback for trait competence inferences about humans. These results suggest that social learning may engage additional processing within person perception brain regions that hampers learning in economic contexts.

  5. A dynamic model for managing overlapped iterative product development

    Lin, J.; Chai, K.H.; Wong, Y.S.; Brombacher, A.C.

    2008-01-01

    Intense competition in many industries impels firms to develop more products in less time. Overlapping of development activities is regarded as one of the most promising strategies to reduce project cycle time. However, the gain from overlapping must be weighed against the additional resource and

  6. Overlapped optics induced perfect coherent effects

    Li, Jian Jie; Zang, Xiao Fei; Mao, Jun Fa; Tang, Min; Zhu, Yi Ming; Zhuang, Song Lin

    2013-12-01

    For traditional coherent effects, two separated identical point sources can be interfered with each other only when the optical path difference is integer number of wavelengths, leading to alternate dark and bright fringes for different optical path difference. For hundreds of years, such a perfect coherent condition seems insurmountable. However, in this paper, based on transformation optics, two separated in-phase identical point sources can induce perfect interference with each other without satisfying the traditional coherent condition. This shifting illusion media is realized by inductor-capacitor transmission line network. Theoretical analysis, numerical simulations and experimental results are performed to confirm such a kind of perfect coherent effect and it is found that the total radiation power of multiple elements system can be greatly enhanced. Our investigation may be applicable to National Ignition Facility (NIF), Inertial Confined Fusion (ICF) of China, LED lighting technology, terahertz communication, and so on.

  7. Functional overlap of top-down emotion regulation and generation: an fMRI study identifying common neural substrates between cognitive reappraisal and cognitively generated emotions.

    Otto, Benjamin; Misra, Supriya; Prasad, Aditya; McRae, Kateri

    2014-09-01

    One factor that influences the success of emotion regulation is the manner in which the regulated emotion was generated. Recent research has suggested that reappraisal, a top-down emotion regulation strategy, is more effective in decreasing self-reported negative affect when emotions were generated from the top-down, versus the bottom-up. On the basis of a process overlap framework, we hypothesized that the neural regions active during reappraisal would overlap more with emotions that were generated from the top-down, rather than from the bottom-up. In addition, we hypothesized that increased neural overlap between reappraisal and the history effects of top-down emotion generation would be associated with increased reappraisal success. The results of several analyses suggested that reappraisal and emotions that were generated from the top-down share a core network of prefrontal, temporal, and cingulate regions. This overlap is specific; no such overlap was observed between reappraisal and emotions that were generated in a bottom-up fashion. This network consists of regions previously implicated in linguistic processing, cognitive control, and self-relevant appraisals, which are processes thought to be crucial to both reappraisal and top-down emotion generation. Furthermore, individuals with high reappraisal success demonstrated greater neural overlap between reappraisal and the history of top-down emotion generation than did those with low reappraisal success. The overlap of these key regions, reflecting overlapping processes, provides an initial insight into the mechanism by which generation history may facilitate emotion regulation.

  8. Transcriptome-Based Modeling Reveals that Oxidative Stress Induces Modulation of the AtfA-Dependent Signaling Networks in Aspergillus nidulans

    Erzsébet Orosz

    2017-01-01

    Full Text Available To better understand the molecular functions of the master stress-response regulator AtfA in Aspergillus nidulans, transcriptomic analyses of the atfA null mutant and the appropriate control strains exposed to menadione sodium bisulfite- (MSB-, t-butylhydroperoxide- and diamide-induced oxidative stresses were performed. Several elements of oxidative stress response were differentially expressed. Many of them, including the downregulation of the mitotic cell cycle, as the MSB stress-specific upregulation of FeS cluster assembly and the MSB stress-specific downregulation of nitrate reduction, tricarboxylic acid cycle, and ER to Golgi vesicle-mediated transport, showed AtfA dependence. To elucidate the potential global regulatory role of AtfA governing expression of a high number of genes with very versatile biological functions, we devised a model based on the comprehensive transcriptomic data. Our model suggests that an important function of AtfA is to modulate the transduction of stress signals. Although it may regulate directly only a limited number of genes, these include elements of the signaling network, for example, members of the two-component signal transduction systems. AtfA acts in a stress-specific manner, which may increase further the number and diversity of AtfA-dependent genes. Our model sheds light on the versatility of the physiological functions of AtfA and its orthologs in fungi.

  9. Identification of HDA15-PIF1 as a key repression module directing the transcriptional network of seed germination in the dark.

    Gu, Dachuan; Chen, Chia-Yang; Zhao, Minglei; Zhao, Linmao; Duan, Xuewu; Duan, Jun; Wu, Keqiang; Liu, Xuncheng

    2017-07-07

    Light is a major external factor in regulating seed germination. Photoreceptor phytochrome B (PHYB) plays a predominant role in promoting seed germination in the initial phase after imbibition, partially by repressing phytochrome-interacting factor1 (PIF1). However, the mechanism underlying the PHYB-PIF1-mediated transcription regulation remains largely unclear. Here, we identified that histone deacetylase15 (HDA15) is a negative component of PHYB-dependent seed germination. Overexpression of HDA15 in Arabidopsis inhibits PHYB-dependent seed germination, whereas loss of function of HDA15 increases PHYB-dependent seed germination. Genetic evidence indicated that HDA15 acts downstream of PHYB and represses seed germination dependent on PIF1. Furthermore, HDA15 interacts with PIF1 both in vitro and in vivo. Genome-wide transcriptome analysis revealed that HDA15 and PIF1 co-regulate the transcription of the light-responsive genes involved in multiple hormonal signaling pathways and cellular processes in germinating seeds in the dark. In addition, PIF1 recruits HDA15 to the promoter regions of target genes and represses their expression by decreasing the histone H3 acetylation levels in the dark. Taken together, our analysis uncovered the role of histone deacetylation in the light-regulated seed germination process and identified that HDA15-PIF1 acts as a key repression module directing the transcription network of seed germination. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

    Zaag, Rim; Tamby, Jean Philippe; Guichard, Cécile; Tariq, Zakia; Rigaill, Guillem; Delannoy, Etienne; Renou, Jean-Pierre; Balzergue, Sandrine; Mary-Huard, Tristan; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique

    2015-01-01

    CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Piles, tabs and overlaps in navigation among documents

    Jakobsen, Mikkel Rønne; Hornbæk, Kasper

    2010-01-01

    Navigation among documents is a frequent, but ill supported activity.